Fabric Sensing of Intrinsic Hand Muscle Activity
Abstract
Wearable robotics have the capacity to assist stroke survivors in assisting and rehabilitating hand function. Many devices that use surface electromyographic (sEMG) for control rely on extrinsic muscle signals, since sEMG sensors are relatively easy to place on the forearm without interfering with hand activity. In this work, we target the intrinsic muscles of the thumb, which are superficial to the skin and thus potentially more accessible via sEMG sensing. However, traditional, rigid electrodes can not be placed on the hand without adding bulk and affecting hand functionality. We thus present a novel sensing sleeve that uses textile electrodes to measure sEMG activity of intrinsic thumb muscles. We evaluate the sleeve's performance on detecting thumb movements and muscle activity during both isolated and isometric muscle contractions of the thumb and fingers. This work highlights the potential of textile-based sensors as a low-cost, lightweight, and non-obtrusive alternative to conventional sEMG sensors for wearable robotics.
Keywords
Cite
@article{arxiv.2412.14185,
title = {Fabric Sensing of Intrinsic Hand Muscle Activity},
author = {Katelyn Lee and Runsheng Wang and Ava Chen and Lauren Winterbottom and Ho Man Colman Leung and Lisa Maria DiSalvo and Iris Xu and Jingxi Xu and Dawn M. Nilsen and Joel Stein and Xia Zhou and Matei Ciocarlie},
journal= {arXiv preprint arXiv:2412.14185},
year = {2025}
}
Comments
6 pages, 4 figures, ICORR 2025 submission