Fractal analysis of surface EMG signals from the biceps.
Nonlinear analysis techniques are necessary to understand the complexity of the EMG. The purpose of the present study was to determine the fractal dimension of surface EMG obtained from the biceps brachii of normal subjects during isokinetic flexion-extension of the arm. The measurements were obtained with different loading conditions on the arm and for various rates of flexion-extension. Fractal dimensions of the surface EMG signals were calculated for each of these conditions. ANOVA results showed statistically significant differences between the fractal dimensions calculated for different loading conditions and rates of flexion-extensin (P < or = 0.005). Linear regression analysis showed a correlation coefficient of 0.99 between the fractal dimension and the load, and a correlation coefficient of 0.98 between the fractal dimension and the rate of flexion-extension. The results of the study show that the fractal dimension can be used along with other parameters to characterize the EMG signal.
Gupta
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Department of Biomedical Engineering, University of Akron, OH 44325-0302, USA.
Suryanarayanan
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S
Reddy
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NP
D000465:Algorithms; D000704:Analysis of Variance; D001132:Arm / Q000502:physiology; D004576:Electromyography; D017709:Fractals; D006801:Humans; D007537:Isometric Contraction / Q000502:physiology; D016014:Linear Models; D018482:Muscle, Skeletal / Q000502:physiology*; D017711:Nonlinear Dynamics