Abstract
The percentage of people having a lower leg amputation is high, and the incidence of unemployment among these amputees is likewise rising. Hence, it requires the intervention of an innovative solution to serve the function of a lost limb. Electromyogram (EMG) signals is a result of the potential generated by muscles during contraction. In this work, an attempt has been made to extract EMG signals from four set of muscle groups and the acquired signals were pre-processed and transformed to pulses to extract the contraction phase of the signal. Furthermore, the processed signals were subject to feature extraction process where in the Mean Absolute Value (MAV), Integrated EMG Feature (IEMG) and various statistical parameters associated with the signal such as the mean, median, standard deviation, variance, kurtosis, skewness was calculated in order to serve as an input to drive the stepper motor of a transfemoral prosthesis. To promote real time acquisition and control, a transfemoral socket with an ischial containment has been designed.
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