Continuous wavelet transform-based analysis of shoulder muscle fatigue during dynamic abduction: a surface...

Area of Science:

• Biomechanics
• Neuroscience
• Signal Processing

Background:

• Quantifying neuromuscular fatigue from surface electromyography (sEMG) during dynamic movements is challenging due to signal non-stationarity.
• Wavelet-based methods show promise for analyzing muscle fatigue in dynamic tasks, but protocols and metrics vary.
• This study focuses on dynamic shoulder abduction, a key movement for daily activities.

Purpose of the Study:

• To evaluate a Continuous Wavelet Transform (CWT)-based framework for assessing fatigue-related spectral changes in sEMG during dynamic shoulder abduction.
• To compare the CWT approach with traditional Fast Fourier Transform (FFT) methods for fatigue quantification.
• To investigate the impact of load on neuromuscular fatigue in shoulder muscles.

Main Methods:

• Eight healthy subjects performed dynamic shoulder abductions with and without 2-kg weights.
• Surface EMG signals from upper trapezius (UT) and lower trapezius (LT) were recorded.
• CWT and FFT were used to analyze median frequency changes over time, with linear regression quantifying fatigue.

Main Results:

• The CWT framework detected significant load-related reductions in median frequency slopes for the right UT, left UT, and right LT.
• The upper trapezius showed significantly greater fatigue responses compared to the lower trapezius.
• CWT analysis provided stronger statistical evidence of fatigue compared to FFT analysis.

Conclusions:

• The applied CWT-based framework is feasible for detecting fatigue-related spectral changes during dynamic shoulder movements.
• This approach overcomes limitations of conventional frequency-domain methods for sEMG analysis.
• The CWT framework shows potential for applications in biomechanics, rehabilitation, and performance monitoring.