Electroencephalographic and electromyographic information automatic intention recognition and upper limb intelligent control method and system

Abstract

The invention relates to an electroencephalographic and electromyographic information automatic intention recognition and upper limb intelligent control method and system, which are used for rehabilitation treatment of the upper limb of a stroke patient, an electroencephalographic and surface electromyographic signal collector collects and processes the electroencephalographic and surface electromyographic signals of the patient in real time, a mixed kernel function formed by weighting a polynomial kernel function and an RBF kernel function weights is used to perform fitting and prediction, soas to more accurately identify and monitor the motion intention of the patient, and judge the corresponding degree of rehabilitation, according to which a corresponding rehabilitation training strategy is adopted. When the rehabilitation degree of the upper limb of the stroke patient is low, passive training control is adopted. When the rehabilitation degree of the upper limb of the stroke patient is high, active, assisted and resistive control modes are adopted. The hybrid kernel function support vector machine model provided by the invention has better learning ability and generalization performance, high prediction accuracy and good control performance, and the prediction result meets the index requirements of a rehabilitation robot for stroke patients.

Description

technical field [0001] The invention relates to robot control technology, in particular to an upper limb rehabilitation robot intention recognition and an intelligent control system and method based on an adaptive simulated annealing algorithm, which adopts various rehabilitation training modes to perform rehabilitation treatment for stroke patients. Background technique [0002] Clinical and research results show that stroke (stroke) and spinal cord injury are relatively common neurological diseases in major Chinese and Western countries in recent years. Improper treatment will lead to serious consequences such as hemiplegia, disability and even death. According to relevant statistics, there are only 6 million stroke patients in my country, and there are more than 2 million new stroke patients every year. Patients often suffer from sequelae such as hemiplegia. Among them, the number of patients with upper limb motor dysfunction caused by central nervous system diseases such...

AI Technical Summary

Problems solved by technology

[0014] The present invention aims at the key bottlenecks that affect system performance in the information perception, intention recognition and control accuracy of existing stroke exoskeleton upper limb rehabilitation robots, and proposes an automatic intention recognition of brain muscle information based on a hybrid kernel function support vector machine Intelligent upper limb control method and system

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