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

Muhammad Faiz Md ShakhihNursyazana RidzuanAsnida Abdul WahabNurul Farha ZainuddinLaila Fadhillah Ulta DelestriAnis Suzziani RosslanMohammed Rafiq Abdul Kadir
Published in: Medical & biological engineering & computing (2021)
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<0.05. While ANOVA test conducted shows that there is significant impact of loads on RMS and MF where F=12.61 and 3.59, respectively, at p< 0.05. This study suggested that skin surface temperature can be utilized in monitoring and predicting muscle fatigue in low intensity dynamic exercise and can be extended to other dynamic exercises.
Keyphrases
  • skeletal muscle
  • sleep quality
  • high intensity
  • physical activity
  • deep learning
  • healthcare
  • high frequency
  • wound healing
  • optical coherence tomography