The aim of this paper is to design and develop a low-cost prosthetic arm based on surface electromyography (sEMG) signal activities of the biceps muscle during upper-limb movement. Different methods are described in the literature, but many problems are encountered in dealing with the online processing of raw EMG (rEMG) signals, such as signal sampling and memory requirements. In this paper, the enveloped EMG (eEMG) signal is used as a control signal that reduces signal sampling rate and memory requirements. The relationship between elbow motion and the activity level of the biceps muscle is characterized using relevant extracted features (root mean square (RMS)). Validation of the proposed low-cost system is conducted using comparison with a professional biomedical system (Bioback MP150). In addition, the estimated equation of movements of each subject is estimated based on the recorded data. From this equation, the angle of motion is calculated as the control of the movement of the robotic arm. Finally, the system proposed in this paper considers the eEMG signal rather than the rEMG signal and deals with the signal based on a sample of 1 KHz rather than 10 KHz. This system reduces our target cost (reduction in hardware requirements and processing time) with acceptable accuracy. The experimental results illustrate that the eEMG signal has the same features-print as that of the rEMG signal, and the eEMG signal can generate the control signal required to move the prosthetic arm.

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