Analysis of Surface EMG Signals under Fatigue Conditions using Sum of Sines Models

Muscle fatigue is a common experience for all age groups. In this work a model to fit the fatigue and non fatigue surface electromyography (sEMG) signals using sum of sines is proposed. Signals are recorded from Biceps Brachii muscle of five healthy volunteers until fatigue using a well defined protocol. The fatigue and non fatigue conditions are analysed separately by non linear dynamical model. The sum of sine model is selected for fitting the signals. The sin7 model is found to be the best non linear fit for non fatigue condition and sin8 for fatigue condition. The Root Mean Square Error (RMSE) of fatigue condition reduced by 4 from sin7 model to sin8 model. Also the fatigue signal tends to be periodic than non fatigue signal. This method may be further extended to the non linear analysis of muscular disorders.