Time-frequency and principal-component methods for the analysis of EMGs recorded during a mildly fatiguing exercise on a cycle ergometer.
Electromyographic signals contain the information on muscle activity and have to be frequently averaged, compared, classified or details need to be extracted. A time-frequency analysis, based on wavelets, was previously presented. The analysis transformed an EMG signal into an EMG-intensity-pattern showing the intensities at any point in time for the frequencies filtered out by the wavelets. The purpose of the present study was:to define and apply a new EMG-pattern-space for the analysis of EMG-intensity-patterns; and to determine the variation of EMG-intensity-patterns while getting mildly fatigued by cycling on a cycle-ergometer. The coordinates spanning the pattern space were principal components of the measured EMG-intensity-patterns. A point in pattern-space thus represented an EMG-intensity-pattern. Fatigue resulted in points moving along a line in pattern space. The line was characterized by an intercept at time 0 and a slope. Thus mild fatigue caused a shift from an initial intensity-pattern representing the intercept to a final intensity-pattern adding gradually larger amounts of the pattern representing the slope. The intensity-pattern of the slope revealed the physiologically important individual strategies for coping with mild fatigue. Changes were observed at different times and at different frequencies during the cycling movement.
von Tscharner
Vinzenz
V
Human Performance Laboratory, The University of Calgary, Alberta, Canada. vincent@kin.ucalgary.ca
D000328:Adult; D004576:Electromyography; D016552:Ergometry; D015444:Exercise / Q000502:physiology*; D006801:Humans; D016014:Linear Models; D018763:Muscle Fatigue / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*