Muscle tissues are responsible for producing contracting forces to enable human systems to perform several functions which include walking and running. The inability of the muscle to generate the required force is the condition called fatigue. Analysis of fatigue contractions is essential for the diagnosis of muscle disorders such as those arising due to myopathy and neuropathy. These are carried out using noninvasively recorded biosignals with the help of surface electrodes and are called Surface Electromyography signals. The behavior of these signals depends on several interdependent factors and often demand nonlinear signal processing methods to differentiate fatiguing and nonfatiguing conditions. In this work, surface EMG signals recorded on Biceps Brachii muscle under standard protocol are utilized to understand the fatiguing conditions during isometric and dynamic contractions. The random, multicomponent, nonstationary and nonlinear nature of these signals are analyzed using complex network methods. The significance of muscle endurance time on the contractility of the Biceps Brachii muscle was examined. In this defense presentation, the objectives, methods, results and significant contributions would be discussed in detail.