Variable-impedance lower limb rehabilitation robot control method based on brain muscle information

Abstract

The invention discloses a variable-impedance lower limb rehabilitation robot control method based on brain muscle information. The method includes: collecting electroencephalogram and surface electromyogram signals of a patient in real time through an electroencephalogram and surface electromyogram signal collector, and monitoring and evaluating rehabilitation degree of the patient; adopting different rehabilitation training strategies; when the rehabilitation degree is low, implementing passive training control, adopting a PD position servo control method, and controlling a lower limb rehabilitation device to enable the patient to move with a correct physiological gait track; when the rehabilitation degree is high, adopting an active control mode, and predicting a movement intention of the patient by extracting feature vectors of electroencephalogram signals and surface electromyogram signals of the patient in real time; using a fuzzy neutral network algorithm to integrate the electroencephalogram signals and the surface electromyogram signals to generate a movement gait track curve expected by the patient in real time; utilizing a variable-impedance control method to realize active, realtime and synergistic control of a lower limb rehabilitation robot man-machine system.

Description

technical field [0001] The invention relates to robot control technology, in particular to a control method for a lower limb rehabilitation robot. Background technique [0002] In recent years, the number of patients with lower extremity motor dysfunction caused by central nervous system diseases such as spinal injuries and strokes has increased sharply, seriously endangering human health. With the development of society and the improvement of people's medical care and living standards, the health of the disabled has attracted the attention of the whole society. Weight-loss walking training is one of the important means of walking rehabilitation for patients with such diseases, and a large number of clinical studies have confirmed its effectiveness. Traditional rehabilitation treatment methods mainly rely on nurses to assist patients in rehabilitation training. The effect of rehabilitation training depends on the technical level and love of nurses. At the same time, the num...

AI Technical Summary

Problems solved by technology

Due to the lack of time-varying impedance characteristics that consider the characteristics of human motion, the real-time collaborative control of the human-machine system cannot be well realized.

In addition, the lack of real-time monitoring of the patient's physiological information and evaluation of the degree of rehabilitation, real-time feedback of the degree of rehabilitation, and advance prediction and correction of human body motion control are all difficult, and it is impossible to realize the active cooperative control of the human-machine system in the true sense.

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