The study of muscular fatigue using sEMG signals as non-invasive method has become a major tool in physiological studies of motor behavior, control of robotic devices to assist the disability, ergonomic designs, clinical diagnosis and sport sciences among others. The search for a computational method for measuring, estimating components, identify and assessment the fatigue index has become the problem to solve because it offers a variety of applications in relation to improving the quality of life. Here is a review focused on the identification of different parameters to quantify muscle fatigue using data processing tools parametric and nonparametric. Found 6 application areas and 6 types of muscle contractions that define the application of 22 mathematical tools of biological sEMG signal processing.