EITPose: Wearable and Practical Electrical Impedance Tomography for Continuous Hand Pose Estimation
Author(s)
Kyu, Alexander; Mao, Hongyu; Zhu, Junyi; Goel, Mayank; Ahuja, Karan
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Real-time hand pose estimation has a wide range of applications spanning gaming, robotics, and human-computer interaction. In this paper, we introduce EITPose, a wrist-worn, continuous 3D hand pose estimation approach that uses eight electrodes positioned around the forearm to model its interior impedance distribution during pose articulation. Unlike wrist-worn systems relying on cameras, EITPose has a slim profile (12 mm thick sensing strap) and is power-efficient (consuming only 0.3 W of power), making it an excellent candidate for integration into consumer electronic devices. In a user study involving 22 participants, EITPose achieves with a within-session mean per joint positional error of 11.06 mm. Its camera-free design prioritizes user privacy, yet it maintains cross-session and cross-user accuracy levels comparable to camera-based wrist-worn systems, thus making EITPose a promising technology for practical hand pose estimation.
Description
CHI '24: Proceedings of the CHI Conference on Human Factors in Computing Systems May 11–16, 2024, Honolulu, HI, USA
Date issued
2024-05-11Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence LaboratoryPublisher
ACM
Citation
Kyu, Alexander, Mao, Hongyu, Zhu, Junyi, Goel, Mayank and Ahuja, Karan. 2024. "EITPose: Wearable and Practical Electrical Impedance Tomography for Continuous Hand Pose Estimation."
Version: Final published version
ISBN
979-8-4007-0330-0
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