Danny Griffin HTMAA 2023

Week 08 :: Input Devices

How can we gather information about gestures?

1. Measure Something

In my original sketch for the final project, I thought it might be useful to incorporate biometric feedback into the design of a haptic glove. Niklas Hagemann had two suggestions for how I might do this: measure a flex sensor, and measure gyroscope readings.

1.1. Measuring input from a flex sensor.

Reading the serial plotter, we can register the flexure within a range of resistance values.

The analog signal is remapped to a range of 0-255 to control LED brightness.

Thinking about incorporation into wearable design. These types of sensors are frequently used in the creation of robotic hands, where each finger is equipped with a flex sensor.

To get the flex sensor working, I simply referred to code and wiring diagram available in the following tutorial. I wasn't intending to control lights with the flex sensor, but this example makes it extremely intuitive. Now that I know I can connect a gesture to an output device, I'm wondering if I might be able to set up gesture control to activate motion tracking in my final project.

1.2. BNO08x, 9 Degree-of-Freedom Orientation IMU

Inertial Measurement Unit (IMU) is an electronic device that measures and reports a body's specific force, angular rate, and sometimes orientation.

I thought it would be straightforward to incorporate the BNO08x accelerometer, since the pinout was similar to the OLED I had used in previous weeks.

Excerpt from documentation on Adafruit's BNO08x page.

Reading the documentation, I learned that the ESP-32C3 I intended to use might not be compatible with the accelerometer. Instead, I'll be trying to use XIAO RP2040 to connect to the IMU.

I milled a basic board to connect an IMU and OLED on the same serial communication bus, based on Michael Schnebly's.

The green light of the IMU was promising, but I wouldn't realize until much later that I was getting poor electrical connections which would prevent proper communication with the device.

At this point I was wondering if I should be using SPI instead of I2C, and I tried to diagram a schematic for how that wiring would work.

I tried connecting to the IMU this way on a breadoard, only to have the same issues as with my milled board.

After consulting with Michael Schnebly, I realized that I was running the right example scripts, using appropriate power supply, and wiring my SDA/SCL lines correctly. The green light verified that my IMU was functional - meaning that the only thing left was to improve my soldering to get better connections.

Success! After remaking my board with cleaner traces and improving my soldering skills, I was finally able to run the rotation vector example script from Adafruit.

2. Probe an Input Device's analog levels and digital signals

Working with Niklas Hagemann, we attemped to use the oscilloscope to visualize both analog and digital communication.

For digital communication, we probed an ESP-32CAM, which uses UART, universal asynchronous receiver / transmtter. Measuring the UOT pin from the oscilloscope, we see a constant signal.

For analog communication, we measured the signal from a capacitive sensor.

Connecting to the UOT pin on the ESP-32CAM.

Hitting the reset button on the camera, we can see the process of communication being disrupted and then reestablished.

Wiring setup of the capacitive sensor.

The signal displayed on the oscilloscope corresponds to the compression of the capacitive accordion.