Abstract

Currently, there are many patients with lower extremity motor dysfunction, and weight support gait training is a common rehabilitation method, among which weight support is an extremely important part. In view of the traditional weight support system (WSS) can't cooperate with gait training system and unable to follow the patients' gravity center in rehabilitation training, a new type of WSS of lower limb rehabilitation robot is developed in this paper. Design includes device for carrying gait training equipment which can easily cooperate with gait training system, and a bionic adjustable cable-driven weight support mechanism for simulating the gravity center trajectory while walking normally. First, in order to ensure the safety of patients and equipment, the static analysis of frame was carried out to verify the structural strength. Next, the self-learning PID control algorithm based on BP neural network was designed to follow the control of gravity center. The simulation results showed that the algorithm can track the target trajectory well and verify the feasibility of the system design.

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