We introduce Serpentine, a self-powered sensor that is a reversibly deformable cord capable of sensing a variety of human input. The material properties and structural design of Serpentine allow it to be flexible, twistable, stretchable and squeezable, enabling a broad variety of expressive input modalities. The sensor operates using the principle of Triboelectric Nanogenerators (TENG), which allows it to sense mechanical deformation without an external power source. The affordances of the cord include six interactions—Pluck, Twirl, Stretch, Pinch, Wiggle and Twist. Serpentine demonstrates the ability to simultaneously recognize these inputs through a single physical interface. A 12-participant user study illustrates 95.7% accuracy for a user-dependent recognition model using a realtime system and 92.17% for user-independent offline detection. We conclude by demonstrating how Serpentine can be employed in everyday ubiquitous computing applications.
Fereshteh Shahmiri, Chaoyu Chen, Anandghan Waghmare, Dingtian Zhang, Shivan Mittal, Steven L. Zhang, Yi-Cheng Wang, Zhong Lin Wang, Thad E. Starner, and Gregory D. Abowd. 2019. Serpentine: A Self-Powered Reversibly Deformable Cord Sensor for Human Input. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI ’19). ACM, New York, NY, USA, Paper 545, 14 pages. DOI: https://doi.org/10.1145/3290605.3300775