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Capacitive Sensing Based On-board Hand Gesture Recognition with TinyML

Sizhen Bian; Paul Lukowicz
In: ACM. ACM International Symposium on Wearable Computers (ISWC-2021), UbiComp-ISWC '21 Adjunct: Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers, located at UbiComp-ISWC '21, September 21-26, ACM, 2021.


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%.