My goal is to design a wristband which tracks the wearer’s hand activities and alerts them of activities that are potentially harmful to their health. Specifically, I am considering two types of activities. Firstly, I want to detect unconscious self-manipulator gestures such as scratching and alert the user when they occur – this could be user to prevent people from scratching at injuries, rashes, etc. (Basically, I want to build a human version of the flea collar.) As a secondary (or alternative) feature, I want to track repetitive movements such as typing and mouse usage and notify the wearer to take periodic breaks.

I intend to work alone on the project. I feel confident that I can quickly prototype a wristband with a microcontroller and IMU that can track 6DOF hand movements and classify them using simple heuristics. However, I expect I will need to utilize a trained model to perform robust, reliable classification, which may prove challenging due to hardware limitations and the need to collect and annotate high-quality training data. Moreover, reliable detection of self-manipulator gestures is likely to be impossible using just 6DOF tracking data and may require integration of additional sensors into the design.