AI-Assisted Project Highlights and Camera Subsystem Development
Cursor AI Transcript · HTMAA 2025
Table of Contents
Overview
Cursor AI assisted with adding project highlights section and creating comprehensive camera subsystem documentation
Full Conversation
I'll help you add a project highlights section to the final project page and create the camera subsystem section with all the requested content. Let me start by examining the current final project page and the weekly pages to understand the formatting structure.
Let me read the weekly pages to understand the highlights format:
Now let me check the camera files to understand what content I need to work with:
Now let me create the todo list and start implementing the changes:
Now I'll start by adding the project highlights section to the final project page. Let me first find where to insert it:
I can see there's already a Project Highlights section. Let me add the camera highlights row to it. I'll insert it after the existing content but before the Vision Board section:
Final Project · HTMAA 2025 · Saleem A. Al Dajani
Final Project
Bioprinting & Aging Biomarker Device · HTMAA 2025
Project Highlights
Camera Works!
XIAO ESP32S3 camera successfully captures and displays images on OLED screen using Floyd-Steinberg dithering
Vision Board
Conceptual visualization of the multimodal intrinsic capacity assessment system integrating grip strength, voice analysis, facial recognition, video motion capture, reaction time measurement, and wearable accelerometer data.
Intrinsic Capacity (IC) Coverage by Digital Biomarkers
✅ Strong coverage |
🔸 Partial/indirect |
❌ Not covered |
View full table →
Multimodal IC Pipeline
Inputs: Grip Strength, Voice, Face, Video, Reaction Time, Wearable Accelerometer
Process: Feature extraction → Embeddings → Fusion layer → IC Score
Output: Overall Intrinsic Capacity Score + Domain sub-scores
Weekly System Development
Weeks 0-1: Project foundation, cutting techniques for device components
Weeks 2-4: Electronics foundation, embedded programming, PCB design
Weeks 5-7: Input devices, sensors for grip strength, voice, face detection
Weeks 8-10: Output devices, mechanical design, system integration
Weeks 11-13: Communication, UI development, final integration
Project Presentation
Summary Slide: [Placeholder for project summary slide download]
One Minute Video: [Placeholder for 1-minute video showing conception, construction, and operation]
Final Project Spiral Development Model
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Development Approach: Following the spiral model methodology, this final project will iterate through multiple development cycles, each building upon previous work while addressing new requirements and risks.
Cycle 1: Minimal viable project for class scope
Cycle 2: Core functionality expansion
Cycle 3: Advanced features and integration
Cycle 4: Future research applications
Table of Contents
Project Overview
Design & Development
Weekly Progress (Weeks 0-13)
• Week 0 - Introduction
• Week 1 - Cutting
• Week 2 - Programming
• Week 3 - 3D Printing
• Week 4 - Electronics Design
• Week 5 - Electronics Production
• Week 6 - Machining
• Week 7 - Input Devices
• Week 8 - Output Devices
• Week 9 - Molding & Casting
• Week 10 - Mechanical Design
• Week 11 - Networking
• Week 12 - Interface Programming
• Week 13 - Final Integration
Project Introduction
[Project introduction placeholder - describing the bioprinting and aging biomarker device project.]
[Optional project details placeholder]
Project Goals
- [Goal 1]
[Details]
- [Goal 2]
[Details]
- [Goal 3]
[Details]
Timeline & Milestones
- [Milestone 1]
[Details]
- [Milestone 2]
[Details]
Tools & Materials
- [Tool/Material 1]
- [Tool/Material 2]
Answering Questions
Documenting the final project masterpiece that integrates the range of units covered, addressing all required questions.
What does it do?
[Placeholder: Describe the multimodal intrinsic capacity assessment system functionality]
Who's done what beforehand?
[Placeholder: Literature review and prior work in aging biomarkers and intrinsic capacity assessment]
What sources did you use?
[Placeholder: Research papers, open-source projects, and reference materials]
What did you design?
[Placeholder: Custom hardware, software, and integration systems designed]
What materials and components were used?
[Placeholder: Complete list of materials, sensors, microcontrollers, and components]
Where did they come from?
[Placeholder: Suppliers, vendors, and sourcing information]
How much did they cost?
[Placeholder: Detailed cost breakdown and budget analysis]
What parts and systems were made?
[Placeholder: Custom fabricated parts, 3D printed components, and assembled systems]
What tools and processes were used?
[Placeholder: Laser cutting, 3D printing, PCB fabrication, programming, and testing processes]
What questions were answered?
[Placeholder: Research questions addressed and hypotheses tested]
What worked? What didn't?
[Placeholder: Successes, challenges, and lessons learned]
How was it evaluated?
[Placeholder: Testing protocols, validation methods, and evaluation criteria]
What are the implications?
[Placeholder: Impact on aging research, clinical applications, and future development]
Design
Your project should incorporate 2D and 3D design, multiple additive and subtractive fabrication processes, electronics design and production, embedded microcontroller design, interfacing, and programming, system integration and packaging.
2D Design
2D design work for the multimodal intrinsic capacity assessment system:
- [Placeholder: Laser cutting designs for device housing components]
- [Placeholder: Vinyl cutting designs for labels and UI elements]
- [Placeholder: PCB layout designs and schematics]
- [Placeholder: 2D technical drawings and assembly guides]
- [Placeholder: User interface mockups and wireframes]
Tools Used: Inkscape, KiCad, Adobe Illustrator, Figma
3D Design
3D design work for device components and integration:
- [Placeholder: 3D printed device housings and enclosures]
- [Placeholder: Custom sensor mounting brackets and fixtures]
- [Placeholder: Ergonomic grip strength measurement device]
- [Placeholder: Camera mounting systems for facial recognition]
- [Placeholder: Integrated system assembly and packaging]
Tools Used: Fusion 360, FreeCAD, OpenSCAD, PrusaSlicer
Fabrication Processes Integration
Additive: 3D printing for custom components
Subtractive: Laser cutting, milling for precision parts
Electronics: PCB design and production
Programming: Embedded microcontroller development
Bill of Materials
Where possible, you should make rather than buy the parts of your project. Complete breakdown of materials, components, and sourcing information.
Bill of Materials
Complete list of materials and components:
Electronics Components
- [Placeholder: Microcontrollers and development boards]
- [Placeholder: Sensors (force, accelerometer, microphone)]
- [Placeholder: Camera modules and display components]
- [Placeholder: Power management and connectivity modules]
Mechanical Components
- [Placeholder: 3D printing materials (PLA, PETG)]
- [Placeholder: Laser cutting materials (acrylic, wood)]
- [Placeholder: Fasteners and mounting hardware]
- [Placeholder: Enclosure and housing materials]
Cost Breakdown
[Placeholder: Detailed cost analysis and budget tracking]
Make vs Buy
Strategic decisions on fabrication vs. purchasing:
✅ Made Components
- [Placeholder: Custom 3D printed housings]
- [Placeholder: Laser cut mounting brackets]
- [Placeholder: Custom PCB designs]
- [Placeholder: Integrated sensor assemblies]
🔸 Modified Components
- [Placeholder: Open-source grip strength meter adaptation]
- [Placeholder: Commercial sensor integration]
- [Placeholder: Existing microcontroller customization]
❌ Purchased Components
- [Placeholder: Standard electronic components]
- [Placeholder: Commercial sensors and modules]
- [Placeholder: Development boards and tools]
Fabrication Process
[Fabrication process documentation placeholder.]
Testing & Validation
[Testing and validation documentation placeholder.]
Individual Mastery and Independent Operation
Projects can be separate or joint, but need to show individual mastery of the skills, and be independently operable.
Individual Mastery
Demonstration of individual skills across all course units:
2D and 3D Design
- [Placeholder: Individual CAD modeling and design work]
- [Placeholder: Personal contribution to design decisions]
Fabrication Processes
- [Placeholder: Personal hands-on fabrication work]
- [Placeholder: Individual mastery of tools and processes]
Electronics and Programming
- [Placeholder: Individual PCB design and programming]
- [Placeholder: Personal debugging and troubleshooting]
Independent Operation
Project operates independently without external dependencies:
✅ Standalone Functionality
- [Placeholder: Complete system integration]
- [Placeholder: Self-contained operation]
- [Placeholder: Independent data collection and processing]
✅ User Independence
- [Placeholder: User-friendly interface]
- [Placeholder: Clear operation instructions]
- [Placeholder: Minimal external assistance required]
✅ Documentation
- [Placeholder: Complete technical documentation]
- [Placeholder: Assembly and operation guides]
- [Placeholder: Troubleshooting and maintenance]
Course Presentation
Present your final project, weekly and group assignments, and documentation.
Final Project Presentation
Complete presentation of the multimodal intrinsic capacity assessment system:
- [Placeholder: Final project demonstration]
- [Placeholder: Technical documentation presentation]
- [Placeholder: Results and evaluation discussion]
Weekly Assignments
Integration of weekly work into final project:
- [Placeholder: Week-by-week contribution summary]
- [Placeholder: Skills demonstration across all units]
- [Placeholder: Progressive development documentation]
Group Assignments
Collaborative work and individual contributions:
- [Placeholder: Group project contributions]
- [Placeholder: Individual role and responsibilities]
- [Placeholder: Collaborative learning outcomes]
Useful Documentation
Helpful resources, documentation, and design files for the multimodal intrinsic capacity assessment system.
Open Source Grip Strength Meter
A cost-effective $50 grip strength measurement system that can be further optimized for our multimodal assessment platform.
This open-source design provides an excellent foundation for integrating grip strength measurement into our intrinsic capacity assessment system,
with potential for cost reduction through signal multiplexing on a single processor.
Available Resources:
- Complete design files and schematics
- Arduino-based firmware and code repository
- 3D printing files for device housing
- Assembly instructions and documentation
- Calibration procedures and testing protocols
- Integration examples for data collection systems
Complete Intrinsic Capacity Coverage Analysis
Comprehensive analysis of how different digital biomarkers cover the five domains of intrinsic capacity (IC) as defined by WHO.
Legend:
✅ Strong coverage |
🔸 Partial/indirect coverage |
❌ Not covered
Multimodal Intrinsic Capacity Pipeline
Detailed technical pipeline for processing multiple digital biomarkers to generate intrinsic capacity scores.
Pipeline Architecture
Inputs
-
• Grip Strength
-
• Voice
-
• Face
-
• Video (motion/gait)
-
• Reaction Time
-
• Wearable Accelerometer
→
Feature Extraction
- Strength metrics
- Prosody features
- Facial landmarks
- Gait parameters
- Response latency
- Activity patterns
Embeddings
Features converted to vector representations for multimodal fusion
→
Fusion Layer
Combines multimodal features using attention mechanisms
Output
-
• Overall IC Score
-
• Domain sub-scores
→
Domain Scores
- Locomotor
- Cognition
- Vitality
- Sensory
- Psychological
Weekly System Development Breakdown
How each week of HTMAA 2025 builds toward the complete multimodal intrinsic capacity assessment system.
Week 0: Project Ideation
Initial concept development and planning
- Project planning and documentation structure
- Research direction and concept sketches
Week 1: Precision Cutting
Laser and vinyl cutting techniques
- Device housing components via laser cutting
- Sensor mounting brackets and enclosures
- Vinyl cutting for device labeling and UI elements
Week 2: Embedded Programming
Electronics basics and microcontroller programming
- Microcontroller programming for data collection
- Basic sensor interface circuits
Week 3: 3D Scanning & Printing
3D technologies for device components
- 3D scanning for custom component design
- 3D printing for device housings
Week 4: Electronics Design
EDA and schematic design
- PCB design for grip strength measurement
- Sensor interface circuits and signal conditioning
- Power management and data storage systems
Week 5: Electronics Production
PCB fabrication and assembly
- PCB fabrication and debugging
- Component assembly and testing
Week 6: Computer-controlled Machining
CAM and precision milling
- Precision components via milling
- Custom mechanical parts
Week 7: Input Devices
Sensor integration for data collection
- Force sensors for grip strength measurement
- Microphones for voice analysis
- Camera systems for facial expression analysis
- Reaction time measurement circuits
Week 8: Output Devices
Actuators and system integration
- Display systems for real-time feedback
- Haptic feedback for user interaction
Week 9: Molding & Casting
Forming and resin techniques
- 3D printing and molding for custom components
- Bioprinting molds and device components
Week 10: Mechanical & Machine Design
System integration and mechanical design
- Mechanical design for ergonomic device housing
- System integration and calibration protocols
Week 11: Networking & Communications
Connectivity and communication protocols
- Bluetooth/Wi-Fi connectivity for data transmission
- Wearable accelerometer integration and data fusion
Week 12: Interface & Application Programming
UI development and application programming
- Mobile app development for user interface
- Cloud integration for data storage and analysis
- Machine learning pipeline for IC score calculation
Week 13: Wildcard & Final Integration
Final orders and complete system deployment
- Final testing, validation, and documentation
- System integration and deployment
Week 0 - Introduction & Design
Project ideation and initial concept development for bioprinting rejuvenated tissue and aging biomarker devices.
Project planning
Concept sketches
Research direction
System Integration Plans: Establish the foundational architecture for multimodal data collection by designing the overall system framework that will integrate all six digital biomarkers (grip strength, voice, face, video, reaction time, wearable accelerometer) into a cohesive intrinsic capacity assessment platform.
[Week 0 progress and contributions to final project placeholder]
Week 1 - Principles & Cutting
Version control, laser cutting, and vinyl cutting techniques applied to final project components.
Laser cutting
Vinyl cutting
Version control
System Integration Plans: Fabricate precision-cut housing components and mounting brackets for all sensor modules (force sensors, microphones, cameras, reaction time circuits) using laser cutting, while creating vinyl-cut labels and UI elements for device identification and user guidance.
[Week 1 progress and contributions to final project placeholder]
Week 2 - Embedded Programming
Electronics basics and embedded programming for the aging biomarker device components.
Microcontrollers
Programming
Electronics
System Integration Plans: Develop embedded programming protocols for real-time data collection from all six biomarker sensors, implementing initial signal processing algorithms and establishing the communication framework for multimodal data fusion.
[Week 2 progress and contributions to final project placeholder]
Week 3 - 3D Scanning & Printing
3D scanning and printing techniques for bioprinting components and device housings.
3D scanning
3D printing
AI tools
System Integration Plans: Create custom 3D-printed components for camera mounting systems and facial recognition hardware, while developing 3D scanning protocols for ergonomic device design that accommodates all sensor modalities in a user-friendly form factor.
[Week 3 progress and contributions to final project placeholder]
Week 4 - Electronics Design
EDA and schematic design for the aging biomarker device electronics.
EDA tools
Schematic design
Circuit design
System Integration Plans: Design comprehensive PCB schematics that integrate force sensor circuits for grip strength measurement, microphone preamplifiers for voice analysis, camera interfaces for facial recognition, and timing circuits for reaction time assessment into a unified electronics platform.
[Week 4 progress and contributions to final project placeholder]
Week 5 - Electronics Production
PCB fabrication, debugging, and assembly for the biomarker device.
PCB fabrication
Debugging
Assembly
System Integration Plans: Fabricate and assemble the integrated PCB containing all sensor interfaces, implementing power management systems for continuous operation and establishing data storage protocols for the multimodal biomarker data collection system.
[Week 5 progress and contributions to final project placeholder]
Week 6 - Computer-controlled Machining
CAM and milling for precision components and device housings.
CAM
Milling
Precision machining
System Integration Plans: Machine precision mechanical components for the integrated device housing using computer-controlled milling, ensuring proper alignment and mounting for all sensor modules while maintaining ergonomic design for user comfort during multimodal data collection.
[Week 6 progress and contributions to final project placeholder]
Week 7 - Input Devices
Sensors and embedded architectures for data collection in the biomarker device.
Sensors
Input devices
Data collection
System Integration Plans: Integrate all six input sensor systems (force sensors for grip strength, microphones for voice analysis, cameras for facial recognition and gait analysis, reaction time circuits, and wearable accelerometer) into the unified data collection platform with real-time processing capabilities.
[Week 7 progress and contributions to final project placeholder]
Week 8 - Output Devices
Actuators and system integration for the biomarker device outputs.
Actuators
Output devices
System integration
System Integration Plans: Implement output devices including display systems for real-time intrinsic capacity feedback and haptic feedback mechanisms for user interaction, creating an intuitive interface for the multimodal biomarker assessment system.
[Week 8 progress and contributions to final project placeholder]
Week 9 - Molding & Casting
Forming and resin techniques for bioprinting molds and device components.
Molding
Casting
Resins
System Integration Plans: Create custom molded components for the bioprinting aspects of the project and develop specialized casings for sensor protection, ensuring the device can withstand continuous use during multimodal data collection sessions.
[Week 9 progress and contributions to final project placeholder]
Week 10 - Mechanical & Machine Design
Kits and mechanical design for the bioprinting and biomarker device systems.
Mechanical design
Machine design
System integration
System Integration Plans: Complete the mechanical design integration of all system components, implementing calibration protocols for sensor alignment and developing the complete mechanical framework that houses all six digital biomarker measurement systems.
[Week 10 progress and contributions to final project placeholder]
Week 11 - Networking & Communications
BLE, Wi-Fi, and communication protocols for the biomarker device connectivity.
BLE
Wi-Fi
Communications
System Integration Plans: Implement wireless communication protocols (Bluetooth/Wi-Fi) for seamless data transmission from all six sensor modalities, enabling real-time data fusion and establishing connectivity for the wearable accelerometer integration into the multimodal assessment system.
[Week 11 progress and contributions to final project placeholder]
Week 12 - Interface & Application Programming
UI and application development for the biomarker device interface.
UI design
Applications
User interface
System Integration Plans: Develop the complete user interface and application programming for the multimodal system, implementing the machine learning pipeline for intrinsic capacity score calculation and creating cloud integration for comprehensive data storage and analysis of all biomarker measurements.
[Week 12 progress and contributions to final project placeholder]
Week 13 - Wildcard & Final Orders
Final orders and wildcard week activities for project completion.
Final orders
Wildcard activities
Project completion
System Integration Plans: Complete final system integration, testing, and validation of the complete multimodal intrinsic capacity assessment platform, ensuring all six digital biomarkers work cohesively to provide accurate WHO-defined intrinsic capacity scores across all five domains (locomotor, cognition, vitality, sensory, psychological).
[Week 13 progress and contributions to final project placeholder]
Design Files
[Links to CAD/SVG/assets placeholder.]
Reflections & Learnings
[Reflection notes placeholder.]
Contributions
Acknowledgements and contributions that made this project possible.
Gladyshev Lab and Collaborators
Special thanks to the Gladyshev Lab and collaborators for the fruitful discussions that led to this multimodal intrinsic capacity assessment idea,
which supplements my PhD research goals in aging and longevity. The conceptual framework for integrating multiple digital biomarkers
to assess intrinsic capacity domains emerged from collaborative research discussions on aging biomarkers and healthspan assessment.
Ethical AI Use
Transparent documentation of AI assistance used in this final project work, following course guidelines for ethical AI usage.
AI-Assisted Final Project Page Creation
Cursor AI assisted with creating the final project page structure, setting up navigation links, and organizing weekly progress sections.
The AI helped with HTML structure, responsive design patterns, and creating a comprehensive table of contents for tracking project progress across all weeks.
AI-Assisted Intrinsic Capacity Research & Design
ChatGPT was used to research and develop the multimodal intrinsic capacity assessment framework, including the comprehensive coverage analysis table and technical pipeline design.
The AI assisted with structuring the WHO-defined intrinsic capacity domains, identifying appropriate digital biomarkers, and designing the fusion architecture for multimodal data processing.
AI-Assisted Final Project Development
Cursor AI assisted with developing the complete final project page structure, implementing the multimodal intrinsic capacity assessment framework, and creating comprehensive documentation.
The AI helped with HTML structure, responsive design, weekly system integration plans, and organizing the technical documentation for the complete biomarker assessment system.
AI-Assisted Final Project Presentation Structure
Cursor AI assisted with finalizing the project presentation structure to ensure full compliance with MIT Academy project presentation requirements.
The AI helped implement all required sections including answering questions, design documentation, bill of materials, individual mastery requirements,
course presentation structure, and spiral model development approach visualization.
This work is licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
Now I need to add the camera subsystem section. Let me find a good place to insert it, probably after the existing sections but before the weekly progress sections:
Perfect! I'll add the camera subsystem section right before the "Weekly Progress Sections" comment. Let me insert it there:
Final Project · HTMAA 2025 · Saleem A. Al Dajani
Final Project
Bioprinting & Aging Biomarker Device · HTMAA 2025
Project Highlights
Camera Works!
XIAO ESP32S3 camera successfully captures and displays images on OLED screen using Floyd-Steinberg dithering
Vision Board
Conceptual visualization of the multimodal intrinsic capacity assessment system integrating grip strength, voice analysis, facial recognition, video motion capture, reaction time measurement, and wearable accelerometer data.
Intrinsic Capacity (IC) Coverage by Digital Biomarkers
✅ Strong coverage |
🔸 Partial/indirect |
❌ Not covered |
View full table →
Multimodal IC Pipeline
Inputs: Grip Strength, Voice, Face, Video, Reaction Time, Wearable Accelerometer
Process: Feature extraction → Embeddings → Fusion layer → IC Score
Output: Overall Intrinsic Capacity Score + Domain sub-scores
Weekly System Development
Weeks 0-1: Project foundation, cutting techniques for device components
Weeks 2-4: Electronics foundation, embedded programming, PCB design
Weeks 5-7: Input devices, sensors for grip strength, voice, face detection
Weeks 8-10: Output devices, mechanical design, system integration
Weeks 11-13: Communication, UI development, final integration
Project Presentation
Summary Slide: [Placeholder for project summary slide download]
One Minute Video: [Placeholder for 1-minute video showing conception, construction, and operation]
Final Project Spiral Development Model
Development Approach: Following the spiral model methodology, this final project will iterate through multiple development cycles, each building upon previous work while addressing new requirements and risks.
Cycle 1: Minimal viable project for class scope
Cycle 2: Core functionality expansion
Cycle 3: Advanced features and integration
Cycle 4: Future research applications
Table of Contents
Project Overview
Design & Development
Weekly Progress (Weeks 0-13)
• Week 0 - Introduction
• Week 1 - Cutting
• Week 2 - Programming
• Week 3 - 3D Printing
• Week 4 - Electronics Design
• Week 5 - Electronics Production
• Week 6 - Machining
• Week 7 - Input Devices
• Week 8 - Output Devices
• Week 9 - Molding & Casting
• Week 10 - Mechanical Design
• Week 11 - Networking
• Week 12 - Interface Programming
• Week 13 - Final Integration
Project Introduction
[Project introduction placeholder - describing the bioprinting and aging biomarker device project.]
[Optional project details placeholder]
Project Goals
- [Goal 1]
[Details]
- [Goal 2]
[Details]
- [Goal 3]
[Details]
Timeline & Milestones
- [Milestone 1]
[Details]
- [Milestone 2]
[Details]
Tools & Materials
- [Tool/Material 1]
- [Tool/Material 2]
Answering Questions
Documenting the final project masterpiece that integrates the range of units covered, addressing all required questions.
What does it do?
[Placeholder: Describe the multimodal intrinsic capacity assessment system functionality]
Who's done what beforehand?
[Placeholder: Literature review and prior work in aging biomarkers and intrinsic capacity assessment]
What sources did you use?
[Placeholder: Research papers, open-source projects, and reference materials]
What did you design?
[Placeholder: Custom hardware, software, and integration systems designed]
What materials and components were used?
[Placeholder: Complete list of materials, sensors, microcontrollers, and components]
Where did they come from?
[Placeholder: Suppliers, vendors, and sourcing information]
How much did they cost?
[Placeholder: Detailed cost breakdown and budget analysis]
What parts and systems were made?
[Placeholder: Custom fabricated parts, 3D printed components, and assembled systems]
What tools and processes were used?
[Placeholder: Laser cutting, 3D printing, PCB fabrication, programming, and testing processes]
What questions were answered?
[Placeholder: Research questions addressed and hypotheses tested]
What worked? What didn't?
[Placeholder: Successes, challenges, and lessons learned]
How was it evaluated?
[Placeholder: Testing protocols, validation methods, and evaluation criteria]
What are the implications?
[Placeholder: Impact on aging research, clinical applications, and future development]
Design
Your project should incorporate 2D and 3D design, multiple additive and subtractive fabrication processes, electronics design and production, embedded microcontroller design, interfacing, and programming, system integration and packaging.
2D Design
2D design work for the multimodal intrinsic capacity assessment system:
- [Placeholder: Laser cutting designs for device housing components]
- [Placeholder: Vinyl cutting designs for labels and UI elements]
- [Placeholder: PCB layout designs and schematics]
- [Placeholder: 2D technical drawings and assembly guides]
- [Placeholder: User interface mockups and wireframes]
Tools Used: Inkscape, KiCad, Adobe Illustrator, Figma
3D Design
3D design work for device components and integration:
- [Placeholder: 3D printed device housings and enclosures]
- [Placeholder: Custom sensor mounting brackets and fixtures]
- [Placeholder: Ergonomic grip strength measurement device]
- [Placeholder: Camera mounting systems for facial recognition]
- [Placeholder: Integrated system assembly and packaging]
Tools Used: Fusion 360, FreeCAD, OpenSCAD, PrusaSlicer
Fabrication Processes Integration
Additive: 3D printing for custom components
Subtractive: Laser cutting, milling for precision parts
Electronics: PCB design and production
Programming: Embedded microcontroller development
Bill of Materials
Where possible, you should make rather than buy the parts of your project. Complete breakdown of materials, components, and sourcing information.
Bill of Materials
Complete list of materials and components:
Electronics Components
- [Placeholder: Microcontrollers and development boards]
- [Placeholder: Sensors (force, accelerometer, microphone)]
- [Placeholder: Camera modules and display components]
- [Placeholder: Power management and connectivity modules]
Mechanical Components
- [Placeholder: 3D printing materials (PLA, PETG)]
- [Placeholder: Laser cutting materials (acrylic, wood)]
- [Placeholder: Fasteners and mounting hardware]
- [Placeholder: Enclosure and housing materials]
Cost Breakdown
[Placeholder: Detailed cost analysis and budget tracking]
Make vs Buy
Strategic decisions on fabrication vs. purchasing:
✅ Made Components
- [Placeholder: Custom 3D printed housings]
- [Placeholder: Laser cut mounting brackets]
- [Placeholder: Custom PCB designs]
- [Placeholder: Integrated sensor assemblies]
🔸 Modified Components
- [Placeholder: Open-source grip strength meter adaptation]
- [Placeholder: Commercial sensor integration]
- [Placeholder: Existing microcontroller customization]
❌ Purchased Components
- [Placeholder: Standard electronic components]
- [Placeholder: Commercial sensors and modules]
- [Placeholder: Development boards and tools]
Fabrication Process
[Fabrication process documentation placeholder.]
Testing & Validation
[Testing and validation documentation placeholder.]
Individual Mastery and Independent Operation
Projects can be separate or joint, but need to show individual mastery of the skills, and be independently operable.
Individual Mastery
Demonstration of individual skills across all course units:
2D and 3D Design
- [Placeholder: Individual CAD modeling and design work]
- [Placeholder: Personal contribution to design decisions]
Fabrication Processes
- [Placeholder: Personal hands-on fabrication work]
- [Placeholder: Individual mastery of tools and processes]
Electronics and Programming
- [Placeholder: Individual PCB design and programming]
- [Placeholder: Personal debugging and troubleshooting]
Independent Operation
Project operates independently without external dependencies:
✅ Standalone Functionality
- [Placeholder: Complete system integration]
- [Placeholder: Self-contained operation]
- [Placeholder: Independent data collection and processing]
✅ User Independence
- [Placeholder: User-friendly interface]
- [Placeholder: Clear operation instructions]
- [Placeholder: Minimal external assistance required]
✅ Documentation
- [Placeholder: Complete technical documentation]
- [Placeholder: Assembly and operation guides]
- [Placeholder: Troubleshooting and maintenance]
Course Presentation
Present your final project, weekly and group assignments, and documentation.
Final Project Presentation
Complete presentation of the multimodal intrinsic capacity assessment system:
- [Placeholder: Final project demonstration]
- [Placeholder: Technical documentation presentation]
- [Placeholder: Results and evaluation discussion]
Weekly Assignments
Integration of weekly work into final project:
- [Placeholder: Week-by-week contribution summary]
- [Placeholder: Skills demonstration across all units]
- [Placeholder: Progressive development documentation]
Group Assignments
Collaborative work and individual contributions:
- [Placeholder: Group project contributions]
- [Placeholder: Individual role and responsibilities]
- [Placeholder: Collaborative learning outcomes]
Useful Documentation
Helpful resources, documentation, and design files for the multimodal intrinsic capacity assessment system.
Open Source Grip Strength Meter
A cost-effective $50 grip strength measurement system that can be further optimized for our multimodal assessment platform.
This open-source design provides an excellent foundation for integrating grip strength measurement into our intrinsic capacity assessment system,
with potential for cost reduction through signal multiplexing on a single processor.
Available Resources:
- Complete design files and schematics
- Arduino-based firmware and code repository
- 3D printing files for device housing
- Assembly instructions and documentation
- Calibration procedures and testing protocols
- Integration examples for data collection systems
Complete Intrinsic Capacity Coverage Analysis
Comprehensive analysis of how different digital biomarkers cover the five domains of intrinsic capacity (IC) as defined by WHO.
Legend:
✅ Strong coverage |
🔸 Partial/indirect coverage |
❌ Not covered
Multimodal Intrinsic Capacity Pipeline
Detailed technical pipeline for processing multiple digital biomarkers to generate intrinsic capacity scores.
Pipeline Architecture
Inputs
-
• Grip Strength
-
• Voice
-
• Face
-
• Video (motion/gait)
-
• Reaction Time
-
• Wearable Accelerometer
→
Feature Extraction
- Strength metrics
- Prosody features
- Facial landmarks
- Gait parameters
- Response latency
- Activity patterns
Embeddings
Features converted to vector representations for multimodal fusion
→
Fusion Layer
Combines multimodal features using attention mechanisms
Output
-
• Overall IC Score
-
• Domain sub-scores
→
Domain Scores
- Locomotor
- Cognition
- Vitality
- Sensory
- Psychological
Weekly System Development Breakdown
How each week of HTMAA 2025 builds toward the complete multimodal intrinsic capacity assessment system.
Week 0: Project Ideation
Initial concept development and planning
- Project planning and documentation structure
- Research direction and concept sketches
Week 1: Precision Cutting
Laser and vinyl cutting techniques
- Device housing components via laser cutting
- Sensor mounting brackets and enclosures
- Vinyl cutting for device labeling and UI elements
Week 2: Embedded Programming
Electronics basics and microcontroller programming
- Microcontroller programming for data collection
- Basic sensor interface circuits
Week 3: 3D Scanning & Printing
3D technologies for device components
- 3D scanning for custom component design
- 3D printing for device housings
Week 4: Electronics Design
EDA and schematic design
- PCB design for grip strength measurement
- Sensor interface circuits and signal conditioning
- Power management and data storage systems
Week 5: Electronics Production
PCB fabrication and assembly
- PCB fabrication and debugging
- Component assembly and testing
Week 6: Computer-controlled Machining
CAM and precision milling
- Precision components via milling
- Custom mechanical parts
Week 7: Input Devices
Sensor integration for data collection
- Force sensors for grip strength measurement
- Microphones for voice analysis
- Camera systems for facial expression analysis
- Reaction time measurement circuits
Week 8: Output Devices
Actuators and system integration
- Display systems for real-time feedback
- Haptic feedback for user interaction
Week 9: Molding & Casting
Forming and resin techniques
- 3D printing and molding for custom components
- Bioprinting molds and device components
Week 10: Mechanical & Machine Design
System integration and mechanical design
- Mechanical design for ergonomic device housing
- System integration and calibration protocols
Week 11: Networking & Communications
Connectivity and communication protocols
- Bluetooth/Wi-Fi connectivity for data transmission
- Wearable accelerometer integration and data fusion
Week 12: Interface & Application Programming
UI development and application programming
- Mobile app development for user interface
- Cloud integration for data storage and analysis
- Machine learning pipeline for IC score calculation
Week 13: Wildcard & Final Integration
Final orders and complete system deployment
- Final testing, validation, and documentation
- System integration and deployment
Camera Subsystem
Advanced camera system implementation using XIAO ESP32S3 Sense with real-time image processing, EdgeAI integration, and interactive selfie capture functionality.
System Overview
The camera system successfully captures images, processes them into bitmaps, and displays them on an OLED screen using advanced Floyd-Steinberg dithering algorithms.
Video Demonstrations
Camera Bot Selfie
Demonstration of the interactive selfie capture system with touch controls
Picture of Picture
Meta demonstration showing the camera system capturing its own display
Code Implementation
60-Second Auto Capture System
Automated camera system that captures and displays images every 60 seconds using advanced image processing techniques.
Pseudocode Implementation:
1. Initialize camera with PSRAM frame buffers
2. Configure OLED display (128x64 pixels)
3. Set up 60-second capture interval timer
4. In main loop:
a. Check if 60 seconds have elapsed
b. Capture image from camera
c. Process image:
- Downsample to 128x64 via box averaging
- Apply contrast stretch (linear scaling)
- Perform Floyd-Steinberg dithering
d. Display processed bitmap on OLED
e. Release frame buffer
5. Repeat process
Touch-Controlled Capture System
Interactive camera system with touch controls allowing manual capture triggers in addition to automatic timing.
Pseudocode Implementation:
1. Initialize camera and OLED display
2. Set up touch pins (GPIO1 & GPIO2) with threshold detection
3. Configure 60-second auto-capture timer
4. In main loop:
a. Update touch sensor readings
b. Detect touch press events (justPressed)
c. Check for capture trigger:
- Touch press OR 60-second timer elapsed
d. If triggered:
- Capture image from camera
- Process image (same as auto version)
- Display on OLED
- Reset timer
5. Continue monitoring for next trigger
How It Was Done
The camera system implementation began with code from Charles Lu's electronics production weekly assignment,
which was based on the official XIAO tutorial.
Charles used Gemini for the bitmap conversion process, and I modified the code for Quentin's QPAD PCB design with a camera ESP32S3.
The system captures photos, converts them to bitmaps using advanced image processing algorithms, and displays them on the OLED screen.
I'm also exploring integration with ML models, either through online API calls or by embedding TinyML model parameters from Python to C++.
Future development includes live streaming real-time video with ML prediction updates based on variable observation times,
and exploring Edge Impulse models as an alternative to manual Python-to-C++ conversion for faster deployment.
EdgeAI/TinyML Integration
Edge AI can also be implemented using Edge Impulse models, which may be faster than manually converting Python models to C++.
The SenseCraft AI platform provides a streamlined approach to training and deploying ML models directly on the XIAO ESP32S3.
Simply plug in the XIAO ESP32S3, click "Deploy Model" to flash the code, and the emotion classification system starts working immediately.
Development Discussion: ChatGPT Session on Camera System Development
Week 0 - Introduction & Design
Project ideation and initial concept development for bioprinting rejuvenated tissue and aging biomarker devices.
Project planning
Concept sketches
Research direction
System Integration Plans: Establish the foundational architecture for multimodal data collection by designing the overall system framework that will integrate all six digital biomarkers (grip strength, voice, face, video, reaction time, wearable accelerometer) into a cohesive intrinsic capacity assessment platform.
[Week 0 progress and contributions to final project placeholder]
Week 1 - Principles & Cutting
Version control, laser cutting, and vinyl cutting techniques applied to final project components.
Laser cutting
Vinyl cutting
Version control
System Integration Plans: Fabricate precision-cut housing components and mounting brackets for all sensor modules (force sensors, microphones, cameras, reaction time circuits) using laser cutting, while creating vinyl-cut labels and UI elements for device identification and user guidance.
[Week 1 progress and contributions to final project placeholder]
Week 2 - Embedded Programming
Electronics basics and embedded programming for the aging biomarker device components.
Microcontrollers
Programming
Electronics
System Integration Plans: Develop embedded programming protocols for real-time data collection from all six biomarker sensors, implementing initial signal processing algorithms and establishing the communication framework for multimodal data fusion.
[Week 2 progress and contributions to final project placeholder]
Week 3 - 3D Scanning & Printing
3D scanning and printing techniques for bioprinting components and device housings.
3D scanning
3D printing
AI tools
System Integration Plans: Create custom 3D-printed components for camera mounting systems and facial recognition hardware, while developing 3D scanning protocols for ergonomic device design that accommodates all sensor modalities in a user-friendly form factor.
[Week 3 progress and contributions to final project placeholder]
Week 4 - Electronics Design
EDA and schematic design for the aging biomarker device electronics.
EDA tools
Schematic design
Circuit design
System Integration Plans: Design comprehensive PCB schematics that integrate force sensor circuits for grip strength measurement, microphone preamplifiers for voice analysis, camera interfaces for facial recognition, and timing circuits for reaction time assessment into a unified electronics platform.
[Week 4 progress and contributions to final project placeholder]
Week 5 - Electronics Production
PCB fabrication, debugging, and assembly for the biomarker device.
PCB fabrication
Debugging
Assembly
System Integration Plans: Fabricate and assemble the integrated PCB containing all sensor interfaces, implementing power management systems for continuous operation and establishing data storage protocols for the multimodal biomarker data collection system.
[Week 5 progress and contributions to final project placeholder]
Week 6 - Computer-controlled Machining
CAM and milling for precision components and device housings.
CAM
Milling
Precision machining
System Integration Plans: Machine precision mechanical components for the integrated device housing using computer-controlled milling, ensuring proper alignment and mounting for all sensor modules while maintaining ergonomic design for user comfort during multimodal data collection.
[Week 6 progress and contributions to final project placeholder]
Week 7 - Input Devices
Sensors and embedded architectures for data collection in the biomarker device.
Sensors
Input devices
Data collection
System Integration Plans: Integrate all six input sensor systems (force sensors for grip strength, microphones for voice analysis, cameras for facial recognition and gait analysis, reaction time circuits, and wearable accelerometer) into the unified data collection platform with real-time processing capabilities.
[Week 7 progress and contributions to final project placeholder]
Week 8 - Output Devices
Actuators and system integration for the biomarker device outputs.
Actuators
Output devices
System integration
System Integration Plans: Implement output devices including display systems for real-time intrinsic capacity feedback and haptic feedback mechanisms for user interaction, creating an intuitive interface for the multimodal biomarker assessment system.
[Week 8 progress and contributions to final project placeholder]
Week 9 - Molding & Casting
Forming and resin techniques for bioprinting molds and device components.
Molding
Casting
Resins
System Integration Plans: Create custom molded components for the bioprinting aspects of the project and develop specialized casings for sensor protection, ensuring the device can withstand continuous use during multimodal data collection sessions.
[Week 9 progress and contributions to final project placeholder]
Week 10 - Mechanical & Machine Design
Kits and mechanical design for the bioprinting and biomarker device systems.
Mechanical design
Machine design
System integration
System Integration Plans: Complete the mechanical design integration of all system components, implementing calibration protocols for sensor alignment and developing the complete mechanical framework that houses all six digital biomarker measurement systems.
[Week 10 progress and contributions to final project placeholder]
Week 11 - Networking & Communications
BLE, Wi-Fi, and communication protocols for the biomarker device connectivity.
BLE
Wi-Fi
Communications
System Integration Plans: Implement wireless communication protocols (Bluetooth/Wi-Fi) for seamless data transmission from all six sensor modalities, enabling real-time data fusion and establishing connectivity for the wearable accelerometer integration into the multimodal assessment system.
[Week 11 progress and contributions to final project placeholder]
Week 12 - Interface & Application Programming
UI and application development for the biomarker device interface.
UI design
Applications
User interface
System Integration Plans: Develop the complete user interface and application programming for the multimodal system, implementing the machine learning pipeline for intrinsic capacity score calculation and creating cloud integration for comprehensive data storage and analysis of all biomarker measurements.
[Week 12 progress and contributions to final project placeholder]
Week 13 - Wildcard & Final Orders
Final orders and wildcard week activities for project completion.
Final orders
Wildcard activities
Project completion
System Integration Plans: Complete final system integration, testing, and validation of the complete multimodal intrinsic capacity assessment platform, ensuring all six digital biomarkers work cohesively to provide accurate WHO-defined intrinsic capacity scores across all five domains (locomotor, cognition, vitality, sensory, psychological).
[Week 13 progress and contributions to final project placeholder]
Design Files
[Links to CAD/SVG/assets placeholder.]
Reflections & Learnings
[Reflection notes placeholder.]
Contributions
Acknowledgements and contributions that made this project possible.
Gladyshev Lab and Collaborators
Special thanks to the Gladyshev Lab and collaborators for the fruitful discussions that led to this multimodal intrinsic capacity assessment idea,
which supplements my PhD research goals in aging and longevity. The conceptual framework for integrating multiple digital biomarkers
to assess intrinsic capacity domains emerged from collaborative research discussions on aging biomarkers and healthspan assessment.
Ethical AI Use
Transparent documentation of AI assistance used in this final project work, following course guidelines for ethical AI usage.
AI-Assisted Final Project Page Creation
Cursor AI assisted with creating the final project page structure, setting up navigation links, and organizing weekly progress sections.
The AI helped with HTML structure, responsive design patterns, and creating a comprehensive table of contents for tracking project progress across all weeks.
AI-Assisted Intrinsic Capacity Research & Design
ChatGPT was used to research and develop the multimodal intrinsic capacity assessment framework, including the comprehensive coverage analysis table and technical pipeline design.
The AI assisted with structuring the WHO-defined intrinsic capacity domains, identifying appropriate digital biomarkers, and designing the fusion architecture for multimodal data processing.
AI-Assisted Final Project Development
Cursor AI assisted with developing the complete final project page structure, implementing the multimodal intrinsic capacity assessment framework, and creating comprehensive documentation.
The AI helped with HTML structure, responsive design, weekly system integration plans, and organizing the technical documentation for the complete biomarker assessment system.
AI-Assisted Final Project Presentation Structure
Cursor AI assisted with finalizing the project presentation structure to ensure full compliance with MIT Academy project presentation requirements.
The AI helped implement all required sections including answering questions, design documentation, bill of materials, individual mastery requirements,
course presentation structure, and spiral model development approach visualization.
This work is licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
Now I need to add the ChatGPT session link to the Ethical AI Use section as well. Let me find that section:
Let me add the ChatGPT session link to the Ethical AI Use section. I'll add it as a new subsection:
Final Project · HTMAA 2025 · Saleem A. Al Dajani
Final Project
Bioprinting & Aging Biomarker Device · HTMAA 2025
Project Highlights
Camera Works!
XIAO ESP32S3 camera successfully captures and displays images on OLED screen using Floyd-Steinberg dithering
Vision Board
Conceptual visualization of the multimodal intrinsic capacity assessment system integrating grip strength, voice analysis, facial recognition, video motion capture, reaction time measurement, and wearable accelerometer data.
Intrinsic Capacity (IC) Coverage by Digital Biomarkers
✅ Strong coverage |
🔸 Partial/indirect |
❌ Not covered |
View full table →
Multimodal IC Pipeline
Inputs: Grip Strength, Voice, Face, Video, Reaction Time, Wearable Accelerometer
Process: Feature extraction → Embeddings → Fusion layer → IC Score
Output: Overall Intrinsic Capacity Score + Domain sub-scores
Weekly System Development
Weeks 0-1: Project foundation, cutting techniques for device components
Weeks 2-4: Electronics foundation, embedded programming, PCB design
Weeks 5-7: Input devices, sensors for grip strength, voice, face detection
Weeks 8-10: Output devices, mechanical design, system integration
Weeks 11-13: Communication, UI development, final integration
Project Presentation
Summary Slide: [Placeholder for project summary slide download]
One Minute Video: [Placeholder for 1-minute video showing conception, construction, and operation]
Final Project Spiral Development Model
Development Approach: Following the spiral model methodology, this final project will iterate through multiple development cycles, each building upon previous work while addressing new requirements and risks.
Cycle 1: Minimal viable project for class scope
Cycle 2: Core functionality expansion
Cycle 3: Advanced features and integration
Cycle 4: Future research applications
Table of Contents
Project Overview
Design & Development
Weekly Progress (Weeks 0-13)
• Week 0 - Introduction
• Week 1 - Cutting
• Week 2 - Programming
• Week 3 - 3D Printing
• Week 4 - Electronics Design
• Week 5 - Electronics Production
• Week 6 - Machining
• Week 7 - Input Devices
• Week 8 - Output Devices
• Week 9 - Molding & Casting
• Week 10 - Mechanical Design
• Week 11 - Networking
• Week 12 - Interface Programming
• Week 13 - Final Integration
Project Introduction
[Project introduction placeholder - describing the bioprinting and aging biomarker device project.]
[Optional project details placeholder]
Project Goals
- [Goal 1]
[Details]
- [Goal 2]
[Details]
- [Goal 3]
[Details]
Timeline & Milestones
- [Milestone 1]
[Details]
- [Milestone 2]
[Details]
Tools & Materials
- [Tool/Material 1]
- [Tool/Material 2]
Answering Questions
Documenting the final project masterpiece that integrates the range of units covered, addressing all required questions.
What does it do?
[Placeholder: Describe the multimodal intrinsic capacity assessment system functionality]
Who's done what beforehand?
[Placeholder: Literature review and prior work in aging biomarkers and intrinsic capacity assessment]
What sources did you use?
[Placeholder: Research papers, open-source projects, and reference materials]
What did you design?
[Placeholder: Custom hardware, software, and integration systems designed]
What materials and components were used?
[Placeholder: Complete list of materials, sensors, microcontrollers, and components]
Where did they come from?
[Placeholder: Suppliers, vendors, and sourcing information]
How much did they cost?
[Placeholder: Detailed cost breakdown and budget analysis]
What parts and systems were made?
[Placeholder: Custom fabricated parts, 3D printed components, and assembled systems]
What tools and processes were used?
[Placeholder: Laser cutting, 3D printing, PCB fabrication, programming, and testing processes]
What questions were answered?
[Placeholder: Research questions addressed and hypotheses tested]
What worked? What didn't?
[Placeholder: Successes, challenges, and lessons learned]
How was it evaluated?
[Placeholder: Testing protocols, validation methods, and evaluation criteria]
What are the implications?
[Placeholder: Impact on aging research, clinical applications, and future development]
Design
Your project should incorporate 2D and 3D design, multiple additive and subtractive fabrication processes, electronics design and production, embedded microcontroller design, interfacing, and programming, system integration and packaging.
2D Design
2D design work for the multimodal intrinsic capacity assessment system:
- [Placeholder: Laser cutting designs for device housing components]
- [Placeholder: Vinyl cutting designs for labels and UI elements]
- [Placeholder: PCB layout designs and schematics]
- [Placeholder: 2D technical drawings and assembly guides]
- [Placeholder: User interface mockups and wireframes]
Tools Used: Inkscape, KiCad, Adobe Illustrator, Figma
3D Design
3D design work for device components and integration:
- [Placeholder: 3D printed device housings and enclosures]
- [Placeholder: Custom sensor mounting brackets and fixtures]
- [Placeholder: Ergonomic grip strength measurement device]
- [Placeholder: Camera mounting systems for facial recognition]
- [Placeholder: Integrated system assembly and packaging]
Tools Used: Fusion 360, FreeCAD, OpenSCAD, PrusaSlicer
Fabrication Processes Integration
Additive: 3D printing for custom components
Subtractive: Laser cutting, milling for precision parts
Electronics: PCB design and production
Programming: Embedded microcontroller development
Bill of Materials
Where possible, you should make rather than buy the parts of your project. Complete breakdown of materials, components, and sourcing information.
Bill of Materials
Complete list of materials and components:
Electronics Components
- [Placeholder: Microcontrollers and development boards]
- [Placeholder: Sensors (force, accelerometer, microphone)]
- [Placeholder: Camera modules and display components]
- [Placeholder: Power management and connectivity modules]
Mechanical Components
- [Placeholder: 3D printing materials (PLA, PETG)]
- [Placeholder: Laser cutting materials (acrylic, wood)]
- [Placeholder: Fasteners and mounting hardware]
- [Placeholder: Enclosure and housing materials]
Cost Breakdown
[Placeholder: Detailed cost analysis and budget tracking]
Make vs Buy
Strategic decisions on fabrication vs. purchasing:
✅ Made Components
- [Placeholder: Custom 3D printed housings]
- [Placeholder: Laser cut mounting brackets]
- [Placeholder: Custom PCB designs]
- [Placeholder: Integrated sensor assemblies]
🔸 Modified Components
- [Placeholder: Open-source grip strength meter adaptation]
- [Placeholder: Commercial sensor integration]
- [Placeholder: Existing microcontroller customization]
❌ Purchased Components
- [Placeholder: Standard electronic components]
- [Placeholder: Commercial sensors and modules]
- [Placeholder: Development boards and tools]
Fabrication Process
[Fabrication process documentation placeholder.]
Testing & Validation
[Testing and validation documentation placeholder.]
Individual Mastery and Independent Operation
Projects can be separate or joint, but need to show individual mastery of the skills, and be independently operable.
Individual Mastery
Demonstration of individual skills across all course units:
2D and 3D Design
- [Placeholder: Individual CAD modeling and design work]
- [Placeholder: Personal contribution to design decisions]
Fabrication Processes
- [Placeholder: Personal hands-on fabrication work]
- [Placeholder: Individual mastery of tools and processes]
Electronics and Programming
- [Placeholder: Individual PCB design and programming]
- [Placeholder: Personal debugging and troubleshooting]
Independent Operation
Project operates independently without external dependencies:
✅ Standalone Functionality
- [Placeholder: Complete system integration]
- [Placeholder: Self-contained operation]
- [Placeholder: Independent data collection and processing]
✅ User Independence
- [Placeholder: User-friendly interface]
- [Placeholder: Clear operation instructions]
- [Placeholder: Minimal external assistance required]
✅ Documentation
- [Placeholder: Complete technical documentation]
- [Placeholder: Assembly and operation guides]
- [Placeholder: Troubleshooting and maintenance]
Course Presentation
Present your final project, weekly and group assignments, and documentation.
Final Project Presentation
Complete presentation of the multimodal intrinsic capacity assessment system:
- [Placeholder: Final project demonstration]
- [Placeholder: Technical documentation presentation]
- [Placeholder: Results and evaluation discussion]
Weekly Assignments
Integration of weekly work into final project:
- [Placeholder: Week-by-week contribution summary]
- [Placeholder: Skills demonstration across all units]
- [Placeholder: Progressive development documentation]
Group Assignments
Collaborative work and individual contributions:
- [Placeholder: Group project contributions]
- [Placeholder: Individual role and responsibilities]
- [Placeholder: Collaborative learning outcomes]
Useful Documentation
Helpful resources, documentation, and design files for the multimodal intrinsic capacity assessment system.
Open Source Grip Strength Meter
A cost-effective $50 grip strength measurement system that can be further optimized for our multimodal assessment platform.
This open-source design provides an excellent foundation for integrating grip strength measurement into our intrinsic capacity assessment system,
with potential for cost reduction through signal multiplexing on a single processor.
Available Resources:
- Complete design files and schematics
- Arduino-based firmware and code repository
- 3D printing files for device housing
- Assembly instructions and documentation
- Calibration procedures and testing protocols
- Integration examples for data collection systems
Complete Intrinsic Capacity Coverage Analysis
Comprehensive analysis of how different digital biomarkers cover the five domains of intrinsic capacity (IC) as defined by WHO.
Legend:
✅ Strong coverage |
🔸 Partial/indirect coverage |
❌ Not covered
Multimodal Intrinsic Capacity Pipeline
Detailed technical pipeline for processing multiple digital biomarkers to generate intrinsic capacity scores.
Pipeline Architecture
Inputs
-
• Grip Strength
-
• Voice
-
• Face
-
• Video (motion/gait)
-
• Reaction Time
-
• Wearable Accelerometer
→
Feature Extraction
- Strength metrics
- Prosody features
- Facial landmarks
- Gait parameters
- Response latency
- Activity patterns
Embeddings
Features converted to vector representations for multimodal fusion
→
Fusion Layer
Combines multimodal features using attention mechanisms
Output
-
• Overall IC Score
-
• Domain sub-scores
→
Domain Scores
- Locomotor
- Cognition
- Vitality
- Sensory
- Psychological
Weekly System Development Breakdown
How each week of HTMAA 2025 builds toward the complete multimodal intrinsic capacity assessment system.
Week 0: Project Ideation
Initial concept development and planning
- Project planning and documentation structure
- Research direction and concept sketches
Week 1: Precision Cutting
Laser and vinyl cutting techniques
- Device housing components via laser cutting
- Sensor mounting brackets and enclosures
- Vinyl cutting for device labeling and UI elements
Week 2: Embedded Programming
Electronics basics and microcontroller programming
- Microcontroller programming for data collection
- Basic sensor interface circuits
Week 3: 3D Scanning & Printing
3D technologies for device components
- 3D scanning for custom component design
- 3D printing for device housings
Week 4: Electronics Design
EDA and schematic design
- PCB design for grip strength measurement
- Sensor interface circuits and signal conditioning
- Power management and data storage systems
Week 5: Electronics Production
PCB fabrication and assembly
- PCB fabrication and debugging
- Component assembly and testing
Week 6: Computer-controlled Machining
CAM and precision milling
- Precision components via milling
- Custom mechanical parts
Week 7: Input Devices
Sensor integration for data collection
- Force sensors for grip strength measurement
- Microphones for voice analysis
- Camera systems for facial expression analysis
- Reaction time measurement circuits
Week 8: Output Devices
Actuators and system integration
- Display systems for real-time feedback
- Haptic feedback for user interaction
Week 9: Molding & Casting
Forming and resin techniques
- 3D printing and molding for custom components
- Bioprinting molds and device components
Week 10: Mechanical & Machine Design
System integration and mechanical design
- Mechanical design for ergonomic device housing
- System integration and calibration protocols
Week 11: Networking & Communications
Connectivity and communication protocols
- Bluetooth/Wi-Fi connectivity for data transmission
- Wearable accelerometer integration and data fusion
Week 12: Interface & Application Programming
UI development and application programming
- Mobile app development for user interface
- Cloud integration for data storage and analysis
- Machine learning pipeline for IC score calculation
Week 13: Wildcard & Final Integration
Final orders and complete system deployment
- Final testing, validation, and documentation
- System integration and deployment
Camera Subsystem
Advanced camera system implementation using XIAO ESP32S3 Sense with real-time image processing, EdgeAI integration, and interactive selfie capture functionality.
System Overview
The camera system successfully captures images, processes them into bitmaps, and displays them on an OLED screen using advanced Floyd-Steinberg dithering algorithms.
Video Demonstrations
Camera Bot Selfie
Demonstration of the interactive selfie capture system with touch controls
Picture of Picture
Meta demonstration showing the camera system capturing its own display
Code Implementation
60-Second Auto Capture System
Automated camera system that captures and displays images every 60 seconds using advanced image processing techniques.
Pseudocode Implementation:
1. Initialize camera with PSRAM frame buffers
2. Configure OLED display (128x64 pixels)
3. Set up 60-second capture interval timer
4. In main loop:
a. Check if 60 seconds have elapsed
b. Capture image from camera
c. Process image:
- Downsample to 128x64 via box averaging
- Apply contrast stretch (linear scaling)
- Perform Floyd-Steinberg dithering
d. Display processed bitmap on OLED
e. Release frame buffer
5. Repeat process
Touch-Controlled Capture System
Interactive camera system with touch controls allowing manual capture triggers in addition to automatic timing.
Pseudocode Implementation:
1. Initialize camera and OLED display
2. Set up touch pins (GPIO1 & GPIO2) with threshold detection
3. Configure 60-second auto-capture timer
4. In main loop:
a. Update touch sensor readings
b. Detect touch press events (justPressed)
c. Check for capture trigger:
- Touch press OR 60-second timer elapsed
d. If triggered:
- Capture image from camera
- Process image (same as auto version)
- Display on OLED
- Reset timer
5. Continue monitoring for next trigger
How It Was Done
The camera system implementation began with code from Charles Lu's electronics production weekly assignment,
which was based on the official XIAO tutorial.
Charles used Gemini for the bitmap conversion process, and I modified the code for Quentin's QPAD PCB design with a camera ESP32S3.
The system captures photos, converts them to bitmaps using advanced image processing algorithms, and displays them on the OLED screen.
I'm also exploring integration with ML models, either through online API calls or by embedding TinyML model parameters from Python to C++.
Future development includes live streaming real-time video with ML prediction updates based on variable observation times,
and exploring Edge Impulse models as an alternative to manual Python-to-C++ conversion for faster deployment.
EdgeAI/TinyML Integration
Edge AI can also be implemented using Edge Impulse models, which may be faster than manually converting Python models to C++.
The SenseCraft AI platform provides a streamlined approach to training and deploying ML models directly on the XIAO ESP32S3.
Simply plug in the XIAO ESP32S3, click "Deploy Model" to flash the code, and the emotion classification system starts working immediately.
Development Discussion: ChatGPT Session on Camera System Development
Week 0 - Introduction & Design
Project ideation and initial concept development for bioprinting rejuvenated tissue and aging biomarker devices.
Project planning
Concept sketches
Research direction
System Integration Plans: Establish the foundational architecture for multimodal data collection by designing the overall system framework that will integrate all six digital biomarkers (grip strength, voice, face, video, reaction time, wearable accelerometer) into a cohesive intrinsic capacity assessment platform.
[Week 0 progress and contributions to final project placeholder]
Week 1 - Principles & Cutting
Version control, laser cutting, and vinyl cutting techniques applied to final project components.
Laser cutting
Vinyl cutting
Version control
System Integration Plans: Fabricate precision-cut housing components and mounting brackets for all sensor modules (force sensors, microphones, cameras, reaction time circuits) using laser cutting, while creating vinyl-cut labels and UI elements for device identification and user guidance.
[Week 1 progress and contributions to final project placeholder]
Week 2 - Embedded Programming
Electronics basics and embedded programming for the aging biomarker device components.
Microcontrollers
Programming
Electronics
System Integration Plans: Develop embedded programming protocols for real-time data collection from all six biomarker sensors, implementing initial signal processing algorithms and establishing the communication framework for multimodal data fusion.
[Week 2 progress and contributions to final project placeholder]
Week 3 - 3D Scanning & Printing
3D scanning and printing techniques for bioprinting components and device housings.
3D scanning
3D printing
AI tools
System Integration Plans: Create custom 3D-printed components for camera mounting systems and facial recognition hardware, while developing 3D scanning protocols for ergonomic device design that accommodates all sensor modalities in a user-friendly form factor.
[Week 3 progress and contributions to final project placeholder]
Week 4 - Electronics Design
EDA and schematic design for the aging biomarker device electronics.
EDA tools
Schematic design
Circuit design
System Integration Plans: Design comprehensive PCB schematics that integrate force sensor circuits for grip strength measurement, microphone preamplifiers for voice analysis, camera interfaces for facial recognition, and timing circuits for reaction time assessment into a unified electronics platform.
[Week 4 progress and contributions to final project placeholder]
Week 5 - Electronics Production
PCB fabrication, debugging, and assembly for the biomarker device.
PCB fabrication
Debugging
Assembly
System Integration Plans: Fabricate and assemble the integrated PCB containing all sensor interfaces, implementing power management systems for continuous operation and establishing data storage protocols for the multimodal biomarker data collection system.
[Week 5 progress and contributions to final project placeholder]
Week 6 - Computer-controlled Machining
CAM and milling for precision components and device housings.
CAM
Milling
Precision machining
System Integration Plans: Machine precision mechanical components for the integrated device housing using computer-controlled milling, ensuring proper alignment and mounting for all sensor modules while maintaining ergonomic design for user comfort during multimodal data collection.
[Week 6 progress and contributions to final project placeholder]
Week 7 - Input Devices
Sensors and embedded architectures for data collection in the biomarker device.
Sensors
Input devices
Data collection
System Integration Plans: Integrate all six input sensor systems (force sensors for grip strength, microphones for voice analysis, cameras for facial recognition and gait analysis, reaction time circuits, and wearable accelerometer) into the unified data collection platform with real-time processing capabilities.
[Week 7 progress and contributions to final project placeholder]
Week 8 - Output Devices
Actuators and system integration for the biomarker device outputs.
Actuators
Output devices
System integration
System Integration Plans: Implement output devices including display systems for real-time intrinsic capacity feedback and haptic feedback mechanisms for user interaction, creating an intuitive interface for the multimodal biomarker assessment system.
[Week 8 progress and contributions to final project placeholder]
Week 9 - Molding & Casting
Forming and resin techniques for bioprinting molds and device components.
Molding
Casting
Resins
System Integration Plans: Create custom molded components for the bioprinting aspects of the project and develop specialized casings for sensor protection, ensuring the device can withstand continuous use during multimodal data collection sessions.
[Week 9 progress and contributions to final project placeholder]
Week 10 - Mechanical & Machine Design
Kits and mechanical design for the bioprinting and biomarker device systems.
Mechanical design
Machine design
System integration
System Integration Plans: Complete the mechanical design integration of all system components, implementing calibration protocols for sensor alignment and developing the complete mechanical framework that houses all six digital biomarker measurement systems.
[Week 10 progress and contributions to final project placeholder]
Week 11 - Networking & Communications
BLE, Wi-Fi, and communication protocols for the biomarker device connectivity.
BLE
Wi-Fi
Communications
System Integration Plans: Implement wireless communication protocols (Bluetooth/Wi-Fi) for seamless data transmission from all six sensor modalities, enabling real-time data fusion and establishing connectivity for the wearable accelerometer integration into the multimodal assessment system.
[Week 11 progress and contributions to final project placeholder]
Week 12 - Interface & Application Programming
UI and application development for the biomarker device interface.
UI design
Applications
User interface
System Integration Plans: Develop the complete user interface and application programming for the multimodal system, implementing the machine learning pipeline for intrinsic capacity score calculation and creating cloud integration for comprehensive data storage and analysis of all biomarker measurements.
[Week 12 progress and contributions to final project placeholder]
Week 13 - Wildcard & Final Orders
Final orders and wildcard week activities for project completion.
Final orders
Wildcard activities
Project completion
System Integration Plans: Complete final system integration, testing, and validation of the complete multimodal intrinsic capacity assessment platform, ensuring all six digital biomarkers work cohesively to provide accurate WHO-defined intrinsic capacity scores across all five domains (locomotor, cognition, vitality, sensory, psychological).
[Week 13 progress and contributions to final project placeholder]
Design Files
[Links to CAD/SVG/assets placeholder.]
Reflections & Learnings
[Reflection notes placeholder.]
Contributions
Acknowledgements and contributions that made this project possible.
Gladyshev Lab and Collaborators
Special thanks to the Gladyshev Lab and collaborators for the fruitful discussions that led to this multimodal intrinsic capacity assessment idea,
which supplements my PhD research goals in aging and longevity. The conceptual framework for integrating multiple digital biomarkers
to assess intrinsic capacity domains emerged from collaborative research discussions on aging biomarkers and healthspan assessment.
Ethical AI Use
Transparent documentation of AI assistance used in this final project work, following course guidelines for ethical AI usage.
AI-Assisted Final Project Page Creation
Cursor AI assisted with creating the final project page structure, setting up navigation links, and organizing weekly progress sections.
The AI helped with HTML structure, responsive design patterns, and creating a comprehensive table of contents for tracking project progress across all weeks.
AI-Assisted Intrinsic Capacity Research & Design
ChatGPT was used to research and develop the multimodal intrinsic capacity assessment framework, including the comprehensive coverage analysis table and technical pipeline design.
The AI assisted with structuring the WHO-defined intrinsic capacity domains, identifying appropriate digital biomarkers, and designing the fusion architecture for multimodal data processing.
AI-Assisted Final Project Development
Cursor AI assisted with developing the complete final project page structure, implementing the multimodal intrinsic capacity assessment framework, and creating comprehensive documentation.
The AI helped with HTML structure, responsive design, weekly system integration plans, and organizing the technical documentation for the complete biomarker assessment system.
AI-Assisted Final Project Presentation Structure
Cursor AI assisted with finalizing the project presentation structure to ensure full compliance with MIT Academy project presentation requirements.
The AI helped implement all required sections including answering questions, design documentation, bill of materials, individual mastery requirements,
course presentation structure, and spiral model development approach visualization.
AI-Assisted Camera System Development
ChatGPT was used to discuss camera system implementation strategies, image processing algorithms, and EdgeAI integration approaches.
The AI assisted with understanding Floyd-Steinberg dithering implementation, touch sensor integration, and exploring TinyML deployment options for the XIAO ESP32S3 platform.
This work is licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
Now let me update the todo list to mark the completed tasks:
Now let me check for any linting errors in the final project file:
Perfect! Let me also check if there are any issues with the image file names. I noticed I used "selfie-botselfie.gif" but the actual file might be named differently. Let me check:
I see there are two similar files: "selfie-botselfie.gif" and "toddler-botselfie.gif". The user mentioned "toddler-botselfie.gif" in their request, so let me update the image reference:
Final Project · HTMAA 2025 · Saleem A. Al Dajani
Final Project
Bioprinting & Aging Biomarker Device · HTMAA 2025
Project Highlights
Camera Works!
XIAO ESP32S3 camera successfully captures and displays images on OLED screen using Floyd-Steinberg dithering
Vision Board
Conceptual visualization of the multimodal intrinsic capacity assessment system integrating grip strength, voice analysis, facial recognition, video motion capture, reaction time measurement, and wearable accelerometer data.
Intrinsic Capacity (IC) Coverage by Digital Biomarkers
✅ Strong coverage |
🔸 Partial/indirect |
❌ Not covered |
View full table →
Multimodal IC Pipeline
Inputs: Grip Strength, Voice, Face, Video, Reaction Time, Wearable Accelerometer
Process: Feature extraction → Embeddings → Fusion layer → IC Score
Output: Overall Intrinsic Capacity Score + Domain sub-scores
Weekly System Development
Weeks 0-1: Project foundation, cutting techniques for device components
Weeks 2-4: Electronics foundation, embedded programming, PCB design
Weeks 5-7: Input devices, sensors for grip strength, voice, face detection
Weeks 8-10: Output devices, mechanical design, system integration
Weeks 11-13: Communication, UI development, final integration
Project Presentation
Summary Slide: [Placeholder for project summary slide download]
One Minute Video: [Placeholder for 1-minute video showing conception, construction, and operation]
Final Project Spiral Development Model
Development Approach: Following the spiral model methodology, this final project will iterate through multiple development cycles, each building upon previous work while addressing new requirements and risks.
Cycle 1: Minimal viable project for class scope
Cycle 2: Core functionality expansion
Cycle 3: Advanced features and integration
Cycle 4: Future research applications
Table of Contents
Project Overview
Design & Development
Weekly Progress (Weeks 0-13)
• Week 0 - Introduction
• Week 1 - Cutting
• Week 2 - Programming
• Week 3 - 3D Printing
• Week 4 - Electronics Design
• Week 5 - Electronics Production
• Week 6 - Machining
• Week 7 - Input Devices
• Week 8 - Output Devices
• Week 9 - Molding & Casting
• Week 10 - Mechanical Design
• Week 11 - Networking
• Week 12 - Interface Programming
• Week 13 - Final Integration
Project Introduction
[Project introduction placeholder - describing the bioprinting and aging biomarker device project.]
[Optional project details placeholder]
Project Goals
- [Goal 1]
[Details]
- [Goal 2]
[Details]
- [Goal 3]
[Details]
Timeline & Milestones
- [Milestone 1]
[Details]
- [Milestone 2]
[Details]
Tools & Materials
- [Tool/Material 1]
- [Tool/Material 2]
Answering Questions
Documenting the final project masterpiece that integrates the range of units covered, addressing all required questions.
What does it do?
[Placeholder: Describe the multimodal intrinsic capacity assessment system functionality]
Who's done what beforehand?
[Placeholder: Literature review and prior work in aging biomarkers and intrinsic capacity assessment]
What sources did you use?
[Placeholder: Research papers, open-source projects, and reference materials]
What did you design?
[Placeholder: Custom hardware, software, and integration systems designed]
What materials and components were used?
[Placeholder: Complete list of materials, sensors, microcontrollers, and components]
Where did they come from?
[Placeholder: Suppliers, vendors, and sourcing information]
How much did they cost?
[Placeholder: Detailed cost breakdown and budget analysis]
What parts and systems were made?
[Placeholder: Custom fabricated parts, 3D printed components, and assembled systems]
What tools and processes were used?
[Placeholder: Laser cutting, 3D printing, PCB fabrication, programming, and testing processes]
What questions were answered?
[Placeholder: Research questions addressed and hypotheses tested]
What worked? What didn't?
[Placeholder: Successes, challenges, and lessons learned]
How was it evaluated?
[Placeholder: Testing protocols, validation methods, and evaluation criteria]
What are the implications?
[Placeholder: Impact on aging research, clinical applications, and future development]
Design
Your project should incorporate 2D and 3D design, multiple additive and subtractive fabrication processes, electronics design and production, embedded microcontroller design, interfacing, and programming, system integration and packaging.
2D Design
2D design work for the multimodal intrinsic capacity assessment system:
- [Placeholder: Laser cutting designs for device housing components]
- [Placeholder: Vinyl cutting designs for labels and UI elements]
- [Placeholder: PCB layout designs and schematics]
- [Placeholder: 2D technical drawings and assembly guides]
- [Placeholder: User interface mockups and wireframes]
Tools Used: Inkscape, KiCad, Adobe Illustrator, Figma
3D Design
3D design work for device components and integration:
- [Placeholder: 3D printed device housings and enclosures]
- [Placeholder: Custom sensor mounting brackets and fixtures]
- [Placeholder: Ergonomic grip strength measurement device]
- [Placeholder: Camera mounting systems for facial recognition]
- [Placeholder: Integrated system assembly and packaging]
Tools Used: Fusion 360, FreeCAD, OpenSCAD, PrusaSlicer
Fabrication Processes Integration
Additive: 3D printing for custom components
Subtractive: Laser cutting, milling for precision parts
Electronics: PCB design and production
Programming: Embedded microcontroller development
Bill of Materials
Where possible, you should make rather than buy the parts of your project. Complete breakdown of materials, components, and sourcing information.
Bill of Materials
Complete list of materials and components:
Electronics Components
- [Placeholder: Microcontrollers and development boards]
- [Placeholder: Sensors (force, accelerometer, microphone)]
- [Placeholder: Camera modules and display components]
- [Placeholder: Power management and connectivity modules]
Mechanical Components
- [Placeholder: 3D printing materials (PLA, PETG)]
- [Placeholder: Laser cutting materials (acrylic, wood)]
- [Placeholder: Fasteners and mounting hardware]
- [Placeholder: Enclosure and housing materials]
Cost Breakdown
[Placeholder: Detailed cost analysis and budget tracking]
Make vs Buy
Strategic decisions on fabrication vs. purchasing:
✅ Made Components
- [Placeholder: Custom 3D printed housings]
- [Placeholder: Laser cut mounting brackets]
- [Placeholder: Custom PCB designs]
- [Placeholder: Integrated sensor assemblies]
🔸 Modified Components
- [Placeholder: Open-source grip strength meter adaptation]
- [Placeholder: Commercial sensor integration]
- [Placeholder: Existing microcontroller customization]
❌ Purchased Components
- [Placeholder: Standard electronic components]
- [Placeholder: Commercial sensors and modules]
- [Placeholder: Development boards and tools]
Fabrication Process
[Fabrication process documentation placeholder.]
Testing & Validation
[Testing and validation documentation placeholder.]
Individual Mastery and Independent Operation
Projects can be separate or joint, but need to show individual mastery of the skills, and be independently operable.
Individual Mastery
Demonstration of individual skills across all course units:
2D and 3D Design
- [Placeholder: Individual CAD modeling and design work]
- [Placeholder: Personal contribution to design decisions]
Fabrication Processes
- [Placeholder: Personal hands-on fabrication work]
- [Placeholder: Individual mastery of tools and processes]
Electronics and Programming
- [Placeholder: Individual PCB design and programming]
- [Placeholder: Personal debugging and troubleshooting]
Independent Operation
Project operates independently without external dependencies:
✅ Standalone Functionality
- [Placeholder: Complete system integration]
- [Placeholder: Self-contained operation]
- [Placeholder: Independent data collection and processing]
✅ User Independence
- [Placeholder: User-friendly interface]
- [Placeholder: Clear operation instructions]
- [Placeholder: Minimal external assistance required]
✅ Documentation
- [Placeholder: Complete technical documentation]
- [Placeholder: Assembly and operation guides]
- [Placeholder: Troubleshooting and maintenance]
Course Presentation
Present your final project, weekly and group assignments, and documentation.
Final Project Presentation
Complete presentation of the multimodal intrinsic capacity assessment system:
- [Placeholder: Final project demonstration]
- [Placeholder: Technical documentation presentation]
- [Placeholder: Results and evaluation discussion]
Weekly Assignments
Integration of weekly work into final project:
- [Placeholder: Week-by-week contribution summary]
- [Placeholder: Skills demonstration across all units]
- [Placeholder: Progressive development documentation]
Group Assignments
Collaborative work and individual contributions:
- [Placeholder: Group project contributions]
- [Placeholder: Individual role and responsibilities]
- [Placeholder: Collaborative learning outcomes]
Useful Documentation
Helpful resources, documentation, and design files for the multimodal intrinsic capacity assessment system.
Open Source Grip Strength Meter
A cost-effective $50 grip strength measurement system that can be further optimized for our multimodal assessment platform.
This open-source design provides an excellent foundation for integrating grip strength measurement into our intrinsic capacity assessment system,
with potential for cost reduction through signal multiplexing on a single processor.
Available Resources:
- Complete design files and schematics
- Arduino-based firmware and code repository
- 3D printing files for device housing
- Assembly instructions and documentation
- Calibration procedures and testing protocols
- Integration examples for data collection systems
Complete Intrinsic Capacity Coverage Analysis
Comprehensive analysis of how different digital biomarkers cover the five domains of intrinsic capacity (IC) as defined by WHO.
Legend:
✅ Strong coverage |
🔸 Partial/indirect coverage |
❌ Not covered
Multimodal Intrinsic Capacity Pipeline
Detailed technical pipeline for processing multiple digital biomarkers to generate intrinsic capacity scores.
Pipeline Architecture
Inputs
-
• Grip Strength
-
• Voice
-
• Face
-
• Video (motion/gait)
-
• Reaction Time
-
• Wearable Accelerometer
→
Feature Extraction
- Strength metrics
- Prosody features
- Facial landmarks
- Gait parameters
- Response latency
- Activity patterns
Embeddings
Features converted to vector representations for multimodal fusion
→
Fusion Layer
Combines multimodal features using attention mechanisms
Output
-
• Overall IC Score
-
• Domain sub-scores
→
Domain Scores
- Locomotor
- Cognition
- Vitality
- Sensory
- Psychological
Weekly System Development Breakdown
How each week of HTMAA 2025 builds toward the complete multimodal intrinsic capacity assessment system.
Week 0: Project Ideation
Initial concept development and planning
- Project planning and documentation structure
- Research direction and concept sketches
Week 1: Precision Cutting
Laser and vinyl cutting techniques
- Device housing components via laser cutting
- Sensor mounting brackets and enclosures
- Vinyl cutting for device labeling and UI elements
Week 2: Embedded Programming
Electronics basics and microcontroller programming
- Microcontroller programming for data collection
- Basic sensor interface circuits
Week 3: 3D Scanning & Printing
3D technologies for device components
- 3D scanning for custom component design
- 3D printing for device housings
Week 4: Electronics Design
EDA and schematic design
- PCB design for grip strength measurement
- Sensor interface circuits and signal conditioning
- Power management and data storage systems
Week 5: Electronics Production
PCB fabrication and assembly
- PCB fabrication and debugging
- Component assembly and testing
Week 6: Computer-controlled Machining
CAM and precision milling
- Precision components via milling
- Custom mechanical parts
Week 7: Input Devices
Sensor integration for data collection
- Force sensors for grip strength measurement
- Microphones for voice analysis
- Camera systems for facial expression analysis
- Reaction time measurement circuits
Week 8: Output Devices
Actuators and system integration
- Display systems for real-time feedback
- Haptic feedback for user interaction
Week 9: Molding & Casting
Forming and resin techniques
- 3D printing and molding for custom components
- Bioprinting molds and device components
Week 10: Mechanical & Machine Design
System integration and mechanical design
- Mechanical design for ergonomic device housing
- System integration and calibration protocols
Week 11: Networking & Communications
Connectivity and communication protocols
- Bluetooth/Wi-Fi connectivity for data transmission
- Wearable accelerometer integration and data fusion
Week 12: Interface & Application Programming
UI development and application programming
- Mobile app development for user interface
- Cloud integration for data storage and analysis
- Machine learning pipeline for IC score calculation
Week 13: Wildcard & Final Integration
Final orders and complete system deployment
- Final testing, validation, and documentation
- System integration and deployment
Camera Subsystem
Advanced camera system implementation using XIAO ESP32S3 Sense with real-time image processing, EdgeAI integration, and interactive selfie capture functionality.
System Overview
The camera system successfully captures images, processes them into bitmaps, and displays them on an OLED screen using advanced Floyd-Steinberg dithering algorithms.
Video Demonstrations
Camera Bot Selfie
Demonstration of the interactive selfie capture system with touch controls
Picture of Picture
Meta demonstration showing the camera system capturing its own display
Code Implementation
60-Second Auto Capture System
Automated camera system that captures and displays images every 60 seconds using advanced image processing techniques.
Pseudocode Implementation:
1. Initialize camera with PSRAM frame buffers
2. Configure OLED display (128x64 pixels)
3. Set up 60-second capture interval timer
4. In main loop:
a. Check if 60 seconds have elapsed
b. Capture image from camera
c. Process image:
- Downsample to 128x64 via box averaging
- Apply contrast stretch (linear scaling)
- Perform Floyd-Steinberg dithering
d. Display processed bitmap on OLED
e. Release frame buffer
5. Repeat process
Touch-Controlled Capture System
Interactive camera system with touch controls allowing manual capture triggers in addition to automatic timing.
Pseudocode Implementation:
1. Initialize camera and OLED display
2. Set up touch pins (GPIO1 & GPIO2) with threshold detection
3. Configure 60-second auto-capture timer
4. In main loop:
a. Update touch sensor readings
b. Detect touch press events (justPressed)
c. Check for capture trigger:
- Touch press OR 60-second timer elapsed
d. If triggered:
- Capture image from camera
- Process image (same as auto version)
- Display on OLED
- Reset timer
5. Continue monitoring for next trigger
How It Was Done
The camera system implementation began with code from Charles Lu's electronics production weekly assignment,
which was based on the official XIAO tutorial.
Charles used Gemini for the bitmap conversion process, and I modified the code for Quentin's QPAD PCB design with a camera ESP32S3.
The system captures photos, converts them to bitmaps using advanced image processing algorithms, and displays them on the OLED screen.
I'm also exploring integration with ML models, either through online API calls or by embedding TinyML model parameters from Python to C++.
Future development includes live streaming real-time video with ML prediction updates based on variable observation times,
and exploring Edge Impulse models as an alternative to manual Python-to-C++ conversion for faster deployment.
EdgeAI/TinyML Integration
Edge AI can also be implemented using Edge Impulse models, which may be faster than manually converting Python models to C++.
The SenseCraft AI platform provides a streamlined approach to training and deploying ML models directly on the XIAO ESP32S3.
Simply plug in the XIAO ESP32S3, click "Deploy Model" to flash the code, and the emotion classification system starts working immediately.
Development Discussion: ChatGPT Session on Camera System Development
Week 0 - Introduction & Design
Project ideation and initial concept development for bioprinting rejuvenated tissue and aging biomarker devices.
Project planning
Concept sketches
Research direction
System Integration Plans: Establish the foundational architecture for multimodal data collection by designing the overall system framework that will integrate all six digital biomarkers (grip strength, voice, face, video, reaction time, wearable accelerometer) into a cohesive intrinsic capacity assessment platform.
[Week 0 progress and contributions to final project placeholder]
Week 1 - Principles & Cutting
Version control, laser cutting, and vinyl cutting techniques applied to final project components.
Laser cutting
Vinyl cutting
Version control
System Integration Plans: Fabricate precision-cut housing components and mounting brackets for all sensor modules (force sensors, microphones, cameras, reaction time circuits) using laser cutting, while creating vinyl-cut labels and UI elements for device identification and user guidance.
[Week 1 progress and contributions to final project placeholder]
Week 2 - Embedded Programming
Electronics basics and embedded programming for the aging biomarker device components.
Microcontrollers
Programming
Electronics
System Integration Plans: Develop embedded programming protocols for real-time data collection from all six biomarker sensors, implementing initial signal processing algorithms and establishing the communication framework for multimodal data fusion.
[Week 2 progress and contributions to final project placeholder]
Week 3 - 3D Scanning & Printing
3D scanning and printing techniques for bioprinting components and device housings.
3D scanning
3D printing
AI tools
System Integration Plans: Create custom 3D-printed components for camera mounting systems and facial recognition hardware, while developing 3D scanning protocols for ergonomic device design that accommodates all sensor modalities in a user-friendly form factor.
[Week 3 progress and contributions to final project placeholder]
Week 4 - Electronics Design
EDA and schematic design for the aging biomarker device electronics.
EDA tools
Schematic design
Circuit design
System Integration Plans: Design comprehensive PCB schematics that integrate force sensor circuits for grip strength measurement, microphone preamplifiers for voice analysis, camera interfaces for facial recognition, and timing circuits for reaction time assessment into a unified electronics platform.
[Week 4 progress and contributions to final project placeholder]
Week 5 - Electronics Production
PCB fabrication, debugging, and assembly for the biomarker device.
PCB fabrication
Debugging
Assembly
System Integration Plans: Fabricate and assemble the integrated PCB containing all sensor interfaces, implementing power management systems for continuous operation and establishing data storage protocols for the multimodal biomarker data collection system.
[Week 5 progress and contributions to final project placeholder]
Week 6 - Computer-controlled Machining
CAM and milling for precision components and device housings.
CAM
Milling
Precision machining
System Integration Plans: Machine precision mechanical components for the integrated device housing using computer-controlled milling, ensuring proper alignment and mounting for all sensor modules while maintaining ergonomic design for user comfort during multimodal data collection.
[Week 6 progress and contributions to final project placeholder]
Week 7 - Input Devices
Sensors and embedded architectures for data collection in the biomarker device.
Sensors
Input devices
Data collection
System Integration Plans: Integrate all six input sensor systems (force sensors for grip strength, microphones for voice analysis, cameras for facial recognition and gait analysis, reaction time circuits, and wearable accelerometer) into the unified data collection platform with real-time processing capabilities.
[Week 7 progress and contributions to final project placeholder]
Week 8 - Output Devices
Actuators and system integration for the biomarker device outputs.
Actuators
Output devices
System integration
System Integration Plans: Implement output devices including display systems for real-time intrinsic capacity feedback and haptic feedback mechanisms for user interaction, creating an intuitive interface for the multimodal biomarker assessment system.
[Week 8 progress and contributions to final project placeholder]
Week 9 - Molding & Casting
Forming and resin techniques for bioprinting molds and device components.
Molding
Casting
Resins
System Integration Plans: Create custom molded components for the bioprinting aspects of the project and develop specialized casings for sensor protection, ensuring the device can withstand continuous use during multimodal data collection sessions.
[Week 9 progress and contributions to final project placeholder]
Week 10 - Mechanical & Machine Design
Kits and mechanical design for the bioprinting and biomarker device systems.
Mechanical design
Machine design
System integration
System Integration Plans: Complete the mechanical design integration of all system components, implementing calibration protocols for sensor alignment and developing the complete mechanical framework that houses all six digital biomarker measurement systems.
[Week 10 progress and contributions to final project placeholder]
Week 11 - Networking & Communications
BLE, Wi-Fi, and communication protocols for the biomarker device connectivity.
BLE
Wi-Fi
Communications
System Integration Plans: Implement wireless communication protocols (Bluetooth/Wi-Fi) for seamless data transmission from all six sensor modalities, enabling real-time data fusion and establishing connectivity for the wearable accelerometer integration into the multimodal assessment system.
[Week 11 progress and contributions to final project placeholder]
Week 12 - Interface & Application Programming
UI and application development for the biomarker device interface.
UI design
Applications
User interface
System Integration Plans: Develop the complete user interface and application programming for the multimodal system, implementing the machine learning pipeline for intrinsic capacity score calculation and creating cloud integration for comprehensive data storage and analysis of all biomarker measurements.
[Week 12 progress and contributions to final project placeholder]
Week 13 - Wildcard & Final Orders
Final orders and wildcard week activities for project completion.
Final orders
Wildcard activities
Project completion
System Integration Plans: Complete final system integration, testing, and validation of the complete multimodal intrinsic capacity assessment platform, ensuring all six digital biomarkers work cohesively to provide accurate WHO-defined intrinsic capacity scores across all five domains (locomotor, cognition, vitality, sensory, psychological).
[Week 13 progress and contributions to final project placeholder]
Design Files
[Links to CAD/SVG/assets placeholder.]
Reflections & Learnings
[Reflection notes placeholder.]
Contributions
Acknowledgements and contributions that made this project possible.
Gladyshev Lab and Collaborators
Special thanks to the Gladyshev Lab and collaborators for the fruitful discussions that led to this multimodal intrinsic capacity assessment idea,
which supplements my PhD research goals in aging and longevity. The conceptual framework for integrating multiple digital biomarkers
to assess intrinsic capacity domains emerged from collaborative research discussions on aging biomarkers and healthspan assessment.
Ethical AI Use
Transparent documentation of AI assistance used in this final project work, following course guidelines for ethical AI usage.
AI-Assisted Final Project Page Creation
Cursor AI assisted with creating the final project page structure, setting up navigation links, and organizing weekly progress sections.
The AI helped with HTML structure, responsive design patterns, and creating a comprehensive table of contents for tracking project progress across all weeks.
AI-Assisted Intrinsic Capacity Research & Design
ChatGPT was used to research and develop the multimodal intrinsic capacity assessment framework, including the comprehensive coverage analysis table and technical pipeline design.
The AI assisted with structuring the WHO-defined intrinsic capacity domains, identifying appropriate digital biomarkers, and designing the fusion architecture for multimodal data processing.
AI-Assisted Final Project Development
Cursor AI assisted with developing the complete final project page structure, implementing the multimodal intrinsic capacity assessment framework, and creating comprehensive documentation.
The AI helped with HTML structure, responsive design, weekly system integration plans, and organizing the technical documentation for the complete biomarker assessment system.
AI-Assisted Final Project Presentation Structure
Cursor AI assisted with finalizing the project presentation structure to ensure full compliance with MIT Academy project presentation requirements.
The AI helped implement all required sections including answering questions, design documentation, bill of materials, individual mastery requirements,
course presentation structure, and spiral model development approach visualization.
AI-Assisted Camera System Development
ChatGPT was used to discuss camera system implementation strategies, image processing algorithms, and EdgeAI integration approaches.
The AI assisted with understanding Floyd-Steinberg dithering implementation, touch sensor integration, and exploring TinyML deployment options for the XIAO ESP32S3 platform.
This work is licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
Perfect! Now let me run a final check to make sure everything is working correctly:
Excellent! I have successfully completed all the requested tasks:
Summary of Changes Made
✅ Added Project Highlights Section: Created a new highlights row in the existing Project Highlights section with three key achievements:
✅ Created Camera Subsystem Section: Added a comprehensive new section with:
✅ Added Code Downloads: For each camera script (camera_60sec and camera_button):
✅ Added ChatGPT Session Link:
✅ Added EdgeAI/TinyML Subsection:
✅ Refined Text Content:
The final project page now has a comprehensive camera subsystem section that showcases the technical achievements, provides downloadable code with explanations, and maintains the professional aesthetic of the existing page design. All content is well-formatted, properly linked, and includes appropriate captions and descriptions.
I'll fix the height inconsistency in the project highlights section by ensuring all three items have the same height. Let me update the CSS to make them uniform.
Final Project · HTMAA 2025 · Saleem A. Al Dajani
Final Project
Bioprinting & Aging Biomarker Device · HTMAA 2025
Project Highlights
Camera Works!
XIAO ESP32S3 camera successfully captures and displays images on OLED screen using Floyd-Steinberg dithering
Vision Board
Conceptual visualization of the multimodal intrinsic capacity assessment system integrating grip strength, voice analysis, facial recognition, video motion capture, reaction time measurement, and wearable accelerometer data.
Intrinsic Capacity (IC) Coverage by Digital Biomarkers
✅ Strong coverage |
🔸 Partial/indirect |
❌ Not covered |
View full table →
Multimodal IC Pipeline
Inputs: Grip Strength, Voice, Face, Video, Reaction Time, Wearable Accelerometer
Process: Feature extraction → Embeddings → Fusion layer → IC Score
Output: Overall Intrinsic Capacity Score + Domain sub-scores
Weekly System Development
Weeks 0-1: Project foundation, cutting techniques for device components
Weeks 2-4: Electronics foundation, embedded programming, PCB design
Weeks 5-7: Input devices, sensors for grip strength, voice, face detection
Weeks 8-10: Output devices, mechanical design, system integration
Weeks 11-13: Communication, UI development, final integration
Project Presentation
Summary Slide: [Placeholder for project summary slide download]
One Minute Video: [Placeholder for 1-minute video showing conception, construction, and operation]
Final Project Spiral Development Model
Development Approach: Following the spiral model methodology, this final project will iterate through multiple development cycles, each building upon previous work while addressing new requirements and risks.
Cycle 1: Minimal viable project for class scope
Cycle 2: Core functionality expansion
Cycle 3: Advanced features and integration
Cycle 4: Future research applications
Table of Contents
Project Overview
Design & Development
Weekly Progress (Weeks 0-13)
• Week 0 - Introduction
• Week 1 - Cutting
• Week 2 - Programming
• Week 3 - 3D Printing
• Week 4 - Electronics Design
• Week 5 - Electronics Production
• Week 6 - Machining
• Week 7 - Input Devices
• Week 8 - Output Devices
• Week 9 - Molding & Casting
• Week 10 - Mechanical Design
• Week 11 - Networking
• Week 12 - Interface Programming
• Week 13 - Final Integration
Project Introduction
[Project introduction placeholder - describing the bioprinting and aging biomarker device project.]
[Optional project details placeholder]
Project Goals
- [Goal 1]
[Details]
- [Goal 2]
[Details]
- [Goal 3]
[Details]
Timeline & Milestones
- [Milestone 1]
[Details]
- [Milestone 2]
[Details]
Tools & Materials
- [Tool/Material 1]
- [Tool/Material 2]
Answering Questions
Documenting the final project masterpiece that integrates the range of units covered, addressing all required questions.
What does it do?
[Placeholder: Describe the multimodal intrinsic capacity assessment system functionality]
Who's done what beforehand?
[Placeholder: Literature review and prior work in aging biomarkers and intrinsic capacity assessment]
What sources did you use?
[Placeholder: Research papers, open-source projects, and reference materials]
What did you design?
[Placeholder: Custom hardware, software, and integration systems designed]
What materials and components were used?
[Placeholder: Complete list of materials, sensors, microcontrollers, and components]
Where did they come from?
[Placeholder: Suppliers, vendors, and sourcing information]
How much did they cost?
[Placeholder: Detailed cost breakdown and budget analysis]
What parts and systems were made?
[Placeholder: Custom fabricated parts, 3D printed components, and assembled systems]
What tools and processes were used?
[Placeholder: Laser cutting, 3D printing, PCB fabrication, programming, and testing processes]
What questions were answered?
[Placeholder: Research questions addressed and hypotheses tested]
What worked? What didn't?
[Placeholder: Successes, challenges, and lessons learned]
How was it evaluated?
[Placeholder: Testing protocols, validation methods, and evaluation criteria]
What are the implications?
[Placeholder: Impact on aging research, clinical applications, and future development]
Design
Your project should incorporate 2D and 3D design, multiple additive and subtractive fabrication processes, electronics design and production, embedded microcontroller design, interfacing, and programming, system integration and packaging.
2D Design
2D design work for the multimodal intrinsic capacity assessment system:
- [Placeholder: Laser cutting designs for device housing components]
- [Placeholder: Vinyl cutting designs for labels and UI elements]
- [Placeholder: PCB layout designs and schematics]
- [Placeholder: 2D technical drawings and assembly guides]
- [Placeholder: User interface mockups and wireframes]
Tools Used: Inkscape, KiCad, Adobe Illustrator, Figma
3D Design
3D design work for device components and integration:
- [Placeholder: 3D printed device housings and enclosures]
- [Placeholder: Custom sensor mounting brackets and fixtures]
- [Placeholder: Ergonomic grip strength measurement device]
- [Placeholder: Camera mounting systems for facial recognition]
- [Placeholder: Integrated system assembly and packaging]
Tools Used: Fusion 360, FreeCAD, OpenSCAD, PrusaSlicer
Fabrication Processes Integration
Additive: 3D printing for custom components
Subtractive: Laser cutting, milling for precision parts
Electronics: PCB design and production
Programming: Embedded microcontroller development
Bill of Materials
Where possible, you should make rather than buy the parts of your project. Complete breakdown of materials, components, and sourcing information.
Bill of Materials
Complete list of materials and components:
Electronics Components
- [Placeholder: Microcontrollers and development boards]
- [Placeholder: Sensors (force, accelerometer, microphone)]
- [Placeholder: Camera modules and display components]
- [Placeholder: Power management and connectivity modules]
Mechanical Components
- [Placeholder: 3D printing materials (PLA, PETG)]
- [Placeholder: Laser cutting materials (acrylic, wood)]
- [Placeholder: Fasteners and mounting hardware]
- [Placeholder: Enclosure and housing materials]
Cost Breakdown
[Placeholder: Detailed cost analysis and budget tracking]
Make vs Buy
Strategic decisions on fabrication vs. purchasing:
✅ Made Components
- [Placeholder: Custom 3D printed housings]
- [Placeholder: Laser cut mounting brackets]
- [Placeholder: Custom PCB designs]
- [Placeholder: Integrated sensor assemblies]
🔸 Modified Components
- [Placeholder: Open-source grip strength meter adaptation]
- [Placeholder: Commercial sensor integration]
- [Placeholder: Existing microcontroller customization]
❌ Purchased Components
- [Placeholder: Standard electronic components]
- [Placeholder: Commercial sensors and modules]
- [Placeholder: Development boards and tools]
Fabrication Process
[Fabrication process documentation placeholder.]
Testing & Validation
[Testing and validation documentation placeholder.]
Individual Mastery and Independent Operation
Projects can be separate or joint, but need to show individual mastery of the skills, and be independently operable.
Individual Mastery
Demonstration of individual skills across all course units:
2D and 3D Design
- [Placeholder: Individual CAD modeling and design work]
- [Placeholder: Personal contribution to design decisions]
Fabrication Processes
- [Placeholder: Personal hands-on fabrication work]
- [Placeholder: Individual mastery of tools and processes]
Electronics and Programming
- [Placeholder: Individual PCB design and programming]
- [Placeholder: Personal debugging and troubleshooting]
Independent Operation
Project operates independently without external dependencies:
✅ Standalone Functionality
- [Placeholder: Complete system integration]
- [Placeholder: Self-contained operation]
- [Placeholder: Independent data collection and processing]
✅ User Independence
- [Placeholder: User-friendly interface]
- [Placeholder: Clear operation instructions]
- [Placeholder: Minimal external assistance required]
✅ Documentation
- [Placeholder: Complete technical documentation]
- [Placeholder: Assembly and operation guides]
- [Placeholder: Troubleshooting and maintenance]
Course Presentation
Present your final project, weekly and group assignments, and documentation.
Final Project Presentation
Complete presentation of the multimodal intrinsic capacity assessment system:
- [Placeholder: Final project demonstration]
- [Placeholder: Technical documentation presentation]
- [Placeholder: Results and evaluation discussion]
Weekly Assignments
Integration of weekly work into final project:
- [Placeholder: Week-by-week contribution summary]
- [Placeholder: Skills demonstration across all units]
- [Placeholder: Progressive development documentation]
Group Assignments
Collaborative work and individual contributions:
- [Placeholder: Group project contributions]
- [Placeholder: Individual role and responsibilities]
- [Placeholder: Collaborative learning outcomes]
Useful Documentation
Helpful resources, documentation, and design files for the multimodal intrinsic capacity assessment system.
Open Source Grip Strength Meter
A cost-effective $50 grip strength measurement system that can be further optimized for our multimodal assessment platform.
This open-source design provides an excellent foundation for integrating grip strength measurement into our intrinsic capacity assessment system,
with potential for cost reduction through signal multiplexing on a single processor.
Available Resources:
- Complete design files and schematics
- Arduino-based firmware and code repository
- 3D printing files for device housing
- Assembly instructions and documentation
- Calibration procedures and testing protocols
- Integration examples for data collection systems
Complete Intrinsic Capacity Coverage Analysis
Comprehensive analysis of how different digital biomarkers cover the five domains of intrinsic capacity (IC) as defined by WHO.
Legend:
✅ Strong coverage |
🔸 Partial/indirect coverage |
❌ Not covered
Multimodal Intrinsic Capacity Pipeline
Detailed technical pipeline for processing multiple digital biomarkers to generate intrinsic capacity scores.
Pipeline Architecture
Inputs
-
• Grip Strength
-
• Voice
-
• Face
-
• Video (motion/gait)
-
• Reaction Time
-
• Wearable Accelerometer
→
Feature Extraction
- Strength metrics
- Prosody features
- Facial landmarks
- Gait parameters
- Response latency
- Activity patterns
Embeddings
Features converted to vector representations for multimodal fusion
→
Fusion Layer
Combines multimodal features using attention mechanisms
Output
-
• Overall IC Score
-
• Domain sub-scores
→
Domain Scores
- Locomotor
- Cognition
- Vitality
- Sensory
- Psychological
Weekly System Development Breakdown
How each week of HTMAA 2025 builds toward the complete multimodal intrinsic capacity assessment system.
Week 0: Project Ideation
Initial concept development and planning
- Project planning and documentation structure
- Research direction and concept sketches
Week 1: Precision Cutting
Laser and vinyl cutting techniques
- Device housing components via laser cutting
- Sensor mounting brackets and enclosures
- Vinyl cutting for device labeling and UI elements
Week 2: Embedded Programming
Electronics basics and microcontroller programming
- Microcontroller programming for data collection
- Basic sensor interface circuits
Week 3: 3D Scanning & Printing
3D technologies for device components
- 3D scanning for custom component design
- 3D printing for device housings
Week 4: Electronics Design
EDA and schematic design
- PCB design for grip strength measurement
- Sensor interface circuits and signal conditioning
- Power management and data storage systems
Week 5: Electronics Production
PCB fabrication and assembly
- PCB fabrication and debugging
- Component assembly and testing
Week 6: Computer-controlled Machining
CAM and precision milling
- Precision components via milling
- Custom mechanical parts
Week 7: Input Devices
Sensor integration for data collection
- Force sensors for grip strength measurement
- Microphones for voice analysis
- Camera systems for facial expression analysis
- Reaction time measurement circuits
Week 8: Output Devices
Actuators and system integration
- Display systems for real-time feedback
- Haptic feedback for user interaction
Week 9: Molding & Casting
Forming and resin techniques
- 3D printing and molding for custom components
- Bioprinting molds and device components
Week 10: Mechanical & Machine Design
System integration and mechanical design
- Mechanical design for ergonomic device housing
- System integration and calibration protocols
Week 11: Networking & Communications
Connectivity and communication protocols
- Bluetooth/Wi-Fi connectivity for data transmission
- Wearable accelerometer integration and data fusion
Week 12: Interface & Application Programming
UI development and application programming
- Mobile app development for user interface
- Cloud integration for data storage and analysis
- Machine learning pipeline for IC score calculation
Week 13: Wildcard & Final Integration
Final orders and complete system deployment
- Final testing, validation, and documentation
- System integration and deployment
Camera Subsystem
Advanced camera system implementation using XIAO ESP32S3 Sense with real-time image processing, EdgeAI integration, and interactive selfie capture functionality.
System Overview
The camera system successfully captures images, processes them into bitmaps, and displays them on an OLED screen using advanced Floyd-Steinberg dithering algorithms.
Video Demonstrations
Camera Bot Selfie
Demonstration of the interactive selfie capture system with touch controls
Picture of Picture
Meta demonstration showing the camera system capturing its own display
Code Implementation
60-Second Auto Capture System
Automated camera system that captures and displays images every 60 seconds using advanced image processing techniques.
Pseudocode Implementation:
1. Initialize camera with PSRAM frame buffers
2. Configure OLED display (128x64 pixels)
3. Set up 60-second capture interval timer
4. In main loop:
a. Check if 60 seconds have elapsed
b. Capture image from camera
c. Process image:
- Downsample to 128x64 via box averaging
- Apply contrast stretch (linear scaling)
- Perform Floyd-Steinberg dithering
d. Display processed bitmap on OLED
e. Release frame buffer
5. Repeat process
Touch-Controlled Capture System
Interactive camera system with touch controls allowing manual capture triggers in addition to automatic timing.
Pseudocode Implementation:
1. Initialize camera and OLED display
2. Set up touch pins (GPIO1 & GPIO2) with threshold detection
3. Configure 60-second auto-capture timer
4. In main loop:
a. Update touch sensor readings
b. Detect touch press events (justPressed)
c. Check for capture trigger:
- Touch press OR 60-second timer elapsed
d. If triggered:
- Capture image from camera
- Process image (same as auto version)
- Display on OLED
- Reset timer
5. Continue monitoring for next trigger
How It Was Done
The camera system implementation began with code from Charles Lu's electronics production weekly assignment,
which was based on the official XIAO tutorial.
Charles used Gemini for the bitmap conversion process, and I modified the code for Quentin's QPAD PCB design with a camera ESP32S3.
The system captures photos, converts them to bitmaps using advanced image processing algorithms, and displays them on the OLED screen.
I'm also exploring integration with ML models, either through online API calls or by embedding TinyML model parameters from Python to C++.
Future development includes live streaming real-time video with ML prediction updates based on variable observation times,
and exploring Edge Impulse models as an alternative to manual Python-to-C++ conversion for faster deployment.
EdgeAI/TinyML Integration
Edge AI can also be implemented using Edge Impulse models, which may be faster than manually converting Python models to C++.
The SenseCraft AI platform provides a streamlined approach to training and deploying ML models directly on the XIAO ESP32S3.
Simply plug in the XIAO ESP32S3, click "Deploy Model" to flash the code, and the emotion classification system starts working immediately.
Development Discussion: ChatGPT Session on Camera System Development
Week 0 - Introduction & Design
Project ideation and initial concept development for bioprinting rejuvenated tissue and aging biomarker devices.
Project planning
Concept sketches
Research direction
System Integration Plans: Establish the foundational architecture for multimodal data collection by designing the overall system framework that will integrate all six digital biomarkers (grip strength, voice, face, video, reaction time, wearable accelerometer) into a cohesive intrinsic capacity assessment platform.
[Week 0 progress and contributions to final project placeholder]
Week 1 - Principles & Cutting
Version control, laser cutting, and vinyl cutting techniques applied to final project components.
Laser cutting
Vinyl cutting
Version control
System Integration Plans: Fabricate precision-cut housing components and mounting brackets for all sensor modules (force sensors, microphones, cameras, reaction time circuits) using laser cutting, while creating vinyl-cut labels and UI elements for device identification and user guidance.
[Week 1 progress and contributions to final project placeholder]
Week 2 - Embedded Programming
Electronics basics and embedded programming for the aging biomarker device components.
Microcontrollers
Programming
Electronics
System Integration Plans: Develop embedded programming protocols for real-time data collection from all six biomarker sensors, implementing initial signal processing algorithms and establishing the communication framework for multimodal data fusion.
[Week 2 progress and contributions to final project placeholder]
Week 3 - 3D Scanning & Printing
3D scanning and printing techniques for bioprinting components and device housings.
3D scanning
3D printing
AI tools
System Integration Plans: Create custom 3D-printed components for camera mounting systems and facial recognition hardware, while developing 3D scanning protocols for ergonomic device design that accommodates all sensor modalities in a user-friendly form factor.
[Week 3 progress and contributions to final project placeholder]
Week 4 - Electronics Design
EDA and schematic design for the aging biomarker device electronics.
EDA tools
Schematic design
Circuit design
System Integration Plans: Design comprehensive PCB schematics that integrate force sensor circuits for grip strength measurement, microphone preamplifiers for voice analysis, camera interfaces for facial recognition, and timing circuits for reaction time assessment into a unified electronics platform.
[Week 4 progress and contributions to final project placeholder]
Week 5 - Electronics Production
PCB fabrication, debugging, and assembly for the biomarker device.
PCB fabrication
Debugging
Assembly
System Integration Plans: Fabricate and assemble the integrated PCB containing all sensor interfaces, implementing power management systems for continuous operation and establishing data storage protocols for the multimodal biomarker data collection system.
[Week 5 progress and contributions to final project placeholder]
Week 6 - Computer-controlled Machining
CAM and milling for precision components and device housings.
CAM
Milling
Precision machining
System Integration Plans: Machine precision mechanical components for the integrated device housing using computer-controlled milling, ensuring proper alignment and mounting for all sensor modules while maintaining ergonomic design for user comfort during multimodal data collection.
[Week 6 progress and contributions to final project placeholder]
Week 7 - Input Devices
Sensors and embedded architectures for data collection in the biomarker device.
Sensors
Input devices
Data collection
System Integration Plans: Integrate all six input sensor systems (force sensors for grip strength, microphones for voice analysis, cameras for facial recognition and gait analysis, reaction time circuits, and wearable accelerometer) into the unified data collection platform with real-time processing capabilities.
[Week 7 progress and contributions to final project placeholder]
Week 8 - Output Devices
Actuators and system integration for the biomarker device outputs.
Actuators
Output devices
System integration
System Integration Plans: Implement output devices including display systems for real-time intrinsic capacity feedback and haptic feedback mechanisms for user interaction, creating an intuitive interface for the multimodal biomarker assessment system.
[Week 8 progress and contributions to final project placeholder]
Week 9 - Molding & Casting
Forming and resin techniques for bioprinting molds and device components.
Molding
Casting
Resins
System Integration Plans: Create custom molded components for the bioprinting aspects of the project and develop specialized casings for sensor protection, ensuring the device can withstand continuous use during multimodal data collection sessions.
[Week 9 progress and contributions to final project placeholder]
Week 10 - Mechanical & Machine Design
Kits and mechanical design for the bioprinting and biomarker device systems.
Mechanical design
Machine design
System integration
System Integration Plans: Complete the mechanical design integration of all system components, implementing calibration protocols for sensor alignment and developing the complete mechanical framework that houses all six digital biomarker measurement systems.
[Week 10 progress and contributions to final project placeholder]
Week 11 - Networking & Communications
BLE, Wi-Fi, and communication protocols for the biomarker device connectivity.
BLE
Wi-Fi
Communications
System Integration Plans: Implement wireless communication protocols (Bluetooth/Wi-Fi) for seamless data transmission from all six sensor modalities, enabling real-time data fusion and establishing connectivity for the wearable accelerometer integration into the multimodal assessment system.
[Week 11 progress and contributions to final project placeholder]
Week 12 - Interface & Application Programming
UI and application development for the biomarker device interface.
UI design
Applications
User interface
System Integration Plans: Develop the complete user interface and application programming for the multimodal system, implementing the machine learning pipeline for intrinsic capacity score calculation and creating cloud integration for comprehensive data storage and analysis of all biomarker measurements.
[Week 12 progress and contributions to final project placeholder]
Week 13 - Wildcard & Final Orders
Final orders and wildcard week activities for project completion.
Final orders
Wildcard activities
Project completion
System Integration Plans: Complete final system integration, testing, and validation of the complete multimodal intrinsic capacity assessment platform, ensuring all six digital biomarkers work cohesively to provide accurate WHO-defined intrinsic capacity scores across all five domains (locomotor, cognition, vitality, sensory, psychological).
[Week 13 progress and contributions to final project placeholder]
Design Files
[Links to CAD/SVG/assets placeholder.]
Reflections & Learnings
[Reflection notes placeholder.]
Contributions
Acknowledgements and contributions that made this project possible.
Gladyshev Lab and Collaborators
Special thanks to the Gladyshev Lab and collaborators for the fruitful discussions that led to this multimodal intrinsic capacity assessment idea,
which supplements my PhD research goals in aging and longevity. The conceptual framework for integrating multiple digital biomarkers
to assess intrinsic capacity domains emerged from collaborative research discussions on aging biomarkers and healthspan assessment.
Ethical AI Use
Transparent documentation of AI assistance used in this final project work, following course guidelines for ethical AI usage.
AI-Assisted Final Project Page Creation
Cursor AI assisted with creating the final project page structure, setting up navigation links, and organizing weekly progress sections.
The AI helped with HTML structure, responsive design patterns, and creating a comprehensive table of contents for tracking project progress across all weeks.
AI-Assisted Intrinsic Capacity Research & Design
ChatGPT was used to research and develop the multimodal intrinsic capacity assessment framework, including the comprehensive coverage analysis table and technical pipeline design.
The AI assisted with structuring the WHO-defined intrinsic capacity domains, identifying appropriate digital biomarkers, and designing the fusion architecture for multimodal data processing.
AI-Assisted Final Project Development
Cursor AI assisted with developing the complete final project page structure, implementing the multimodal intrinsic capacity assessment framework, and creating comprehensive documentation.
The AI helped with HTML structure, responsive design, weekly system integration plans, and organizing the technical documentation for the complete biomarker assessment system.
AI-Assisted Final Project Presentation Structure
Cursor AI assisted with finalizing the project presentation structure to ensure full compliance with MIT Academy project presentation requirements.
The AI helped implement all required sections including answering questions, design documentation, bill of materials, individual mastery requirements,
course presentation structure, and spiral model development approach visualization.
AI-Assisted Camera System Development
ChatGPT was used to discuss camera system implementation strategies, image processing algorithms, and EdgeAI integration approaches.
The AI assisted with understanding Floyd-Steinberg dithering implementation, touch sensor integration, and exploring TinyML deployment options for the XIAO ESP32S3 platform.
This work is licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
Perfect! I've fixed the height inconsistency in the project highlights section. Here's what I changed:
Changes Made:
1. Added align-items:stretch to the grid container to ensure all columns stretch to the same height
2. Added flexbox layout to each column with display:flex; flex-direction:column; height:100%
3. Set fixed image height of 200px for all images with object-fit:cover to maintain aspect ratio
4. Used flexbox for image containers with flex:1 to distribute space evenly
5. Centered images vertically within their containers using justify-content:center
Now all three items in the project highlights row will have exactly the same height, with:
The layout will now look much more professional and balanced, with all three camera system highlights having uniform dimensions.
I'll make the images in the project highlights section clickable links that navigate to the camera subsystem section. Let me update the HTML to wrap each image in a link.
Final Project · HTMAA 2025 · Saleem A. Al Dajani
Final Project
Bioprinting & Aging Biomarker Device · HTMAA 2025
Project Highlights
Camera Works!
XIAO ESP32S3 camera successfully captures and displays images on OLED screen using Floyd-Steinberg dithering
Vision Board
Conceptual visualization of the multimodal intrinsic capacity assessment system integrating grip strength, voice analysis, facial recognition, video motion capture, reaction time measurement, and wearable accelerometer data.
Intrinsic Capacity (IC) Coverage by Digital Biomarkers
✅ Strong coverage |
🔸 Partial/indirect |
❌ Not covered |
View full table →
Multimodal IC Pipeline
Inputs: Grip Strength, Voice, Face, Video, Reaction Time, Wearable Accelerometer
Process: Feature extraction → Embeddings → Fusion layer → IC Score
Output: Overall Intrinsic Capacity Score + Domain sub-scores
Weekly System Development
Weeks 0-1: Project foundation, cutting techniques for device components
Weeks 2-4: Electronics foundation, embedded programming, PCB design
Weeks 5-7: Input devices, sensors for grip strength, voice, face detection
Weeks 8-10: Output devices, mechanical design, system integration
Weeks 11-13: Communication, UI development, final integration
Project Presentation
Summary Slide: [Placeholder for project summary slide download]
One Minute Video: [Placeholder for 1-minute video showing conception, construction, and operation]
Final Project Spiral Development Model
Development Approach: Following the spiral model methodology, this final project will iterate through multiple development cycles, each building upon previous work while addressing new requirements and risks.
Cycle 1: Minimal viable project for class scope
Cycle 2: Core functionality expansion
Cycle 3: Advanced features and integration
Cycle 4: Future research applications
Table of Contents
Project Overview
Design & Development
Weekly Progress (Weeks 0-13)
• Week 0 - Introduction
• Week 1 - Cutting
• Week 2 - Programming
• Week 3 - 3D Printing
• Week 4 - Electronics Design
• Week 5 - Electronics Production
• Week 6 - Machining
• Week 7 - Input Devices
• Week 8 - Output Devices
• Week 9 - Molding & Casting
• Week 10 - Mechanical Design
• Week 11 - Networking
• Week 12 - Interface Programming
• Week 13 - Final Integration
Project Introduction
[Project introduction placeholder - describing the bioprinting and aging biomarker device project.]
[Optional project details placeholder]
Project Goals
- [Goal 1]
[Details]
- [Goal 2]
[Details]
- [Goal 3]
[Details]
Timeline & Milestones
- [Milestone 1]
[Details]
- [Milestone 2]
[Details]
Tools & Materials
- [Tool/Material 1]
- [Tool/Material 2]
Answering Questions
Documenting the final project masterpiece that integrates the range of units covered, addressing all required questions.
What does it do?
[Placeholder: Describe the multimodal intrinsic capacity assessment system functionality]
Who's done what beforehand?
[Placeholder: Literature review and prior work in aging biomarkers and intrinsic capacity assessment]
What sources did you use?
[Placeholder: Research papers, open-source projects, and reference materials]
What did you design?
[Placeholder: Custom hardware, software, and integration systems designed]
What materials and components were used?
[Placeholder: Complete list of materials, sensors, microcontrollers, and components]
Where did they come from?
[Placeholder: Suppliers, vendors, and sourcing information]
How much did they cost?
[Placeholder: Detailed cost breakdown and budget analysis]
What parts and systems were made?
[Placeholder: Custom fabricated parts, 3D printed components, and assembled systems]
What tools and processes were used?
[Placeholder: Laser cutting, 3D printing, PCB fabrication, programming, and testing processes]
What questions were answered?
[Placeholder: Research questions addressed and hypotheses tested]
What worked? What didn't?
[Placeholder: Successes, challenges, and lessons learned]
How was it evaluated?
[Placeholder: Testing protocols, validation methods, and evaluation criteria]
What are the implications?
[Placeholder: Impact on aging research, clinical applications, and future development]
Design
Your project should incorporate 2D and 3D design, multiple additive and subtractive fabrication processes, electronics design and production, embedded microcontroller design, interfacing, and programming, system integration and packaging.
2D Design
2D design work for the multimodal intrinsic capacity assessment system:
- [Placeholder: Laser cutting designs for device housing components]
- [Placeholder: Vinyl cutting designs for labels and UI elements]
- [Placeholder: PCB layout designs and schematics]
- [Placeholder: 2D technical drawings and assembly guides]
- [Placeholder: User interface mockups and wireframes]
Tools Used: Inkscape, KiCad, Adobe Illustrator, Figma
3D Design
3D design work for device components and integration:
- [Placeholder: 3D printed device housings and enclosures]
- [Placeholder: Custom sensor mounting brackets and fixtures]
- [Placeholder: Ergonomic grip strength measurement device]
- [Placeholder: Camera mounting systems for facial recognition]
- [Placeholder: Integrated system assembly and packaging]
Tools Used: Fusion 360, FreeCAD, OpenSCAD, PrusaSlicer
Fabrication Processes Integration
Additive: 3D printing for custom components
Subtractive: Laser cutting, milling for precision parts
Electronics: PCB design and production
Programming: Embedded microcontroller development
Bill of Materials
Where possible, you should make rather than buy the parts of your project. Complete breakdown of materials, components, and sourcing information.
Bill of Materials
Complete list of materials and components:
Electronics Components
- [Placeholder: Microcontrollers and development boards]
- [Placeholder: Sensors (force, accelerometer, microphone)]
- [Placeholder: Camera modules and display components]
- [Placeholder: Power management and connectivity modules]
Mechanical Components
- [Placeholder: 3D printing materials (PLA, PETG)]
- [Placeholder: Laser cutting materials (acrylic, wood)]
- [Placeholder: Fasteners and mounting hardware]
- [Placeholder: Enclosure and housing materials]
Cost Breakdown
[Placeholder: Detailed cost analysis and budget tracking]
Make vs Buy
Strategic decisions on fabrication vs. purchasing:
✅ Made Components
- [Placeholder: Custom 3D printed housings]
- [Placeholder: Laser cut mounting brackets]
- [Placeholder: Custom PCB designs]
- [Placeholder: Integrated sensor assemblies]
🔸 Modified Components
- [Placeholder: Open-source grip strength meter adaptation]
- [Placeholder: Commercial sensor integration]
- [Placeholder: Existing microcontroller customization]
❌ Purchased Components
- [Placeholder: Standard electronic components]
- [Placeholder: Commercial sensors and modules]
- [Placeholder: Development boards and tools]
Fabrication Process
[Fabrication process documentation placeholder.]
Testing & Validation
[Testing and validation documentation placeholder.]
Individual Mastery and Independent Operation
Projects can be separate or joint, but need to show individual mastery of the skills, and be independently operable.
Individual Mastery
Demonstration of individual skills across all course units:
2D and 3D Design
- [Placeholder: Individual CAD modeling and design work]
- [Placeholder: Personal contribution to design decisions]
Fabrication Processes
- [Placeholder: Personal hands-on fabrication work]
- [Placeholder: Individual mastery of tools and processes]
Electronics and Programming
- [Placeholder: Individual PCB design and programming]
- [Placeholder: Personal debugging and troubleshooting]
Independent Operation
Project operates independently without external dependencies:
✅ Standalone Functionality
- [Placeholder: Complete system integration]
- [Placeholder: Self-contained operation]
- [Placeholder: Independent data collection and processing]
✅ User Independence
- [Placeholder: User-friendly interface]
- [Placeholder: Clear operation instructions]
- [Placeholder: Minimal external assistance required]
✅ Documentation
- [Placeholder: Complete technical documentation]
- [Placeholder: Assembly and operation guides]
- [Placeholder: Troubleshooting and maintenance]
Course Presentation
Present your final project, weekly and group assignments, and documentation.
Final Project Presentation
Complete presentation of the multimodal intrinsic capacity assessment system:
- [Placeholder: Final project demonstration]
- [Placeholder: Technical documentation presentation]
- [Placeholder: Results and evaluation discussion]
Weekly Assignments
Integration of weekly work into final project:
- [Placeholder: Week-by-week contribution summary]
- [Placeholder: Skills demonstration across all units]
- [Placeholder: Progressive development documentation]
Group Assignments
Collaborative work and individual contributions:
- [Placeholder: Group project contributions]
- [Placeholder: Individual role and responsibilities]
- [Placeholder: Collaborative learning outcomes]
Useful Documentation
Helpful resources, documentation, and design files for the multimodal intrinsic capacity assessment system.
Open Source Grip Strength Meter
A cost-effective $50 grip strength measurement system that can be further optimized for our multimodal assessment platform.
This open-source design provides an excellent foundation for integrating grip strength measurement into our intrinsic capacity assessment system,
with potential for cost reduction through signal multiplexing on a single processor.
Available Resources:
- Complete design files and schematics
- Arduino-based firmware and code repository
- 3D printing files for device housing
- Assembly instructions and documentation
- Calibration procedures and testing protocols
- Integration examples for data collection systems
Complete Intrinsic Capacity Coverage Analysis
Comprehensive analysis of how different digital biomarkers cover the five domains of intrinsic capacity (IC) as defined by WHO.
Legend:
✅ Strong coverage |
🔸 Partial/indirect coverage |
❌ Not covered
Multimodal Intrinsic Capacity Pipeline
Detailed technical pipeline for processing multiple digital biomarkers to generate intrinsic capacity scores.
Pipeline Architecture
Inputs
-
• Grip Strength
-
• Voice
-
• Face
-
• Video (motion/gait)
-
• Reaction Time
-
• Wearable Accelerometer
→
Feature Extraction
- Strength metrics
- Prosody features
- Facial landmarks
- Gait parameters
- Response latency
- Activity patterns
Embeddings
Features converted to vector representations for multimodal fusion
→
Fusion Layer
Combines multimodal features using attention mechanisms
Output
-
• Overall IC Score
-
• Domain sub-scores
→
Domain Scores
- Locomotor
- Cognition
- Vitality
- Sensory
- Psychological
Weekly System Development Breakdown
How each week of HTMAA 2025 builds toward the complete multimodal intrinsic capacity assessment system.
Week 0: Project Ideation
Initial concept development and planning
- Project planning and documentation structure
- Research direction and concept sketches
Week 1: Precision Cutting
Laser and vinyl cutting techniques
- Device housing components via laser cutting
- Sensor mounting brackets and enclosures
- Vinyl cutting for device labeling and UI elements
Week 2: Embedded Programming
Electronics basics and microcontroller programming
- Microcontroller programming for data collection
- Basic sensor interface circuits
Week 3: 3D Scanning & Printing
3D technologies for device components
- 3D scanning for custom component design
- 3D printing for device housings
Week 4: Electronics Design
EDA and schematic design
- PCB design for grip strength measurement
- Sensor interface circuits and signal conditioning
- Power management and data storage systems
Week 5: Electronics Production
PCB fabrication and assembly
- PCB fabrication and debugging
- Component assembly and testing
Week 6: Computer-controlled Machining
CAM and precision milling
- Precision components via milling
- Custom mechanical parts
Week 7: Input Devices
Sensor integration for data collection
- Force sensors for grip strength measurement
- Microphones for voice analysis
- Camera systems for facial expression analysis
- Reaction time measurement circuits
Week 8: Output Devices
Actuators and system integration
- Display systems for real-time feedback
- Haptic feedback for user interaction
Week 9: Molding & Casting
Forming and resin techniques
- 3D printing and molding for custom components
- Bioprinting molds and device components
Week 10: Mechanical & Machine Design
System integration and mechanical design
- Mechanical design for ergonomic device housing
- System integration and calibration protocols
Week 11: Networking & Communications
Connectivity and communication protocols
- Bluetooth/Wi-Fi connectivity for data transmission
- Wearable accelerometer integration and data fusion
Week 12: Interface & Application Programming
UI development and application programming
- Mobile app development for user interface
- Cloud integration for data storage and analysis
- Machine learning pipeline for IC score calculation
Week 13: Wildcard & Final Integration
Final orders and complete system deployment
- Final testing, validation, and documentation
- System integration and deployment
Camera Subsystem
Advanced camera system implementation using XIAO ESP32S3 Sense with real-time image processing, EdgeAI integration, and interactive selfie capture functionality.
System Overview
The camera system successfully captures images, processes them into bitmaps, and displays them on an OLED screen using advanced Floyd-Steinberg dithering algorithms.
Video Demonstrations
Camera Bot Selfie
Demonstration of the interactive selfie capture system with touch controls
Picture of Picture
Meta demonstration showing the camera system capturing its own display
Code Implementation
60-Second Auto Capture System
Automated camera system that captures and displays images every 60 seconds using advanced image processing techniques.
Pseudocode Implementation:
1. Initialize camera with PSRAM frame buffers
2. Configure OLED display (128x64 pixels)
3. Set up 60-second capture interval timer
4. In main loop:
a. Check if 60 seconds have elapsed
b. Capture image from camera
c. Process image:
- Downsample to 128x64 via box averaging
- Apply contrast stretch (linear scaling)
- Perform Floyd-Steinberg dithering
d. Display processed bitmap on OLED
e. Release frame buffer
5. Repeat process
Touch-Controlled Capture System
Interactive camera system with touch controls allowing manual capture triggers in addition to automatic timing.
Pseudocode Implementation:
1. Initialize camera and OLED display
2. Set up touch pins (GPIO1 & GPIO2) with threshold detection
3. Configure 60-second auto-capture timer
4. In main loop:
a. Update touch sensor readings
b. Detect touch press events (justPressed)
c. Check for capture trigger:
- Touch press OR 60-second timer elapsed
d. If triggered:
- Capture image from camera
- Process image (same as auto version)
- Display on OLED
- Reset timer
5. Continue monitoring for next trigger
How It Was Done
The camera system implementation began with code from Charles Lu's electronics production weekly assignment,
which was based on the official XIAO tutorial.
Charles used Gemini for the bitmap conversion process, and I modified the code for Quentin's QPAD PCB design with a camera ESP32S3.
The system captures photos, converts them to bitmaps using advanced image processing algorithms, and displays them on the OLED screen.
I'm also exploring integration with ML models, either through online API calls or by embedding TinyML model parameters from Python to C++.
Future development includes live streaming real-time video with ML prediction updates based on variable observation times,
and exploring Edge Impulse models as an alternative to manual Python-to-C++ conversion for faster deployment.
EdgeAI/TinyML Integration
Edge AI can also be implemented using Edge Impulse models, which may be faster than manually converting Python models to C++.
The SenseCraft AI platform provides a streamlined approach to training and deploying ML models directly on the XIAO ESP32S3.
Simply plug in the XIAO ESP32S3, click "Deploy Model" to flash the code, and the emotion classification system starts working immediately.
Development Discussion: ChatGPT Session on Camera System Development
Week 0 - Introduction & Design
Project ideation and initial concept development for bioprinting rejuvenated tissue and aging biomarker devices.
Project planning
Concept sketches
Research direction
System Integration Plans: Establish the foundational architecture for multimodal data collection by designing the overall system framework that will integrate all six digital biomarkers (grip strength, voice, face, video, reaction time, wearable accelerometer) into a cohesive intrinsic capacity assessment platform.
[Week 0 progress and contributions to final project placeholder]
Week 1 - Principles & Cutting
Version control, laser cutting, and vinyl cutting techniques applied to final project components.
Laser cutting
Vinyl cutting
Version control
System Integration Plans: Fabricate precision-cut housing components and mounting brackets for all sensor modules (force sensors, microphones, cameras, reaction time circuits) using laser cutting, while creating vinyl-cut labels and UI elements for device identification and user guidance.
[Week 1 progress and contributions to final project placeholder]
Week 2 - Embedded Programming
Electronics basics and embedded programming for the aging biomarker device components.
Microcontrollers
Programming
Electronics
System Integration Plans: Develop embedded programming protocols for real-time data collection from all six biomarker sensors, implementing initial signal processing algorithms and establishing the communication framework for multimodal data fusion.
[Week 2 progress and contributions to final project placeholder]
Week 3 - 3D Scanning & Printing
3D scanning and printing techniques for bioprinting components and device housings.
3D scanning
3D printing
AI tools
System Integration Plans: Create custom 3D-printed components for camera mounting systems and facial recognition hardware, while developing 3D scanning protocols for ergonomic device design that accommodates all sensor modalities in a user-friendly form factor.
[Week 3 progress and contributions to final project placeholder]
Week 4 - Electronics Design
EDA and schematic design for the aging biomarker device electronics.
EDA tools
Schematic design
Circuit design
System Integration Plans: Design comprehensive PCB schematics that integrate force sensor circuits for grip strength measurement, microphone preamplifiers for voice analysis, camera interfaces for facial recognition, and timing circuits for reaction time assessment into a unified electronics platform.
[Week 4 progress and contributions to final project placeholder]
Week 5 - Electronics Production
PCB fabrication, debugging, and assembly for the biomarker device.
PCB fabrication
Debugging
Assembly
System Integration Plans: Fabricate and assemble the integrated PCB containing all sensor interfaces, implementing power management systems for continuous operation and establishing data storage protocols for the multimodal biomarker data collection system.
[Week 5 progress and contributions to final project placeholder]
Week 6 - Computer-controlled Machining
CAM and milling for precision components and device housings.
CAM
Milling
Precision machining
System Integration Plans: Machine precision mechanical components for the integrated device housing using computer-controlled milling, ensuring proper alignment and mounting for all sensor modules while maintaining ergonomic design for user comfort during multimodal data collection.
[Week 6 progress and contributions to final project placeholder]
Week 7 - Input Devices
Sensors and embedded architectures for data collection in the biomarker device.
Sensors
Input devices
Data collection
System Integration Plans: Integrate all six input sensor systems (force sensors for grip strength, microphones for voice analysis, cameras for facial recognition and gait analysis, reaction time circuits, and wearable accelerometer) into the unified data collection platform with real-time processing capabilities.
[Week 7 progress and contributions to final project placeholder]
Week 8 - Output Devices
Actuators and system integration for the biomarker device outputs.
Actuators
Output devices
System integration
System Integration Plans: Implement output devices including display systems for real-time intrinsic capacity feedback and haptic feedback mechanisms for user interaction, creating an intuitive interface for the multimodal biomarker assessment system.
[Week 8 progress and contributions to final project placeholder]
Week 9 - Molding & Casting
Forming and resin techniques for bioprinting molds and device components.
Molding
Casting
Resins
System Integration Plans: Create custom molded components for the bioprinting aspects of the project and develop specialized casings for sensor protection, ensuring the device can withstand continuous use during multimodal data collection sessions.
[Week 9 progress and contributions to final project placeholder]
Week 10 - Mechanical & Machine Design
Kits and mechanical design for the bioprinting and biomarker device systems.
Mechanical design
Machine design
System integration
System Integration Plans: Complete the mechanical design integration of all system components, implementing calibration protocols for sensor alignment and developing the complete mechanical framework that houses all six digital biomarker measurement systems.
[Week 10 progress and contributions to final project placeholder]
Week 11 - Networking & Communications
BLE, Wi-Fi, and communication protocols for the biomarker device connectivity.
BLE
Wi-Fi
Communications
System Integration Plans: Implement wireless communication protocols (Bluetooth/Wi-Fi) for seamless data transmission from all six sensor modalities, enabling real-time data fusion and establishing connectivity for the wearable accelerometer integration into the multimodal assessment system.
[Week 11 progress and contributions to final project placeholder]
Week 12 - Interface & Application Programming
UI and application development for the biomarker device interface.
UI design
Applications
User interface
System Integration Plans: Develop the complete user interface and application programming for the multimodal system, implementing the machine learning pipeline for intrinsic capacity score calculation and creating cloud integration for comprehensive data storage and analysis of all biomarker measurements.
[Week 12 progress and contributions to final project placeholder]
Week 13 - Wildcard & Final Orders
Final orders and wildcard week activities for project completion.
Final orders
Wildcard activities
Project completion
System Integration Plans: Complete final system integration, testing, and validation of the complete multimodal intrinsic capacity assessment platform, ensuring all six digital biomarkers work cohesively to provide accurate WHO-defined intrinsic capacity scores across all five domains (locomotor, cognition, vitality, sensory, psychological).
[Week 13 progress and contributions to final project placeholder]
Design Files
[Links to CAD/SVG/assets placeholder.]
Reflections & Learnings
[Reflection notes placeholder.]
Contributions
Acknowledgements and contributions that made this project possible.
Gladyshev Lab and Collaborators
Special thanks to the Gladyshev Lab and collaborators for the fruitful discussions that led to this multimodal intrinsic capacity assessment idea,
which supplements my PhD research goals in aging and longevity. The conceptual framework for integrating multiple digital biomarkers
to assess intrinsic capacity domains emerged from collaborative research discussions on aging biomarkers and healthspan assessment.
Ethical AI Use
Transparent documentation of AI assistance used in this final project work, following course guidelines for ethical AI usage.
AI-Assisted Final Project Page Creation
Cursor AI assisted with creating the final project page structure, setting up navigation links, and organizing weekly progress sections.
The AI helped with HTML structure, responsive design patterns, and creating a comprehensive table of contents for tracking project progress across all weeks.
AI-Assisted Intrinsic Capacity Research & Design
ChatGPT was used to research and develop the multimodal intrinsic capacity assessment framework, including the comprehensive coverage analysis table and technical pipeline design.
The AI assisted with structuring the WHO-defined intrinsic capacity domains, identifying appropriate digital biomarkers, and designing the fusion architecture for multimodal data processing.
AI-Assisted Final Project Development
Cursor AI assisted with developing the complete final project page structure, implementing the multimodal intrinsic capacity assessment framework, and creating comprehensive documentation.
The AI helped with HTML structure, responsive design, weekly system integration plans, and organizing the technical documentation for the complete biomarker assessment system.
AI-Assisted Final Project Presentation Structure
Cursor AI assisted with finalizing the project presentation structure to ensure full compliance with MIT Academy project presentation requirements.
The AI helped implement all required sections including answering questions, design documentation, bill of materials, individual mastery requirements,
course presentation structure, and spiral model development approach visualization.
AI-Assisted Camera System Development
ChatGPT was used to discuss camera system implementation strategies, image processing algorithms, and EdgeAI integration approaches.
The AI assisted with understanding Floyd-Steinberg dithering implementation, touch sensor integration, and exploring TinyML deployment options for the XIAO ESP32S3 platform.
This work is licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
Final Project · HTMAA 2025 · Saleem A. Al Dajani
Final Project
Bioprinting & Aging Biomarker Device · HTMAA 2025
Project Highlights
Camera Works!
XIAO ESP32S3 camera successfully captures and displays images on OLED screen using Floyd-Steinberg dithering
Vision Board
Conceptual visualization of the multimodal intrinsic capacity assessment system integrating grip strength, voice analysis, facial recognition, video motion capture, reaction time measurement, and wearable accelerometer data.
Intrinsic Capacity (IC) Coverage by Digital Biomarkers
✅ Strong coverage |
🔸 Partial/indirect |
❌ Not covered |
View full table →
Multimodal IC Pipeline
Inputs: Grip Strength, Voice, Face, Video, Reaction Time, Wearable Accelerometer
Process: Feature extraction → Embeddings → Fusion layer → IC Score
Output: Overall Intrinsic Capacity Score + Domain sub-scores
Weekly System Development
Weeks 0-1: Project foundation, cutting techniques for device components
Weeks 2-4: Electronics foundation, embedded programming, PCB design
Weeks 5-7: Input devices, sensors for grip strength, voice, face detection
Weeks 8-10: Output devices, mechanical design, system integration
Weeks 11-13: Communication, UI development, final integration
Project Presentation
Summary Slide: [Placeholder for project summary slide download]
One Minute Video: [Placeholder for 1-minute video showing conception, construction, and operation]
Final Project Spiral Development Model
Development Approach: Following the spiral model methodology, this final project will iterate through multiple development cycles, each building upon previous work while addressing new requirements and risks.
Cycle 1: Minimal viable project for class scope
Cycle 2: Core functionality expansion
Cycle 3: Advanced features and integration
Cycle 4: Future research applications
Table of Contents
Project Overview
Design & Development
Weekly Progress (Weeks 0-13)
• Week 0 - Introduction
• Week 1 - Cutting
• Week 2 - Programming
• Week 3 - 3D Printing
• Week 4 - Electronics Design
• Week 5 - Electronics Production
• Week 6 - Machining
• Week 7 - Input Devices
• Week 8 - Output Devices
• Week 9 - Molding & Casting
• Week 10 - Mechanical Design
• Week 11 - Networking
• Week 12 - Interface Programming
• Week 13 - Final Integration
Project Introduction
[Project introduction placeholder - describing the bioprinting and aging biomarker device project.]
[Optional project details placeholder]
Project Goals
- [Goal 1]
[Details]
- [Goal 2]
[Details]
- [Goal 3]
[Details]
Timeline & Milestones
- [Milestone 1]
[Details]
- [Milestone 2]
[Details]
Tools & Materials
- [Tool/Material 1]
- [Tool/Material 2]
Answering Questions
Documenting the final project masterpiece that integrates the range of units covered, addressing all required questions.
What does it do?
[Placeholder: Describe the multimodal intrinsic capacity assessment system functionality]
Who's done what beforehand?
[Placeholder: Literature review and prior work in aging biomarkers and intrinsic capacity assessment]
What sources did you use?
[Placeholder: Research papers, open-source projects, and reference materials]
What did you design?
[Placeholder: Custom hardware, software, and integration systems designed]
What materials and components were used?
[Placeholder: Complete list of materials, sensors, microcontrollers, and components]
Where did they come from?
[Placeholder: Suppliers, vendors, and sourcing information]
How much did they cost?
[Placeholder: Detailed cost breakdown and budget analysis]
What parts and systems were made?
[Placeholder: Custom fabricated parts, 3D printed components, and assembled systems]
What tools and processes were used?
[Placeholder: Laser cutting, 3D printing, PCB fabrication, programming, and testing processes]
What questions were answered?
[Placeholder: Research questions addressed and hypotheses tested]
What worked? What didn't?
[Placeholder: Successes, challenges, and lessons learned]
How was it evaluated?
[Placeholder: Testing protocols, validation methods, and evaluation criteria]
What are the implications?
[Placeholder: Impact on aging research, clinical applications, and future development]
Design
Your project should incorporate 2D and 3D design, multiple additive and subtractive fabrication processes, electronics design and production, embedded microcontroller design, interfacing, and programming, system integration and packaging.
2D Design
2D design work for the multimodal intrinsic capacity assessment system:
- [Placeholder: Laser cutting designs for device housing components]
- [Placeholder: Vinyl cutting designs for labels and UI elements]
- [Placeholder: PCB layout designs and schematics]
- [Placeholder: 2D technical drawings and assembly guides]
- [Placeholder: User interface mockups and wireframes]
Tools Used: Inkscape, KiCad, Adobe Illustrator, Figma
3D Design
3D design work for device components and integration:
- [Placeholder: 3D printed device housings and enclosures]
- [Placeholder: Custom sensor mounting brackets and fixtures]
- [Placeholder: Ergonomic grip strength measurement device]
- [Placeholder: Camera mounting systems for facial recognition]
- [Placeholder: Integrated system assembly and packaging]
Tools Used: Fusion 360, FreeCAD, OpenSCAD, PrusaSlicer
Fabrication Processes Integration
Additive: 3D printing for custom components
Subtractive: Laser cutting, milling for precision parts
Electronics: PCB design and production
Programming: Embedded microcontroller development
Bill of Materials
Where possible, you should make rather than buy the parts of your project. Complete breakdown of materials, components, and sourcing information.
Bill of Materials
Complete list of materials and components:
Electronics Components
- [Placeholder: Microcontrollers and development boards]
- [Placeholder: Sensors (force, accelerometer, microphone)]
- [Placeholder: Camera modules and display components]
- [Placeholder: Power management and connectivity modules]
Mechanical Components
- [Placeholder: 3D printing materials (PLA, PETG)]
- [Placeholder: Laser cutting materials (acrylic, wood)]
- [Placeholder: Fasteners and mounting hardware]
- [Placeholder: Enclosure and housing materials]
Cost Breakdown
[Placeholder: Detailed cost analysis and budget tracking]
Make vs Buy
Strategic decisions on fabrication vs. purchasing:
✅ Made Components
- [Placeholder: Custom 3D printed housings]
- [Placeholder: Laser cut mounting brackets]
- [Placeholder: Custom PCB designs]
- [Placeholder: Integrated sensor assemblies]
🔸 Modified Components
- [Placeholder: Open-source grip strength meter adaptation]
- [Placeholder: Commercial sensor integration]
- [Placeholder: Existing microcontroller customization]
❌ Purchased Components
- [Placeholder: Standard electronic components]
- [Placeholder: Commercial sensors and modules]
- [Placeholder: Development boards and tools]
Fabrication Process
[Fabrication process documentation placeholder.]
Testing & Validation
[Testing and validation documentation placeholder.]
Individual Mastery and Independent Operation
Projects can be separate or joint, but need to show individual mastery of the skills, and be independently operable.
Individual Mastery
Demonstration of individual skills across all course units:
2D and 3D Design
- [Placeholder: Individual CAD modeling and design work]
- [Placeholder: Personal contribution to design decisions]
Fabrication Processes
- [Placeholder: Personal hands-on fabrication work]
- [Placeholder: Individual mastery of tools and processes]
Electronics and Programming
- [Placeholder: Individual PCB design and programming]
- [Placeholder: Personal debugging and troubleshooting]
Independent Operation
Project operates independently without external dependencies:
✅ Standalone Functionality
- [Placeholder: Complete system integration]
- [Placeholder: Self-contained operation]
- [Placeholder: Independent data collection and processing]
✅ User Independence
- [Placeholder: User-friendly interface]
- [Placeholder: Clear operation instructions]
- [Placeholder: Minimal external assistance required]
✅ Documentation
- [Placeholder: Complete technical documentation]
- [Placeholder: Assembly and operation guides]
- [Placeholder: Troubleshooting and maintenance]
Course Presentation
Present your final project, weekly and group assignments, and documentation.
Final Project Presentation
Complete presentation of the multimodal intrinsic capacity assessment system:
- [Placeholder: Final project demonstration]
- [Placeholder: Technical documentation presentation]
- [Placeholder: Results and evaluation discussion]
Weekly Assignments
Integration of weekly work into final project:
- [Placeholder: Week-by-week contribution summary]
- [Placeholder: Skills demonstration across all units]
- [Placeholder: Progressive development documentation]
Group Assignments
Collaborative work and individual contributions:
- [Placeholder: Group project contributions]
- [Placeholder: Individual role and responsibilities]
- [Placeholder: Collaborative learning outcomes]
Useful Documentation
Helpful resources, documentation, and design files for the multimodal intrinsic capacity assessment system.
Open Source Grip Strength Meter
A cost-effective $50 grip strength measurement system that can be further optimized for our multimodal assessment platform.
This open-source design provides an excellent foundation for integrating grip strength measurement into our intrinsic capacity assessment system,
with potential for cost reduction through signal multiplexing on a single processor.
Available Resources:
- Complete design files and schematics
- Arduino-based firmware and code repository
- 3D printing files for device housing
- Assembly instructions and documentation
- Calibration procedures and testing protocols
- Integration examples for data collection systems
Complete Intrinsic Capacity Coverage Analysis
Comprehensive analysis of how different digital biomarkers cover the five domains of intrinsic capacity (IC) as defined by WHO.
Legend:
✅ Strong coverage |
🔸 Partial/indirect coverage |
❌ Not covered
Multimodal Intrinsic Capacity Pipeline
Detailed technical pipeline for processing multiple digital biomarkers to generate intrinsic capacity scores.
Pipeline Architecture
Inputs
-
• Grip Strength
-
• Voice
-
• Face
-
• Video (motion/gait)
-
• Reaction Time
-
• Wearable Accelerometer
→
Feature Extraction
- Strength metrics
- Prosody features
- Facial landmarks
- Gait parameters
- Response latency
- Activity patterns
Embeddings
Features converted to vector representations for multimodal fusion
→
Fusion Layer
Combines multimodal features using attention mechanisms
Output
-
• Overall IC Score
-
• Domain sub-scores
→
Domain Scores
- Locomotor
- Cognition
- Vitality
- Sensory
- Psychological
Weekly System Development Breakdown
How each week of HTMAA 2025 builds toward the complete multimodal intrinsic capacity assessment system.
Week 0: Project Ideation
Initial concept development and planning
- Project planning and documentation structure
- Research direction and concept sketches
Week 1: Precision Cutting
Laser and vinyl cutting techniques
- Device housing components via laser cutting
- Sensor mounting brackets and enclosures
- Vinyl cutting for device labeling and UI elements
Week 2: Embedded Programming
Electronics basics and microcontroller programming
- Microcontroller programming for data collection
- Basic sensor interface circuits
Week 3: 3D Scanning & Printing
3D technologies for device components
- 3D scanning for custom component design
- 3D printing for device housings
Week 4: Electronics Design
EDA and schematic design
- PCB design for grip strength measurement
- Sensor interface circuits and signal conditioning
- Power management and data storage systems
Week 5: Electronics Production
PCB fabrication and assembly
- PCB fabrication and debugging
- Component assembly and testing
Week 6: Computer-controlled Machining
CAM and precision milling
- Precision components via milling
- Custom mechanical parts
Week 7: Input Devices
Sensor integration for data collection
- Force sensors for grip strength measurement
- Microphones for voice analysis
- Camera systems for facial expression analysis
- Reaction time measurement circuits
Week 8: Output Devices
Actuators and system integration
- Display systems for real-time feedback
- Haptic feedback for user interaction
Week 9: Molding & Casting
Forming and resin techniques
- 3D printing and molding for custom components
- Bioprinting molds and device components
Week 10: Mechanical & Machine Design
System integration and mechanical design
- Mechanical design for ergonomic device housing
- System integration and calibration protocols
Week 11: Networking & Communications
Connectivity and communication protocols
- Bluetooth/Wi-Fi connectivity for data transmission
- Wearable accelerometer integration and data fusion
Week 12: Interface & Application Programming
UI development and application programming
- Mobile app development for user interface
- Cloud integration for data storage and analysis
- Machine learning pipeline for IC score calculation
Week 13: Wildcard & Final Integration
Final orders and complete system deployment
- Final testing, validation, and documentation
- System integration and deployment
Camera Subsystem
Advanced camera system implementation using XIAO ESP32S3 Sense with real-time image processing, EdgeAI integration, and interactive selfie capture functionality.
System Overview
The camera system successfully captures images, processes them into bitmaps, and displays them on an OLED screen using advanced Floyd-Steinberg dithering algorithms.
Video Demonstrations
Camera Bot Selfie
Demonstration of the interactive selfie capture system with touch controls
Picture of Picture
Meta demonstration showing the camera system capturing its own display
Code Implementation
60-Second Auto Capture System
Automated camera system that captures and displays images every 60 seconds using advanced image processing techniques.
Pseudocode Implementation:
1. Initialize camera with PSRAM frame buffers
2. Configure OLED display (128x64 pixels)
3. Set up 60-second capture interval timer
4. In main loop:
a. Check if 60 seconds have elapsed
b. Capture image from camera
c. Process image:
- Downsample to 128x64 via box averaging
- Apply contrast stretch (linear scaling)
- Perform Floyd-Steinberg dithering
d. Display processed bitmap on OLED
e. Release frame buffer
5. Repeat process
Touch-Controlled Capture System
Interactive camera system with touch controls allowing manual capture triggers in addition to automatic timing.
Pseudocode Implementation:
1. Initialize camera and OLED display
2. Set up touch pins (GPIO1 & GPIO2) with threshold detection
3. Configure 60-second auto-capture timer
4. In main loop:
a. Update touch sensor readings
b. Detect touch press events (justPressed)
c. Check for capture trigger:
- Touch press OR 60-second timer elapsed
d. If triggered:
- Capture image from camera
- Process image (same as auto version)
- Display on OLED
- Reset timer
5. Continue monitoring for next trigger
How It Was Done
The camera system implementation began with code from Charles Lu's electronics production weekly assignment,
which was based on the official XIAO tutorial.
Charles used Gemini for the bitmap conversion process, and I modified the code for Quentin's QPAD PCB design with a camera ESP32S3.
The system captures photos, converts them to bitmaps using advanced image processing algorithms, and displays them on the OLED screen.
I'm also exploring integration with ML models, either through online API calls or by embedding TinyML model parameters from Python to C++.
Future development includes live streaming real-time video with ML prediction updates based on variable observation times,
and exploring Edge Impulse models as an alternative to manual Python-to-C++ conversion for faster deployment.
EdgeAI/TinyML Integration
Edge AI can also be implemented using Edge Impulse models, which may be faster than manually converting Python models to C++.
The SenseCraft AI platform provides a streamlined approach to training and deploying ML models directly on the XIAO ESP32S3.
Simply plug in the XIAO ESP32S3, click "Deploy Model" to flash the code, and the emotion classification system starts working immediately.
Development Discussion: ChatGPT Session on Camera System Development
Week 0 - Introduction & Design
Project ideation and initial concept development for bioprinting rejuvenated tissue and aging biomarker devices.
Project planning
Concept sketches
Research direction
System Integration Plans: Establish the foundational architecture for multimodal data collection by designing the overall system framework that will integrate all six digital biomarkers (grip strength, voice, face, video, reaction time, wearable accelerometer) into a cohesive intrinsic capacity assessment platform.
[Week 0 progress and contributions to final project placeholder]
Week 1 - Principles & Cutting
Version control, laser cutting, and vinyl cutting techniques applied to final project components.
Laser cutting
Vinyl cutting
Version control
System Integration Plans: Fabricate precision-cut housing components and mounting brackets for all sensor modules (force sensors, microphones, cameras, reaction time circuits) using laser cutting, while creating vinyl-cut labels and UI elements for device identification and user guidance.
[Week 1 progress and contributions to final project placeholder]
Week 2 - Embedded Programming
Electronics basics and embedded programming for the aging biomarker device components.
Microcontrollers
Programming
Electronics
System Integration Plans: Develop embedded programming protocols for real-time data collection from all six biomarker sensors, implementing initial signal processing algorithms and establishing the communication framework for multimodal data fusion.
[Week 2 progress and contributions to final project placeholder]
Week 3 - 3D Scanning & Printing
3D scanning and printing techniques for bioprinting components and device housings.
3D scanning
3D printing
AI tools
System Integration Plans: Create custom 3D-printed components for camera mounting systems and facial recognition hardware, while developing 3D scanning protocols for ergonomic device design that accommodates all sensor modalities in a user-friendly form factor.
[Week 3 progress and contributions to final project placeholder]
Week 4 - Electronics Design
EDA and schematic design for the aging biomarker device electronics.
EDA tools
Schematic design
Circuit design
System Integration Plans: Design comprehensive PCB schematics that integrate force sensor circuits for grip strength measurement, microphone preamplifiers for voice analysis, camera interfaces for facial recognition, and timing circuits for reaction time assessment into a unified electronics platform.
[Week 4 progress and contributions to final project placeholder]
Week 5 - Electronics Production
PCB fabrication, debugging, and assembly for the biomarker device.
PCB fabrication
Debugging
Assembly
System Integration Plans: Fabricate and assemble the integrated PCB containing all sensor interfaces, implementing power management systems for continuous operation and establishing data storage protocols for the multimodal biomarker data collection system.
[Week 5 progress and contributions to final project placeholder]
Week 6 - Computer-controlled Machining
CAM and milling for precision components and device housings.
CAM
Milling
Precision machining
System Integration Plans: Machine precision mechanical components for the integrated device housing using computer-controlled milling, ensuring proper alignment and mounting for all sensor modules while maintaining ergonomic design for user comfort during multimodal data collection.
[Week 6 progress and contributions to final project placeholder]
Week 7 - Input Devices
Sensors and embedded architectures for data collection in the biomarker device.
Sensors
Input devices
Data collection
System Integration Plans: Integrate all six input sensor systems (force sensors for grip strength, microphones for voice analysis, cameras for facial recognition and gait analysis, reaction time circuits, and wearable accelerometer) into the unified data collection platform with real-time processing capabilities.
[Week 7 progress and contributions to final project placeholder]
Week 8 - Output Devices
Actuators and system integration for the biomarker device outputs.
Actuators
Output devices
System integration
System Integration Plans: Implement output devices including display systems for real-time intrinsic capacity feedback and haptic feedback mechanisms for user interaction, creating an intuitive interface for the multimodal biomarker assessment system.
[Week 8 progress and contributions to final project placeholder]
Week 9 - Molding & Casting
Forming and resin techniques for bioprinting molds and device components.
Molding
Casting
Resins
System Integration Plans: Create custom molded components for the bioprinting aspects of the project and develop specialized casings for sensor protection, ensuring the device can withstand continuous use during multimodal data collection sessions.
[Week 9 progress and contributions to final project placeholder]
Week 10 - Mechanical & Machine Design
Kits and mechanical design for the bioprinting and biomarker device systems.
Mechanical design
Machine design
System integration
System Integration Plans: Complete the mechanical design integration of all system components, implementing calibration protocols for sensor alignment and developing the complete mechanical framework that houses all six digital biomarker measurement systems.
[Week 10 progress and contributions to final project placeholder]
Week 11 - Networking & Communications
BLE, Wi-Fi, and communication protocols for the biomarker device connectivity.
BLE
Wi-Fi
Communications
System Integration Plans: Implement wireless communication protocols (Bluetooth/Wi-Fi) for seamless data transmission from all six sensor modalities, enabling real-time data fusion and establishing connectivity for the wearable accelerometer integration into the multimodal assessment system.
[Week 11 progress and contributions to final project placeholder]
Week 12 - Interface & Application Programming
UI and application development for the biomarker device interface.
UI design
Applications
User interface
System Integration Plans: Develop the complete user interface and application programming for the multimodal system, implementing the machine learning pipeline for intrinsic capacity score calculation and creating cloud integration for comprehensive data storage and analysis of all biomarker measurements.
[Week 12 progress and contributions to final project placeholder]
Week 13 - Wildcard & Final Orders
Final orders and wildcard week activities for project completion.
Final orders
Wildcard activities
Project completion
System Integration Plans: Complete final system integration, testing, and validation of the complete multimodal intrinsic capacity assessment platform, ensuring all six digital biomarkers work cohesively to provide accurate WHO-defined intrinsic capacity scores across all five domains (locomotor, cognition, vitality, sensory, psychological).
[Week 13 progress and contributions to final project placeholder]
Design Files
[Links to CAD/SVG/assets placeholder.]
Reflections & Learnings
[Reflection notes placeholder.]
Contributions
Acknowledgements and contributions that made this project possible.
Gladyshev Lab and Collaborators
Special thanks to the Gladyshev Lab and collaborators for the fruitful discussions that led to this multimodal intrinsic capacity assessment idea,
which supplements my PhD research goals in aging and longevity. The conceptual framework for integrating multiple digital biomarkers
to assess intrinsic capacity domains emerged from collaborative research discussions on aging biomarkers and healthspan assessment.
Ethical AI Use
Transparent documentation of AI assistance used in this final project work, following course guidelines for ethical AI usage.
AI-Assisted Final Project Page Creation
Cursor AI assisted with creating the final project page structure, setting up navigation links, and organizing weekly progress sections.
The AI helped with HTML structure, responsive design patterns, and creating a comprehensive table of contents for tracking project progress across all weeks.
AI-Assisted Intrinsic Capacity Research & Design
ChatGPT was used to research and develop the multimodal intrinsic capacity assessment framework, including the comprehensive coverage analysis table and technical pipeline design.
The AI assisted with structuring the WHO-defined intrinsic capacity domains, identifying appropriate digital biomarkers, and designing the fusion architecture for multimodal data processing.
AI-Assisted Final Project Development
Cursor AI assisted with developing the complete final project page structure, implementing the multimodal intrinsic capacity assessment framework, and creating comprehensive documentation.
The AI helped with HTML structure, responsive design, weekly system integration plans, and organizing the technical documentation for the complete biomarker assessment system.
AI-Assisted Final Project Presentation Structure
Cursor AI assisted with finalizing the project presentation structure to ensure full compliance with MIT Academy project presentation requirements.
The AI helped implement all required sections including answering questions, design documentation, bill of materials, individual mastery requirements,
course presentation structure, and spiral model development approach visualization.
AI-Assisted Camera System Development
ChatGPT was used to discuss camera system implementation strategies, image processing algorithms, and EdgeAI integration approaches.
The AI assisted with understanding Floyd-Steinberg dithering implementation, touch sensor integration, and exploring TinyML deployment options for the XIAO ESP32S3 platform.
This work is licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
Final Project · HTMAA 2025 · Saleem A. Al Dajani
Final Project
Bioprinting & Aging Biomarker Device · HTMAA 2025
Project Highlights
Camera Works!
XIAO ESP32S3 camera successfully captures and displays images on OLED screen using Floyd-Steinberg dithering
Vision Board
Conceptual visualization of the multimodal intrinsic capacity assessment system integrating grip strength, voice analysis, facial recognition, video motion capture, reaction time measurement, and wearable accelerometer data.
Intrinsic Capacity (IC) Coverage by Digital Biomarkers
✅ Strong coverage |
🔸 Partial/indirect |
❌ Not covered |
View full table →
Multimodal IC Pipeline
Inputs: Grip Strength, Voice, Face, Video, Reaction Time, Wearable Accelerometer
Process: Feature extraction → Embeddings → Fusion layer → IC Score
Output: Overall Intrinsic Capacity Score + Domain sub-scores
Weekly System Development
Weeks 0-1: Project foundation, cutting techniques for device components
Weeks 2-4: Electronics foundation, embedded programming, PCB design
Weeks 5-7: Input devices, sensors for grip strength, voice, face detection
Weeks 8-10: Output devices, mechanical design, system integration
Weeks 11-13: Communication, UI development, final integration
Project Presentation
Summary Slide: [Placeholder for project summary slide download]
One Minute Video: [Placeholder for 1-minute video showing conception, construction, and operation]
Final Project Spiral Development Model
Development Approach: Following the spiral model methodology, this final project will iterate through multiple development cycles, each building upon previous work while addressing new requirements and risks.
Cycle 1: Minimal viable project for class scope
Cycle 2: Core functionality expansion
Cycle 3: Advanced features and integration
Cycle 4: Future research applications
Table of Contents
Project Overview
Design & Development
Weekly Progress (Weeks 0-13)
• Week 0 - Introduction
• Week 1 - Cutting
• Week 2 - Programming
• Week 3 - 3D Printing
• Week 4 - Electronics Design
• Week 5 - Electronics Production
• Week 6 - Machining
• Week 7 - Input Devices
• Week 8 - Output Devices
• Week 9 - Molding & Casting
• Week 10 - Mechanical Design
• Week 11 - Networking
• Week 12 - Interface Programming
• Week 13 - Final Integration
Project Introduction
[Project introduction placeholder - describing the bioprinting and aging biomarker device project.]
[Optional project details placeholder]
Project Goals
- [Goal 1]
[Details]
- [Goal 2]
[Details]
- [Goal 3]
[Details]
Timeline & Milestones
- [Milestone 1]
[Details]
- [Milestone 2]
[Details]
Tools & Materials
- [Tool/Material 1]
- [Tool/Material 2]
Answering Questions
Documenting the final project masterpiece that integrates the range of units covered, addressing all required questions.
What does it do?
[Placeholder: Describe the multimodal intrinsic capacity assessment system functionality]
Who's done what beforehand?
[Placeholder: Literature review and prior work in aging biomarkers and intrinsic capacity assessment]
What sources did you use?
[Placeholder: Research papers, open-source projects, and reference materials]
What did you design?
[Placeholder: Custom hardware, software, and integration systems designed]
What materials and components were used?
[Placeholder: Complete list of materials, sensors, microcontrollers, and components]
Where did they come from?
[Placeholder: Suppliers, vendors, and sourcing information]
How much did they cost?
[Placeholder: Detailed cost breakdown and budget analysis]
What parts and systems were made?
[Placeholder: Custom fabricated parts, 3D printed components, and assembled systems]
What tools and processes were used?
[Placeholder: Laser cutting, 3D printing, PCB fabrication, programming, and testing processes]
What questions were answered?
[Placeholder: Research questions addressed and hypotheses tested]
What worked? What didn't?
[Placeholder: Successes, challenges, and lessons learned]
How was it evaluated?
[Placeholder: Testing protocols, validation methods, and evaluation criteria]
What are the implications?
[Placeholder: Impact on aging research, clinical applications, and future development]
Design
Your project should incorporate 2D and 3D design, multiple additive and subtractive fabrication processes, electronics design and production, embedded microcontroller design, interfacing, and programming, system integration and packaging.
2D Design
2D design work for the multimodal intrinsic capacity assessment system:
- [Placeholder: Laser cutting designs for device housing components]
- [Placeholder: Vinyl cutting designs for labels and UI elements]
- [Placeholder: PCB layout designs and schematics]
- [Placeholder: 2D technical drawings and assembly guides]
- [Placeholder: User interface mockups and wireframes]
Tools Used: Inkscape, KiCad, Adobe Illustrator, Figma
3D Design
3D design work for device components and integration:
- [Placeholder: 3D printed device housings and enclosures]
- [Placeholder: Custom sensor mounting brackets and fixtures]
- [Placeholder: Ergonomic grip strength measurement device]
- [Placeholder: Camera mounting systems for facial recognition]
- [Placeholder: Integrated system assembly and packaging]
Tools Used: Fusion 360, FreeCAD, OpenSCAD, PrusaSlicer
Fabrication Processes Integration
Additive: 3D printing for custom components
Subtractive: Laser cutting, milling for precision parts
Electronics: PCB design and production
Programming: Embedded microcontroller development
Bill of Materials
Where possible, you should make rather than buy the parts of your project. Complete breakdown of materials, components, and sourcing information.
Bill of Materials
Complete list of materials and components:
Electronics Components
- [Placeholder: Microcontrollers and development boards]
- [Placeholder: Sensors (force, accelerometer, microphone)]
- [Placeholder: Camera modules and display components]
- [Placeholder: Power management and connectivity modules]
Mechanical Components
- [Placeholder: 3D printing materials (PLA, PETG)]
- [Placeholder: Laser cutting materials (acrylic, wood)]
- [Placeholder: Fasteners and mounting hardware]
- [Placeholder: Enclosure and housing materials]
Cost Breakdown
[Placeholder: Detailed cost analysis and budget tracking]
Make vs Buy
Strategic decisions on fabrication vs. purchasing:
✅ Made Components
- [Placeholder: Custom 3D printed housings]
- [Placeholder: Laser cut mounting brackets]
- [Placeholder: Custom PCB designs]
- [Placeholder: Integrated sensor assemblies]
🔸 Modified Components
- [Placeholder: Open-source grip strength meter adaptation]
- [Placeholder: Commercial sensor integration]
- [Placeholder: Existing microcontroller customization]
❌ Purchased Components
- [Placeholder: Standard electronic components]
- [Placeholder: Commercial sensors and modules]
- [Placeholder: Development boards and tools]
Fabrication Process
[Fabrication process documentation placeholder.]
Testing & Validation
[Testing and validation documentation placeholder.]
Individual Mastery and Independent Operation
Projects can be separate or joint, but need to show individual mastery of the skills, and be independently operable.
Individual Mastery
Demonstration of individual skills across all course units:
2D and 3D Design
- [Placeholder: Individual CAD modeling and design work]
- [Placeholder: Personal contribution to design decisions]
Fabrication Processes
- [Placeholder: Personal hands-on fabrication work]
- [Placeholder: Individual mastery of tools and processes]
Electronics and Programming
- [Placeholder: Individual PCB design and programming]
- [Placeholder: Personal debugging and troubleshooting]
Independent Operation
Project operates independently without external dependencies:
✅ Standalone Functionality
- [Placeholder: Complete system integration]
- [Placeholder: Self-contained operation]
- [Placeholder: Independent data collection and processing]
✅ User Independence
- [Placeholder: User-friendly interface]
- [Placeholder: Clear operation instructions]
- [Placeholder: Minimal external assistance required]
✅ Documentation
- [Placeholder: Complete technical documentation]
- [Placeholder: Assembly and operation guides]
- [Placeholder: Troubleshooting and maintenance]
Course Presentation
Present your final project, weekly and group assignments, and documentation.
Final Project Presentation
Complete presentation of the multimodal intrinsic capacity assessment system:
- [Placeholder: Final project demonstration]
- [Placeholder: Technical documentation presentation]
- [Placeholder: Results and evaluation discussion]
Weekly Assignments
Integration of weekly work into final project:
- [Placeholder: Week-by-week contribution summary]
- [Placeholder: Skills demonstration across all units]
- [Placeholder: Progressive development documentation]
Group Assignments
Collaborative work and individual contributions:
- [Placeholder: Group project contributions]
- [Placeholder: Individual role and responsibilities]
- [Placeholder: Collaborative learning outcomes]
Useful Documentation
Helpful resources, documentation, and design files for the multimodal intrinsic capacity assessment system.
Open Source Grip Strength Meter
A cost-effective $50 grip strength measurement system that can be further optimized for our multimodal assessment platform.
This open-source design provides an excellent foundation for integrating grip strength measurement into our intrinsic capacity assessment system,
with potential for cost reduction through signal multiplexing on a single processor.
Available Resources:
- Complete design files and schematics
- Arduino-based firmware and code repository
- 3D printing files for device housing
- Assembly instructions and documentation
- Calibration procedures and testing protocols
- Integration examples for data collection systems
Complete Intrinsic Capacity Coverage Analysis
Comprehensive analysis of how different digital biomarkers cover the five domains of intrinsic capacity (IC) as defined by WHO.
Legend:
✅ Strong coverage |
🔸 Partial/indirect coverage |
❌ Not covered
Multimodal Intrinsic Capacity Pipeline
Detailed technical pipeline for processing multiple digital biomarkers to generate intrinsic capacity scores.
Pipeline Architecture
Inputs
-
• Grip Strength
-
• Voice
-
• Face
-
• Video (motion/gait)
-
• Reaction Time
-
• Wearable Accelerometer
→
Feature Extraction
- Strength metrics
- Prosody features
- Facial landmarks
- Gait parameters
- Response latency
- Activity patterns
Embeddings
Features converted to vector representations for multimodal fusion
→
Fusion Layer
Combines multimodal features using attention mechanisms
Output
-
• Overall IC Score
-
• Domain sub-scores
→
Domain Scores
- Locomotor
- Cognition
- Vitality
- Sensory
- Psychological
Weekly System Development Breakdown
How each week of HTMAA 2025 builds toward the complete multimodal intrinsic capacity assessment system.
Week 0: Project Ideation
Initial concept development and planning
- Project planning and documentation structure
- Research direction and concept sketches
Week 1: Precision Cutting
Laser and vinyl cutting techniques
- Device housing components via laser cutting
- Sensor mounting brackets and enclosures
- Vinyl cutting for device labeling and UI elements
Week 2: Embedded Programming
Electronics basics and microcontroller programming
- Microcontroller programming for data collection
- Basic sensor interface circuits
Week 3: 3D Scanning & Printing
3D technologies for device components
- 3D scanning for custom component design
- 3D printing for device housings
Week 4: Electronics Design
EDA and schematic design
- PCB design for grip strength measurement
- Sensor interface circuits and signal conditioning
- Power management and data storage systems
Week 5: Electronics Production
PCB fabrication and assembly
- PCB fabrication and debugging
- Component assembly and testing
Week 6: Computer-controlled Machining
CAM and precision milling
- Precision components via milling
- Custom mechanical parts
Week 7: Input Devices
Sensor integration for data collection
- Force sensors for grip strength measurement
- Microphones for voice analysis
- Camera systems for facial expression analysis
- Reaction time measurement circuits
Week 8: Output Devices
Actuators and system integration
- Display systems for real-time feedback
- Haptic feedback for user interaction
Week 9: Molding & Casting
Forming and resin techniques
- 3D printing and molding for custom components
- Bioprinting molds and device components
Week 10: Mechanical & Machine Design
System integration and mechanical design
- Mechanical design for ergonomic device housing
- System integration and calibration protocols
Week 11: Networking & Communications
Connectivity and communication protocols
- Bluetooth/Wi-Fi connectivity for data transmission
- Wearable accelerometer integration and data fusion
Week 12: Interface & Application Programming
UI development and application programming
- Mobile app development for user interface
- Cloud integration for data storage and analysis
- Machine learning pipeline for IC score calculation
Week 13: Wildcard & Final Integration
Final orders and complete system deployment
- Final testing, validation, and documentation
- System integration and deployment
Camera Subsystem
Advanced camera system implementation using XIAO ESP32S3 Sense with real-time image processing, EdgeAI integration, and interactive selfie capture functionality.
System Overview
The camera system successfully captures images, processes them into bitmaps, and displays them on an OLED screen using advanced Floyd-Steinberg dithering algorithms.
Video Demonstrations
Camera Bot Selfie
Demonstration of the interactive selfie capture system with touch controls
Picture of Picture
Meta demonstration showing the camera system capturing its own display
Code Implementation
60-Second Auto Capture System
Automated camera system that captures and displays images every 60 seconds using advanced image processing techniques.
Pseudocode Implementation:
1. Initialize camera with PSRAM frame buffers
2. Configure OLED display (128x64 pixels)
3. Set up 60-second capture interval timer
4. In main loop:
a. Check if 60 seconds have elapsed
b. Capture image from camera
c. Process image:
- Downsample to 128x64 via box averaging
- Apply contrast stretch (linear scaling)
- Perform Floyd-Steinberg dithering
d. Display processed bitmap on OLED
e. Release frame buffer
5. Repeat process
Touch-Controlled Capture System
Interactive camera system with touch controls allowing manual capture triggers in addition to automatic timing.
Pseudocode Implementation:
1. Initialize camera and OLED display
2. Set up touch pins (GPIO1 & GPIO2) with threshold detection
3. Configure 60-second auto-capture timer
4. In main loop:
a. Update touch sensor readings
b. Detect touch press events (justPressed)
c. Check for capture trigger:
- Touch press OR 60-second timer elapsed
d. If triggered:
- Capture image from camera
- Process image (same as auto version)
- Display on OLED
- Reset timer
5. Continue monitoring for next trigger
How It Was Done
The camera system implementation began with code from Charles Lu's electronics production weekly assignment,
which was based on the official XIAO tutorial.
Charles used Gemini for the bitmap conversion process, and I modified the code for Quentin's QPAD PCB design with a camera ESP32S3.
The system captures photos, converts them to bitmaps using advanced image processing algorithms, and displays them on the OLED screen.
I'm also exploring integration with ML models, either through online API calls or by embedding TinyML model parameters from Python to C++.
Future development includes live streaming real-time video with ML prediction updates based on variable observation times,
and exploring Edge Impulse models as an alternative to manual Python-to-C++ conversion for faster deployment.
EdgeAI/TinyML Integration
Edge AI can also be implemented using Edge Impulse models, which may be faster than manually converting Python models to C++.
The SenseCraft AI platform provides a streamlined approach to training and deploying ML models directly on the XIAO ESP32S3.
Simply plug in the XIAO ESP32S3, click "Deploy Model" to flash the code, and the emotion classification system starts working immediately.
Development Discussion: ChatGPT Session on Camera System Development
Week 0 - Introduction & Design
Project ideation and initial concept development for bioprinting rejuvenated tissue and aging biomarker devices.
Project planning
Concept sketches
Research direction
System Integration Plans: Establish the foundational architecture for multimodal data collection by designing the overall system framework that will integrate all six digital biomarkers (grip strength, voice, face, video, reaction time, wearable accelerometer) into a cohesive intrinsic capacity assessment platform.
[Week 0 progress and contributions to final project placeholder]
Week 1 - Principles & Cutting
Version control, laser cutting, and vinyl cutting techniques applied to final project components.
Laser cutting
Vinyl cutting
Version control
System Integration Plans: Fabricate precision-cut housing components and mounting brackets for all sensor modules (force sensors, microphones, cameras, reaction time circuits) using laser cutting, while creating vinyl-cut labels and UI elements for device identification and user guidance.
[Week 1 progress and contributions to final project placeholder]
Week 2 - Embedded Programming
Electronics basics and embedded programming for the aging biomarker device components.
Microcontrollers
Programming
Electronics
System Integration Plans: Develop embedded programming protocols for real-time data collection from all six biomarker sensors, implementing initial signal processing algorithms and establishing the communication framework for multimodal data fusion.
[Week 2 progress and contributions to final project placeholder]
Week 3 - 3D Scanning & Printing
3D scanning and printing techniques for bioprinting components and device housings.
3D scanning
3D printing
AI tools
System Integration Plans: Create custom 3D-printed components for camera mounting systems and facial recognition hardware, while developing 3D scanning protocols for ergonomic device design that accommodates all sensor modalities in a user-friendly form factor.
[Week 3 progress and contributions to final project placeholder]
Week 4 - Electronics Design
EDA and schematic design for the aging biomarker device electronics.
EDA tools
Schematic design
Circuit design
System Integration Plans: Design comprehensive PCB schematics that integrate force sensor circuits for grip strength measurement, microphone preamplifiers for voice analysis, camera interfaces for facial recognition, and timing circuits for reaction time assessment into a unified electronics platform.
[Week 4 progress and contributions to final project placeholder]
Week 5 - Electronics Production
PCB fabrication, debugging, and assembly for the biomarker device.
PCB fabrication
Debugging
Assembly
System Integration Plans: Fabricate and assemble the integrated PCB containing all sensor interfaces, implementing power management systems for continuous operation and establishing data storage protocols for the multimodal biomarker data collection system.
[Week 5 progress and contributions to final project placeholder]
Week 6 - Computer-controlled Machining
CAM and milling for precision components and device housings.
CAM
Milling
Precision machining
System Integration Plans: Machine precision mechanical components for the integrated device housing using computer-controlled milling, ensuring proper alignment and mounting for all sensor modules while maintaining ergonomic design for user comfort during multimodal data collection.
[Week 6 progress and contributions to final project placeholder]
Week 7 - Input Devices
Sensors and embedded architectures for data collection in the biomarker device.
Sensors
Input devices
Data collection
System Integration Plans: Integrate all six input sensor systems (force sensors for grip strength, microphones for voice analysis, cameras for facial recognition and gait analysis, reaction time circuits, and wearable accelerometer) into the unified data collection platform with real-time processing capabilities.
[Week 7 progress and contributions to final project placeholder]
Week 8 - Output Devices
Actuators and system integration for the biomarker device outputs.
Actuators
Output devices
System integration
System Integration Plans: Implement output devices including display systems for real-time intrinsic capacity feedback and haptic feedback mechanisms for user interaction, creating an intuitive interface for the multimodal biomarker assessment system.
[Week 8 progress and contributions to final project placeholder]
Week 9 - Molding & Casting
Forming and resin techniques for bioprinting molds and device components.
Molding
Casting
Resins
System Integration Plans: Create custom molded components for the bioprinting aspects of the project and develop specialized casings for sensor protection, ensuring the device can withstand continuous use during multimodal data collection sessions.
[Week 9 progress and contributions to final project placeholder]
Week 10 - Mechanical & Machine Design
Kits and mechanical design for the bioprinting and biomarker device systems.
Mechanical design
Machine design
System integration
System Integration Plans: Complete the mechanical design integration of all system components, implementing calibration protocols for sensor alignment and developing the complete mechanical framework that houses all six digital biomarker measurement systems.
[Week 10 progress and contributions to final project placeholder]
Week 11 - Networking & Communications
BLE, Wi-Fi, and communication protocols for the biomarker device connectivity.
BLE
Wi-Fi
Communications
System Integration Plans: Implement wireless communication protocols (Bluetooth/Wi-Fi) for seamless data transmission from all six sensor modalities, enabling real-time data fusion and establishing connectivity for the wearable accelerometer integration into the multimodal assessment system.
[Week 11 progress and contributions to final project placeholder]
Week 12 - Interface & Application Programming
UI and application development for the biomarker device interface.
UI design
Applications
User interface
System Integration Plans: Develop the complete user interface and application programming for the multimodal system, implementing the machine learning pipeline for intrinsic capacity score calculation and creating cloud integration for comprehensive data storage and analysis of all biomarker measurements.
[Week 12 progress and contributions to final project placeholder]
Week 13 - Wildcard & Final Orders
Final orders and wildcard week activities for project completion.
Final orders
Wildcard activities
Project completion
System Integration Plans: Complete final system integration, testing, and validation of the complete multimodal intrinsic capacity assessment platform, ensuring all six digital biomarkers work cohesively to provide accurate WHO-defined intrinsic capacity scores across all five domains (locomotor, cognition, vitality, sensory, psychological).
[Week 13 progress and contributions to final project placeholder]
Design Files
[Links to CAD/SVG/assets placeholder.]
Reflections & Learnings
[Reflection notes placeholder.]
Contributions
Acknowledgements and contributions that made this project possible.
Gladyshev Lab and Collaborators
Special thanks to the Gladyshev Lab and collaborators for the fruitful discussions that led to this multimodal intrinsic capacity assessment idea,
which supplements my PhD research goals in aging and longevity. The conceptual framework for integrating multiple digital biomarkers
to assess intrinsic capacity domains emerged from collaborative research discussions on aging biomarkers and healthspan assessment.
Ethical AI Use
Transparent documentation of AI assistance used in this final project work, following course guidelines for ethical AI usage.
AI-Assisted Final Project Page Creation
Cursor AI assisted with creating the final project page structure, setting up navigation links, and organizing weekly progress sections.
The AI helped with HTML structure, responsive design patterns, and creating a comprehensive table of contents for tracking project progress across all weeks.
AI-Assisted Intrinsic Capacity Research & Design
ChatGPT was used to research and develop the multimodal intrinsic capacity assessment framework, including the comprehensive coverage analysis table and technical pipeline design.
The AI assisted with structuring the WHO-defined intrinsic capacity domains, identifying appropriate digital biomarkers, and designing the fusion architecture for multimodal data processing.
AI-Assisted Final Project Development
Cursor AI assisted with developing the complete final project page structure, implementing the multimodal intrinsic capacity assessment framework, and creating comprehensive documentation.
The AI helped with HTML structure, responsive design, weekly system integration plans, and organizing the technical documentation for the complete biomarker assessment system.
AI-Assisted Final Project Presentation Structure
Cursor AI assisted with finalizing the project presentation structure to ensure full compliance with MIT Academy project presentation requirements.
The AI helped implement all required sections including answering questions, design documentation, bill of materials, individual mastery requirements,
course presentation structure, and spiral model development approach visualization.
AI-Assisted Camera System Development
ChatGPT was used to discuss camera system implementation strategies, image processing algorithms, and EdgeAI integration approaches.
The AI assisted with understanding Floyd-Steinberg dithering implementation, touch sensor integration, and exploring TinyML deployment options for the XIAO ESP32S3 platform.
This work is licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
Perfect! I've made all three images in the project highlights section clickable links that navigate to the camera subsystem section. Here's what I added:
Changes Made:
1. Wrapped each image in a link () that points to the camera subsystem section
2. Added hover effects with smooth transitions:
- Images scale up slightly (1.02x) on hover
- Box shadow becomes more prominent on hover
- Smooth 0.2s transition for both effects
3. Added cursor pointer to indicate the images are clickable
4. Maintained all existing styling while adding the interactive functionality
Features Added:
Now when users click on any of the three images in the project highlights section (Camera Works!, EdgeAI Works!, or Selfie Capture!), they will be smoothly scrolled to the detailed camera subsystem section below. The hover effects make it clear that the images are interactive elements.
Download Options
For the complete technical details and full conversation transcript: