Analysis and prediction of localized muscle fatigue in isometric muscle contraction
Date of Award
Doctor of Philosophy (Ph.D.)
First Committee Member
Shihab S. Asfour, Committee Chair
Second Committee Member
Tarek M. Khalil, Committee Member
The main objectives of this study were to: (1) develop, test, and validate statistical models for the detection and prediction of muscle fatigue associated with sustained muscle contraction, (2) study the effects of epoch duration on the estimated parameters from the surface electromyography (EMG), and (3) investigate the effect(s) of electrode orientation, with respect to the muscle, on surface EMG, and the detection of muscle fatigue due to isometric contraction.To achieve these objectives, two experiments were conducted. The results of the first experiment showed that both root mean square (RMS) and full wave rectified integral (FWRI) seem to be linearly related to the exerted force. The load corresponding to the maximum voluntary contraction (MVC) showed significantly higher RMS and FWRI values compared to the 50%MVC and 25%MVC. The load showed a significant increase in the lower fractile frequencies (5th, 10th and 25th). For the higher fractile frequencies, only a significant difference was found between the MVC and 25%MVC. The window size had no significant effect on the EMG estimated parameters in the time domain (FWRI and RMS). However, it showed a significant effect on the estimated characteristic frequencies of the power spectrum.The results of the second experiment indicated that the time domain parameters did not change significantly for the all interactions and main effects of the three independent variables (load, electrode orientation and muscle condition of rest or fatigue). The frequency domain parameters was significantly affected by the main effects of electrode orientation and muscle condition. Electrodes placed across the muscle fibers showed lower fractile frequencies compared to electrodes along the muscle fibers. The effect of electrode orientation was only significant for the lower fractiles with the exception of the 99th fractile (peak frequency, 1, 5, 10, 25, and 99 fractile). The effect of muscle fatigue was significant for all the characteristic frequencies used. A significant shift toward lower frequencies was observed. The shift in these frequencies was not linear across the spectrum. Therefore, monitoring a single characteristic frequency may not be adequate for the quantification of the spectrum shift. Discriminant analysis was used successfully to develop a pattern classification model for the detection of local muscle fatigue.
Engineering, Biomedical; Engineering, Industrial
Waly, Sherif M., "Analysis and prediction of localized muscle fatigue in isometric muscle contraction" (1994). Dissertations from ProQuest. 3272.