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

Abstract

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 EMG RMS and decrease in EMG MPF during sustained isometric contraction. The relative agreement between the two EMG systems, assessed by intraclass correlation coefficient (ICC), was excellent for EMG RMS (ICC 0.933, P < 0.001) and moderate for EMG MPF (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.

A Surface Electromyography (sEMG) System Applied for Grip Force Monitoring

“…As a result, two acquisition experiments were performed using two sensors separately. The skin surface on which the electrodes were placed was permanently marked using a marker pen to ensure the sensor attachment location was the same in both experiments [ 54 ]. Normalization of the signals afterwards is necessary because of the difference between output ranges of each system.…”

Multi-Electrode EMG Spatial-Filter Implementation Based on Current Conveyors

“…Their usefulness stems from their ability to obtain an EMG output with filtered muscular crosstalk components, thereby increasing the spatial selectivity of the measurement [9][10][11]. Improvements in electrode materials and support, as well as electronics miniaturization, have led to the implementation of wearable sEMG sensors in compact packages [12][13][14][15]. When the number of contacts in a stand-alone active EMG multi-electrode increases, after a certain point, it is convenient to acquire all channels individually and perform the desired function digitally using arrays, such as in structures larger than 8 × 8 contacts [16,17].…”