Electromyography (EMG) detects electrically or neurogically activated muscle cells on the basis of waveform characteristics from a recorded signal. EMG is useful for evaluating and recording movement abnormalities. The EMG signals can also detect neuromuscular activation level and recruitment order in addition to analyze the biomechanics of human or animal movement (De Luca, 1984; Furey, 1963). The EMG signals are generated based on superimposed motor action potentials during active movement. The myoelectric signals are the instantaneous algebraic summation of all electrical discharges produced by a contraction of the muscle fibers. Muscle fatigue is quantified using surface EMG signals based on the power spectrum which is the Fourier transform of EMG time series (Knowlton et al., 1951; Mannion & Dolan, 1994; Mannion et al., 1997c). Normal electrical source is a muscle membrane potential of approximately -90 mV, and measured EMG potentials range between less than 50 μV and up to 20 to 30 mV, depending on the muscle under observation (Herzog et al., 1987; Nigg et al., 1988). Typical repetition rate of muscle motor unit firing is approximately 7–20 Hz, depending on the size of the muscle, previous axonal damage, and other factors (Hoffmann, 1968; Rack & Ross, 1975). Therefore, the EMG range can be utilized in many clinical and biomechanical applications as a diagnostics tool for identifying neuromuscular diseases, assessing low back pain (LBP), kinesiology, and disorders of motor control. EMG signals are also used as a control signal for prosthetic devices such as prosthetic hands, arms, and lower limbs. It is unknown how the median frequency (MF) of an individual depends on posture, extent of physical activity prior to measurements, and other attributing factors. Such factors may influence the shift of the MF in the fatigue measurement, which is not a consistent indicator for injuries to low back muscles. Subjects with LBP have less endurance and thus smaller MF during sustained muscle contractions (Mannion et al., 1997a; Roy et al., 1997). The MF of the EMG signal is used to characterize physiological aspects of skeletal muscles. The signal from surface EMG is the instantaneous algebraic summation of action potentials from muscle fibers, and its power spectrum can be estimated from a fast Fourier transform of the signal. Fourier transform is a linear analysis of a signal and gives the power spectrum P(f) (Hobbie, 1997). A linear system is described mathematically by equations with oscillatory or exponentially growing solutions. In contrast, EMG time series have an irregular pattern so