Muscle fatigue is a complex physiological phenomenon. The real-time assessment of muscle fatigue by surface electromyography requires that fatigue indices are rapid, noise immunity, and reliable. Thus, the real-time assessment of muscle fatigue has been proposed based on the marginal spectrum entropy. First, deterministic periodic signals with different data lengths and Gauss white noise has been used to analyze the rapidity of marginal spectrum entropy and the robustness of data length. Then, the muscle fatigue signals of long extensor carpi when the 10 subjects grip under continuous static contraction state decreases from 100% maximal voluntary contraction to 50% maximal voluntary contraction, has been used to analyze the reliability of assessment method of muscle fatigue based on marginal spectrum entropy and the stability of the method applied to different individuals. Finally, the noise immunity of marginal spectral entropy has been investigated by adding Gauss white noise and electrocardiogram noise into the muscle fatigue signal of a subject. The experimental results show that compared with approximate entropy and median frequency, the calculation based on marginal spectrum entropy is more rapid and data length robustness is more obvious. Also, Goodness of fit based on marginal spectrum entropy is better(0.46±0.14) ,the marginal spectrum entropy can reliably assess muscle fatigue. Slope of the coefficient of variation is lower(30.30%),the marginal spectrum entropy is highly stable for different individuals. Rate of change of the goodness of fit of the marginal spectral entropy is lower after adding Gaussian white noise and electrocardiogram noise(additive Gaussian white noise and additive electrocardiogram noise are 34.39% and 3.78% respectively).Therefore, marginal spectrum entropy has the advantages of rapidity, noise immunity, reliability of assessing muscle fatigue. It can be concluded that the marginal spectrum entropy is suitable for real-time assessment of muscle fatigue, which supplies a new method for muscle fatigue assessment.