Optimization of Neural Motor Control Model Based on EMG Signals
DOI:
https://doi.org/10.71222/zv591k09Keywords:
EMG signal, neuromotor control, optimization algorithmAbstract
As an important signal of the nervous system, electromyography (EMG) is used in prosthesis control, rehabilitation training, motion intention prediction and human-computer interaction. However, its widespread application is limited by noise, large individual differences, complex computation and poor real-time performance. In this paper, the processing technology, feature extraction, control mode design and calculation optimization based on EMG are reviewed, and optimization strategies based on signal enhancement, deep modeling and accelerated calculation are proposed to ensure the robustness and timeliness of the algorithm and improve the adaptability of motion control to individuals. The results show that the optimized model can effectively improve the precision of motion control, calculation speed and cross-individual compatibility, and provide technical support for EMG intelligent prosthetics, rehabilitation AIDS and wearable neural interfaces.
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