dc.contributor.author | Kyu, Alexander | |
dc.contributor.author | Mao, Hongyu | |
dc.contributor.author | Zhu, Junyi | |
dc.contributor.author | Goel, Mayank | |
dc.contributor.author | Ahuja, Karan | |
dc.date.accessioned | 2024-06-04T19:32:07Z | |
dc.date.available | 2024-06-04T19:32:07Z | |
dc.date.issued | 2024-05-11 | |
dc.identifier.isbn | 979-8-4007-0330-0 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/155185 | |
dc.description | CHI '24: Proceedings of the CHI Conference on Human Factors in Computing Systems May 11–16, 2024, Honolulu, HI, USA | en_US |
dc.description.abstract | 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. | en_US |
dc.publisher | ACM | en_US |
dc.relation.isversionof | 10.1145/3613904.3642663 | en_US |
dc.rights | Creative Commons Attribution | en_US |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
dc.source | Association for Computing Machinery | en_US |
dc.title | EITPose: Wearable and Practical Electrical Impedance Tomography for Continuous Hand Pose Estimation | en_US |
dc.type | Article | en_US |
dc.identifier.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." | |
dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | |
dc.identifier.mitlicense | PUBLISHER_CC | |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
dc.date.updated | 2024-06-01T07:52:36Z | |
dc.language.rfc3066 | en | |
dc.rights.holder | The author(s) | |
dspace.date.submission | 2024-06-01T07:52:36Z | |
mit.license | PUBLISHER_CC | |
mit.metadata.status | Authority Work and Publication Information Needed | en_US |