Skinergy: Machine-Embroidered Silicone-Textile Composites as On-Skin Self-Powered Input Sensors

要旨

We propose Skinergy for self-powered on-skin input sensing, a step towards prolonged on-skin device usage. 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 an 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.

著者
Tianhong Catherine. Yu
Cornell University, Ithaca, New York, United States
Nancy Wang
Cornell University, Ithaca, New York, United States
Sarah Ellenbogen
Cornell University, Ithaca, New York, United States
Cindy Hsin-Liu Kao
Cornell University, Ithaca, New York, United States
論文URL

https://doi.org/10.1145/3586183.3606729

動画

会議: UIST 2023

ACM Symposium on User Interface Software and Technology

セッション: Green Machine: Sustainability in Hardware and Fabrication

Venetian Room
6 件の発表
2023-10-31 01:10:00
2023-10-31 02:30:00