Surface Electromyography (sEMG), the bioelectric currents generated by muscle contractions on the human body surface, enables motion control of exoskeletons. sEMG signal processing combines both software and hardware components, where accuracy and timeliness directly impact the practicality of exoskeleton motion control systems. Addressing the needs of hemiplegic patients with hand function impairments, this paper designs an improved sEMG signal processing system for exoskeleton motion control and completes the structural design and physical implementation of an exoskeleton finger. Experimental results demonstrate that the exoskeleton finger exhibits excellent adaptive capability, cooperating with human fingers to grasp various objects in daily life scenarios.
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