Segmenting Mechanomyography Measures of Muscle Activity Phases Using Inertial Data

Richard B. Woodward,Ravi Vaidyanathan,Sandra J. Shefelbine,Maria J. Stokes

doi:10.1038/s41598-019-41860-4

Richard B. Woodward, Ravi Vaidyanathan + Show 2 more

Open Access

https://doi.org/10.1038/s41598-019-41860-4

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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.

Highlights

Monitoring of muscle activity is predominantly achieved through electromyography (EMG), a method which records the electrical response from contracting muscle fibres
Comparisons between pre- and post-exerting activity saw an increase in root mean square (RMS) amplitude in all contraction periods for both MMG and EMG, with an average percentage increase of 18.09% and 9.79%, respectively (Table 1)
The present study has shown how combining information from muscle contraction (MMG and EMG) and dynamic movement (IMU) can enable a better understanding of human muscle and motion activity at specific periods of contraction

Summary

Introduction

Monitoring of muscle activity is predominantly achieved through electromyography (EMG), a method which records the electrical response from contracting muscle fibres. While still the ‘gold standard’ EMG has well documented disadvantages including change in signal response because of skin impedance changes (e.g., during perspiration), need for electrical connection to the skin, level of hardware required for collection (amplifiers, etc.), are typically expensive, non-portable, and require training and knowledge for sensor placement and operation, which reduces its applicability in use outside of a laboratory[1,2,3]. These disadvantages, which can be managed in a controlled environment, can be difficult to handle in pervasive settings (monitoring in a natural environment). The objective of this study was to segment muscle activity phases and compare MMG and EMG measurements of muscle activity during an exerting task, to demonstrate measures of muscle activity that could be performed in a natural environment

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