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.

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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.

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