We present WiBend, a system that recognizes bending gestures as the input modalities for interacting on non-instrumented and deformable surfaces using WiFi signals. WiBend takes advantage of off-the-shelf 802.11 (Wi-Fi) devices and Channel State Information (CSI) measurements of packet transmissions when the user is placed and interacting between a Wi-Fi transmitter and a receiver. We have performed extensive user experiments in an instrumented laboratory to obtain data for training the HMM models and for evaluating the precision of WiBend. During the experiments, participants performed 12 distinct bending gestures with three surface sizes, two bending speeds and two different directions. The performance evaluation results show that WiBend can distinguish between 12 bending gestures with a precision of 84% on average.
Mira Sarkis, Céline Coutrix, Laurence Nigay, and Andrzej Duda. 2019. WiBend: Wi-Fi for Sensing Passive Deformable Surfaces. In 2019 International Conference on Multimodal Interaction (ICMI ’19), Wen Gao, Helen Mei Ling Meng, Matthew Turk, Susan R. Fussell, Björn Schuller, Yale Song, and Kai Yu (Eds.). ACM, New York, NY, USA, 339-348. DOI: https://doi.org/10.1145/3340555.3353746