Daniel Geißler, Hymalai Bello, Esther Zahn, Emil Woop, Bo Zhou, Paul Lukowicz, and Jakob Karolus. 2024. Head 'n Shoulder: Gesture-Driven Biking Through Capacitive Sensing Garments to Innovate Hands-Free Interaction. Proc. ACM Hum.-Comput. Interact. 8, MHCI, Article 265 (September 2024), 20 pages. https://doi.org/10.1145/3676510

Distractions caused by digital devices are increasingly causing dangerous situations on the road, particularly for more vulnerable road users like cyclists. While researchers have been exploring ways to enable richer interaction scenarios on the bike, safety concerns are frequently neglected and compromised. In this work, we propose Head 'n Shoulder, a gesture-driven approach to bike interaction without affecting bike control, based on a wearable garment that allows hands- and eyes-free interaction with digital devices through integrated capacitive sensors. It achieves an average accuracy of 97% in the final iteration, evaluated on 14 participants. Head 'n Shoulder does not rely on direct pressure sensing, allowing users to wear their everyday garments on top or underneath, not affecting recognition accuracy. Our work introduces a promising research direction: easily deployable smart garments with a minimal set of gestures suited for most bike interaction scenarios, sustaining the rider's comfort and safety.

https://dl.acm.org/doi/10.1145/3676510