Non-obstructive monitoring of muscle fatigue for low intensity dynamic exercise with infrared thermography technique

Surface electromyography (sEMG) has been widely used in evaluating muscle fatigue among athletes where electrodes are attached on the skin during the activity. Recently, infrared thermography technique (IRT) has gain popularity and shown to be another preferred method in monitoring and predicting mu...

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Bibliographic Details
Published in:Medical & biological engineering & computing 2021-08, Vol.59 (7-8), p.1447-1459
Main Authors: Shakhih, Muhammad Faiz Md, Ridzuan, Nursyazana, Wahab, Asnida Abdul, Zainuddin, Nurul Farha, Delestri, Laila Fadhillah Ulta, Rosslan, Anis Suzziani, Kadir, Mohammed Rafiq Abdul
Format: Article
Language:English
Subjects:
Ankle
Athletes
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Computer Applications
Electromyography
Fatigue
Human Physiology
Imaging
Infrared imaging
Monitoring
Muscle contraction
Muscle fatigue
Muscles
Muscular fatigue
Original Article
Radiology
Skin
Statistical analysis
Surface temperature
Temperature gradients
Thermography
Variance analysis
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Summary:Surface electromyography (sEMG) has been widely used in evaluating muscle fatigue among athletes where electrodes are attached on the skin during the activity. Recently, infrared thermography technique (IRT) has gain popularity and shown to be another preferred method in monitoring and predicting muscle fatigue non-obstructively. This paper investigates the correlation between surface temperature and muscle activation parameters obtained using both IRT and sEMG methods simultaneously. Twenty healthy subjects were required to perform a repetitive calf raise exercise with various loads attached around their ankle for 3 min to induce fatigue on the targeted gastrocnemius muscles. Average temperature and temperature difference information were extracted from thermal images, while root mean square (RMS) and median frequency (MF) were extracted from sEMG signals. Spearman statistical analysis performed shows that there is a significant correlation between average temperature with RMS and between temperature difference with MF values at p
ISSN:0140-0118
1741-0444
DOI:10.1007/s11517-021-02387-x