Imperial College London
Alternate

ProfessorRaviVaidyanathan

Faculty of Engineering, Department of Mechanical Engineering

Professor in Biomechatronics
 
 
 
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Contact

 

+44 (0)20 7594 7020r.vaidyanathan CV

 
 
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Location

 

717City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Woodward:2019:10.1038/s41598-019-41860-4,
author = {Woodward, R and Stokes, M and Shefelbine, S and Vaidyanathan, R},
doi = {10.1038/s41598-019-41860-4},
journal = {Scientific Reports},
title = {Segmenting mechanomyography measures of muscle activity phases using inertial data},
url = {http://dx.doi.org/10.1038/s41598-019-41860-4},
volume = {9},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Electromyography (EMG) is the standard technology for monitoring muscle activity in laboratory environments, either using surface electrodes or fine wire electrodes inserted into the muscle. Due to limitations such as cost, complexity, and technical factors, including skin impedance with surface EMG and the invasive nature of fine wire electrodes, EMG is impractical for use outside of a laboratory environment. Mechanomyography (MMG) is an alternative to EMG, which shows promise in pervasive applications. The present study used an exerting squat-based task to induce muscle fatigue. MMG and EMG amplitude and frequency were compared before, during, and after the squatting task. Combining MMG with inertial measurement unit (IMU) data enabled segmentation of muscle activity at specific points: entering, holding, and exiting the squat. Results show MMG measures of muscle activity were similar to EMG in timing, duration, and magnitude during the fatigue task. The size, cost, unobtrusive nature, and usability of the MMG/IMU technology used, paired with the similar results compared to EMG, suggest that such a system could be suitable in uncontrolled natural environments such as within the home.
AU  - Woodward,R
AU  - Stokes,M
AU  - Shefelbine,S
AU  - Vaidyanathan,R
DO  - 10.1038/s41598-019-41860-4
PY  - 2019///
SN  - 2045-2322
TI  - Segmenting mechanomyography measures of muscle activity phases using inertial data
T2  - Scientific Reports
UR  - http://dx.doi.org/10.1038/s41598-019-41860-4
UR  - http://hdl.handle.net/10044/1/69597
VL  - 9
ER  -
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