Abstract
Myoelectric (ME) signals are useful for estimating muscle fatigue, but the estimation of fatigue in the field is difficult. Fatigue is related not only to the neuromuscular system but also to the cardiorespiratory system. We studied a method of evaluating muscle fatigue using a superimposed M wave (SM wave) and background activity at several contraction levels. The SM wave is the electrically elicited M wave superimposed on a voluntary contraction. We estimated the mean power frequency (MPF) of background activity and the instantaneous frequency (IF) at the first peak of the SM wave. The MPF and IF were uncorrelated, or sometimes showed negative correlation, during low-level contractions. At high-level contractions, however, MPF and IF were closely correlated at the beginning and then became uncorrelated as muscle fatigue progressed. The samples {mpf, ifs} were classified into two groups, G 1 and G 2, depending on the features between two contraction phases: muscle force sustaining phase, and degeneration phase. Hence the purpose of this study was to expand our method of fatigue estimation in the field, based on results at different contraction levels. The use of low-level contractions seems suitable in field assessment. Two healthy male subjects (22 years old) ran on a treadmill for three consecutive days. On the first day, the running speed was 7.5 km/h; on the second day, an incline of 4.5 degrees was added; and on the third day, an incline of 9 degrees was used. We measured 5 minutes of biosignals at 30% of maximum voluntary contraction (MVC) during the endurance period before and after exercise. Each subject was seated in a chair, with a force transducer attached to the instep of the foot. We fixed a pair of stimulation pads on the motor point area and adjusted the stimulation levels to obtain the highest superimposed M wave. We measured heart rate, force output, and ME signals from the tibialis anterior muscle. The MPF-IF pattern of the first day was the same as those at low-level contractions. On the third day, however, they showed features of muscle fatigue like those at high-level contractions. This change in the MPF-IF patterns was probably correlated with the accumulation of muscle fatigue and agreed with subjective reports. Furthermore, the spectrum analysis of heart rate variability showed augmented autonomic nervous activity on the third day: increase in frequencies and decrease in amplitudes of the low-and high-frequency components. Our method is, therefore, effective for assessing muscle fatigue quantitatively and has potential for evaluating fatigue from local muscular fatigue.
