Human Adaptive Mechatronics for Gait Rehabilitation using EMG-Based Neuromuscular Control
DOI:
https://doi.org/10.15662/IJEETR.2026.0802296Keywords:
Human adaptive mechatronics, gait rehabilitation, EMG signals, neuromuscular control, assistive robotics, prosthetics, exoskeleton systems, biomedical engineering, motion analysis, rehabilitation systemsAbstract
Human gait impairments caused by neurological disorders, injuries, or aging significantly reduce mobility and quality of life. This paper presents a Human Adaptive Mechatronics (HAM) system designed to assist gait using real-time electromyography (EMG) signals. The system captures muscle activity, processes it through feature extraction, and predicts intended motion using a Support Vector Neural Network (SVNN). Based on predictions, a neuromuscular controller generates control signals to actuate an exoskeleton system. A cybernetic feedback loop ensures adaptive and real-time assistance. Experimental results demonstrate improved gait synchronization and responsiveness, making the system suitable for rehabilitation and assistive applications.
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