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Nonlinear time-course of lumbar muscle fatigue using recurrence quantifications
S Ikegawa1, M Shinohara, T Fukunaga
1Laboratory for Exercise Physiology, Tokyo Metropolitan College, Akishima, Japan.
Biological Cybernetics
|June 3, 2000
Summary
Muscle fatigue analysis using nonlinear recurrence quantification analysis (RQA) reveals complex, nonlinear processes not detected by traditional linear methods like fast Fourier transform (FFT). RQA offers deeper insights into the time-course of skeletal muscle fatigue.
Area of Science:
- Biomechanics
- Neuroscience
- Physiology
Background:
- Skeletal muscle fatigue is commonly modeled as a linear process based on electromyography (EMG) spectral frequency decrease.
- Fast Fourier Transform (FFT) analysis, a linear tool, is standard for assessing EMG during fatigue.
Purpose of the Study:
- To reevaluate the time-course of muscle fatigue using nonlinear recurrence quantification analysis (RQA).
- To compare the efficacy of RQA versus FFT in characterizing muscle fatigue dynamics.
Main Methods:
- Surface EMG data were collected from the multifidus muscle during isometric posture-holding in 17 human subjects.
- Recurrence quantification analysis (RQA) and Fast Fourier Transform (FFT) were employed to analyze EMG time-series data.
Main Results:
- FFT criteria identified muscle fatigue as linear in 59% of subjects.
- RQA criteria revealed nonlinear fatigue dynamics in 76% of subjects.
- RQA accurately depicted both slow and fast transients in a nonlinear mathematical process, unlike FFT.
Conclusions:
- Nonlinear analysis techniques, such as RQA, provide a more comprehensive understanding of muscle fatigue.
- Muscle fatigue involves a summation of nonlinear and competing processes, better captured by RQA than linear methods.