Novel Design of a Robotic Arm Prototype with Complex Movements Based on Surface EMG Signals to Assist Disabilities in Vietnam

Abstract

In recent years, surface electromyography (sEMG) signals have been recognized as a type of signal with significant practical implications not only in medicine but also in the field of science and engineering for functional rehabilitation. This study focuses on understanding the application of surface electromyography signals in controlling a robotic arm for assisting disabled individuals in Vietnam. The raw sEMG signals, collected using appropriate sensors, have been processed using an effective method that includes several steps such as A/D converting and the use of band-pass and low-pass filters combined with an envelope detector. To demonstrate the meaningful effectiveness of the processed sEMG signals, the study has designed a robotic arm model with complex finger movements similar to those of a human. The experimental results show that the robotic arm operates effectively, with fast response times, meeting the support needs of disabled individuals.