Abstract

Abstract Plantar pressure is the main mechanical parameter to understand human lower limb movement, which can fully show the health status of human spine, foot, leg and other regions.At present, researchers have carried out empirical analysis on the rehabilitation training process of lower limbs, but due to the defects of guidance methods and too vague evaluation indicators, it is impossible to conduct comprehensive monitoring and feedback on the rehabilitation process of patients. Therefore, on the basis of the modeling method based on the understanding of skeletal muscle set, the rest of the lower limbs dyskinesia patients rehabilitation training, puts forward the plantar pressure changes as the core of human lower limb rehabilitation training monitoring and feedback methods, at the same time using autoregressive model to construct the algorithm model of lower limb exoskeleton, updating method of the weighted coefficient of contrast research. The final results show that the least mean square error (LMS) algorithm can provide effective driving force for the rehabilitation training model of lower extremity exoskeleton disease, and feedback evaluation of the whole rehabilitation training process

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