µTouch: Enabling Accurate, Lightweight Self-Touch Sensing with Passive Magnets
Published in The Proceedings of the International Conference on Pervasive Computing and Communications (PerCom), 2026
Recommended citation: Siyuan Wang, Ke Li, Jingyuan Huang, Jike Wang, Cheng Zhang, Alanson P. Sample, and Dongyao Chen. 2026. µTouch: Enabling Accurate, Lightweight Self-Touch Sensing with Passive Magnets. The Proceedings of the International Conference on Pervasive Computing and Communications (PerCom). https://arxiv.org/abs/2601.22864
March 16-20, 2026, Pisa, Italy
Keyword: HCI, Healthcare, Pervasive Sensing, Magnetic Sensing, Wearable Computing
Self-touch gestures (e.g., nuanced facial touches and subtle finger scratches) provide rich insights into human behaviors, from hygiene practices to health monitoring. However, existing approaches fall short in detecting such micro gestures due to their diverse movement patterns.
This paper presents µTouch, a novel magnetic sensing platform for self-touch gesture recognition. µTouch features (1) a compact hardware design with low-power magnetometers and magnetic silicon, (2) a lightweight semi-supervised framework requiring minimal user data, and (3) an ambient field detection module to mitigate environmental interference. We evaluated µTouch in two representative applications in user studies with 11 and 12 participants. µTouch only requires three-second finetuning data for each gesture — new users need less than one minute before starting to use the system. µTouch can distinguish eight different face-touching behaviors with an average accuracy of 93.41%, and reliably detect body-scratch behaviors with an average accuracy of 94.63%. µTouch demonstrates accurate and robust sensing performance even after a month, showcasing its potential as a practical tool for hygiene monitoring and dermatological health applications. Code is available at https://wangmerlyn.github.io/muTouch.