Abstract

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.

Details

Title
Segmenting Mechanomyography Measures of Muscle Activity Phases Using Inertial Data
Author
Woodward, Richard B 1   VIAFID ORCID Logo  ; Stokes, Maria J 2 ; Shefelbine, Sandra J 3 ; Vaidyanathan, Ravi 1 

 Imperial College London, Department of Mechanical Engineering, London, UK (GRID:grid.7445.2) (ISNI:0000 0001 2113 8111) 
 University of Southampton, Faculty of Health Science, Southampton, UK (GRID:grid.5491.9) (ISNI:0000 0004 1936 9297) 
 Northeastern University, Department of Mechanical and Industrial Engineering, Boston, USA (GRID:grid.261112.7) (ISNI:0000 0001 2173 3359); Northeastern University, Department of Bioengineering, Boston, USA (GRID:grid.261112.7) (ISNI:0000 0001 2173 3359) 
Publication year
2019
Publication date
Dec 2019
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2202772454
Copyright
© The Author(s) 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.