Capacitive Sensing Based On-board Hand Gesture Recognition with TinyML

Although hand gesture recognition has been widely explored with sensing modalities like IMU, electromyography and camera, it is still a challenge of those modalities to provide a compact, power-efficient on-board inferencing solution. In this work, we present a capacitive-sensing wristband surrounded by four single-end electrodes for on-board hand gesture recognition. By deploying a single convolutional hidden layer as the classifier at the sensing edge, the wristband can recognize seven hand gestures from a single user with an accuracy of 96.4%.