Electric muscle stimulation (EMS) can enable mobile force feedback, support pedestrian navigation, or confer object affordances. To date, however, EMS is limited by two interlinked problems. (1) EMS is low resolution -- achieving only coarse movements and constraining opportunities for exploration. (2) EMS requires time consuming, expert calibration -- confining these interaction techniques to the lab. EMS arrays have been shown to increase stimulation resolution, but as calibration complexity increases exponentially as more electrodes are used, we require heuristics or automated procedures for successful calibration. We explore the feasibility of using electromyography (EMG) to auto-calibrate high density EMS arrays. We determine regions of muscle activity during human-performed gestures, to inform stimulation patterns for EMS-performed gestures. We report on a study which shows that auto-calibration of a 60-electrode array is feasible: achieving 52% accuracy across six gestures, with 82% accuracy across our best three gestures. By highlighting the electrode-array calibration problem, and presenting a first exploration of a potential solution, this work lays the foundations for high resolution, wearable and, perhaps one day, ubiquitous EMS beyond the lab.
|Journal||Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies|
|Publication status||Published - 2017|