Yu, Tianhong Catherine, Nancy Wang, Sarah Ellenbogen, and Cindy Hsin-Liu Kao. "Skinergy: Machine-Embroidered Silicone-Textile Composites as On-Skin Self-Powered Input Sensors." In Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology, pp. 1-15. 2023.
We propose Skinergy for self-powered on-skin input sensing, a step towards prolonged on-skin device usages. In contrast to prior on-skin gesture interaction sensors, Skinergy’s sensor operation does not require external power. Enabled by the triboelectric nanogenerator (TENG) phenomenon, the machine-embroidered silicone-textile composite sensor converts mechanical energy from the input interaction into electrical energy. Our proof-of-concept untethered sensing system measures the voltages of generated electrical signals which are then processed for a diverse set of sensing tasks: discrete touch detection, multi-contact detection, contact localization, and gesture recognition. Skinergy is fabricated with off-the-shelf materials. The aesthetic and functional designs can be easily customized and digitally fabricated. We characterize Skinergy and conduct a 10-participant user study to (1) evaluate its gesture recognition performance and (2) probe user perceptions and potential applications. Skinergy achieves 92.8% accuracy for a 11-class gesture recognition task. Our findings reveal that human factors (e.g., individual differences in skin properties, and aesthetic preferences) are key considerations in designing self-powered on-skin sensors for human inputs.