Muscle fatigue detection using near-infrared spectroscopy and electromyography

Abstract

Introduction: Muscle fatigue is often experienced by athletes and in work settings. Excessive fatigue can lead to injury and musculoskeletal disorders. Surface electromyography (EMG) is typically used to detect and ultimately prevent fatigue during isometric movement. The application of EMG to fatigue detection in dynamic movement requires, however, a secondary confirmation of fatigue based on physiological measures. Our objective was to determine if muscle oxygenation derived via near-infrared spectroscopy (NIRS) was correlated with relevant EMG indicators of neuromuscular fatigue and whether observed correlations were related to the fatigue process. Methods: Bilateral electromyograms from three upper leg muscles and the tissue oxygenation index (TOI) of the vastus lateralis muscle were recorded in sixteen non-disabled individuals during cycle ergometry to volitional exhaustion. Six EMG activity features were extracted and the Pearson correlation coefficient between each feature and TOI was determined. Results: The EMG root mean square, spectral standard deviation, second spectral moment, and zero-crossing rate (ZC) were strongly correlated with TOI. The time course of ZC and the correlation of this feature with TOI suggest that there could be a relation between muscle oxygenation and fatigue. Conclusion: Future work should use the knowledge gained in this study to investigate whether NIRS can be used to verify the onset of fatigue as detected by EMG.

Keywords

• muscle fatigue
• near-infrared spectroscopy
• electromyography
• pearson correlation