Yang Zhang

Tomo: Wearable, Low-cost, Electrical Impedance Tomography for Hand Gesture Recognition

Yang Zhang, Chris Harrison (UIST 2015)

We present Tomo, a wearable, low-cost system using Electrical Impedance Tomography (EIT) to recover the interior impedance geometry of a user's arm. This is achieved by measuring the cross-sectional impedances between all pairs of eight electrodes resting on a user's skin. Our approach is sufficiently compact and low-powered that we integrated the technology into a prototype wrist- and armband, which can monitor and classify gestures in real-time. We conducted a user study that evaluated two gesture sets, one focused on gross hand gestures and another using thumb-to-finger pinches. Our wrist location achieved 97% and 87% accuracies on these gesture sets respectively, while our arm location achieved 93% and 81%. We ultimately envision this technique being integrated into future smartwatches, allowing hand gestures and direct touch manipulation to work synergistically to support interactive tasks on small screens.




Zhang, Y. and Harrison, C. 2015. Tomo: Wearable, Low-Cost, Electrical Impedance Tomography for Hand Gesture Recognition. In Proceedings of the 28th Annual ACM Symposium on User interface Software and Technology (Charlotte, North Carolina, November 8 - 11, 2015). UIST '15. ACM, New York, NY. 167-173.

Videotape of the Presentation