Research on the Method of Human Lower Limb Spatial Movement Intention Recognition Based on sEMG Signals
In the current field of research on lower limb rehabilitation robots,the majority of studies focus on the rehabilitation of movements within the sagittal plane,with a lack of effective methods for recognizing the intentions of human lower limb movements in multi-dimensional space.This paper first designs and develops a new type of lower limb rehabilitation training mechanism capable of simulating movements in multi-dimensional space.Based on this,an in-depth analysis of the distribution of lower limb muscles and movement pattems is conducted.By combining sEMG signals with the innovative African vulture optimization algorithm,a new type of spatial movement intention recognition algorithm for lower limbs is developed.Finally,the effectiveness of this algorithm in recognizing multi-dimensional spatial movement intentions is validated by experiments.The results of this study not only provide a solid theoretical foundation for future active control strategies of lower limb rehabilitation robots but also open up new perspectives in the control of multi-dimensional spatial movements for rehabilitation robots.
rehabilitation robotlower limb spatial movementmovement intention recognitionactive control strategy
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