EITPose: Wearable and Practical Electrical Impedance Tomography for Continuous Hand Pose Estimation

要旨

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.

著者
Alexander Kyu
Human Computer Interaction Institute, Pittsburgh, Pennsylvania, United States
Hongyu Mao
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Junyi Zhu
MIT CSAIL, Cambridge, Massachusetts, United States
Mayank Goel
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Karan Ahuja
Northwestern University, Evanston, Illinois, United States
論文URL

doi.org/10.1145/3613904.3642663

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Hand Interaction

313B
5 件の発表
2024-05-15 18:00:00
2024-05-15 19:20:00