Development of Consumer-Friendly Surface Electromyography System for Muscle Fatigue Detection

In this study, a low-cost, wireless, and smartphone-controlled surface electromyography (EMG) system was designed and developed for consumers, and the recorded EMG signals were evaluated against a reference laboratory EMG system during fatiguing contraction. Using commercially available inexpensive...

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Bibliographic Details
Main Authors: Ryuta Kinugasa, Shimpei Kubo
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10018339/
Description
Summary:In this study, a low-cost, wireless, and smartphone-controlled surface electromyography (EMG) system was designed and developed for consumers, and the recorded EMG signals were evaluated against a reference laboratory EMG system during fatiguing contraction. Using commercially available inexpensive components, the components of the EMG signal-acquisition circuit were optimized, and a microcontroller was combined with a Bluetooth module. The EMG signals were then converted from analog to digital signals and transmitted to a smartphone via Bluetooth serial communication. EMG signals from the biceps brachii of six healthy subjects were recorded separately using two EMG systems during sustained submaximal isometric contraction until the endurance limit was reached. The root mean square (RMS) and mean power frequency (MPF) of the EMG signals were calculated. The results indicated that both the EMG systems exhibited a characteristic progressive increase in EMGRMS and decrease in EMGMPF during sustained isometric contraction. The relative agreement between the two EMG systems, assessed by intraclass correlation coefficient (ICC), was excellent for EMGRMS (ICC 0.933, P < 0.001) and moderate for EMGMPF (ICC 0.662, P =0.049). The cost of the sensor components in the hardware was ¥ 8,486 per unit. The proposed consumer-friendly EMG system, which is inexpensive and highly versatile in terms of wireless and smartphone accessibility, can detect the phenomenon associated with increased amplitude and low-frequency components during muscle fatigue contraction with a magnitude similar to that of the commercially available laboratory EMG systems.
ISSN:2169-3536