Bioimpedance meets biomechanics: Wearable electrical impedance myography encodes fascicle and activation dynamics.

Authors

Christopher J Nichols, Nicholas Harris, H Trask Crane, Autumn Routt, Milki D Haile, Quentin Goossens, Minoru Shinohara, Gregory S Sawicki, Kristen L Jakubowski, Omer T Inan

Published in

Science robotics. Volume 11. Issue 118. Pages eaea4580. Sep 23, 2026. Epub Sep 23, 2026.

Abstract

Modern assistive robotic control demands parallel advancements in wearable, noninvasive sensing. Electrical impedance myography (EIM)-a noninvasive, wearable technology for dynamically measuring tissue electrical impedance properties-is a promising but poorly established solution for quantifying muscle force and fatigue, given that prior approaches have relied on black-box algorithms when attempting to relate EIM to muscle physiology or have extrapolated relationships between EIM and muscle force from singular, isolated movements. Here, we elucidate direct relationships between EIM and muscle kinematics and kinetics during functional movement using biomechanical principles and traditional measures of joint torque, muscle architecture, and activation. Dual-frequency EIM measurements of the medial gastrocnemius of 10 participants were collected and compared against dynamometer, B-mode ultrasound, and electromyography measurements. Participants performed multiple categories of dynamic movements spanning constrained isometric, self-selected isometric, concentric, and eccentric contractions at multiple force levels, joint angles, and angular velocities. EIM correlated to joint torque only for specific conditions, whereas EIM correlated with muscle length change dynamics across all movements. Mixed-effects modeling and sequential feature analysis showed fascicle length and muscle activation as primary drivers of EIM variance. Last, dual-frequency EIM combined with principal components analysis reliably captured changes in fascicle length and activation during walking. These findings validate EIM as a robust, real-time biomechanical tool for sensing muscle kinematics and neuromuscular activity during functional movement, expanding its use in assistive robotic control and injury prevention.

PMID:
42777071
Bibliographic data and abstract were imported from PubMed on 24 Sep 2026.

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