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Title: Towards wearable comprehensive capture and analysis of skeletal muscle activity during human locomotion
Authors: Ma, CZH 
Ling, YT 
Shea, QTK 
Wang, LK 
Wang, XY
Zheng, YP 
Keywords: Electromyography (EMG)
Joint angle
Mechanomyography (MMG)
Motion capture and analysis
Plantar force
Sonomyograph (SMG)
Ultrasound imaging
Issue Date: 2019
Publisher: Molecular Diversity Preservation International (MDPI)
Source: Sensors (Switzerland), 2019, v. 19, no. 1, 195 How to cite?
Journal: Sensors (Switzerland) 
Abstract: Background: Motion capture and analyzing systems are essential for understanding locomotion. However, the existing devices are too cumbersome and can be used indoors only. A newly-developed wearable motion capture and measurement system with multiple sensors and ultrasound imaging was introduced in this study.
Methods: In ten healthy participants, the changes in muscle area and activity of gastrocnemius, plantarflexion and dorsiflexion of right leg during walking were evaluated by the developed system and the Vicon system. The existence of significant changes in a gait cycle, comparison of the ankle kinetic data captured by the developed system and the Vicon system, and test-retest reliability (evaluated by the intraclass correlation coefficient, ICC) in each channel’s data captured by the developed system were examined.
Results: Moderate to good test-retest reliability of various channels of the developed system (0.512 ≤ ICC ≤ 0.988, p < 0.05), significantly high correlation between the developed system and Vicon system in ankle joint angles (0.638R ≤ 0.707, p < 0.05), and significant changes in muscle activity of gastrocnemius during a gait cycle (p < 0.05) were found.
Conclusion: A newly developed wearable motion capture and measurement system with ultrasound imaging that can accurately capture the motion of one leg was evaluated in this study, which paves the way towards real-time comprehensive evaluation of muscles and joint motions during different activities in both indoor and outdoor environments.
ISSN: 1424-8220
DOI: 10.3390/s19010195
Rights: © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
The following publication Ma C -H, Ling YT, Shea QTK, Wang L-K, Wang X-Y, Zheng Y-P. Towards Wearable Comprehensive Capture and Analysis of Skeletal Muscle Activity during Human Locomotion. Sensors. 2019; 19(1):195 is available at
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