Intelligent training system and method for upper limb rehabilitation robot based on machine learning

Abstract

The invention discloses an intelligent training system and method for an upper limb rehabilitation robot based on machine learning, and the system comprises a robot auxiliary subsystem which is used for assisting a patient to complete a rehabilitation training action through an upper limb rehabilitation robot when the patient is not enough to complete a rehabilitation training task; an input statemonitoring subsystem which is used for monitoring the input degree of the patient during training through the upper limb rehabilitation robot, the myoelectricity acquisition equipment and the electroencephalogram acquisition equipment when the upper limb rehabilitation robot assists the patient; an intelligent learning subsystem which is used for learning the influence of a previously applied stimulation test on the input degree according to the input degree of the current moment so as to recommend a personalized stimulation scheme suitable for the patient at the next moment and change a rehabilitation training mode; an input state improving subsystem which is used for detecting whether the input degree of the patient is reduced or not, and intervening the next training process if the input degree is reduced. According to the invention, the system can provide an intelligent training prescription and mobilize a patient according to the condition of the patient to ensure the input stateduring training.

Description

technical field [0001] The invention relates to the technical field of upper limb rehabilitation, in particular to an intelligent training system and method for an upper limb rehabilitation robot based on machine learning. Background technique [0002] With the intensification of the aging phenomenon, the number of patients with stroke and other cerebrovascular diseases in the world increases by tens of millions every year. Stroke is considered to be the second leading cause of death and the leading cause of disability in the world. Most of the damage to the nervous system caused by stroke is permanent, but the nervous system has plasticity and redundancy. Timely treatment and rehabilitation training after hemiplegia can effectively reduce the damage or even avoid disability, and significantly improve the daily life ability of patients , and long-term rehabilitation is particularly important for the recovery of motor function. Rehabilitation robots have a development histor...

AI Technical Summary

Problems solved by technology

However, the previous research on robot-assisted rehabilitation technology focused on robotic equipment, and it was still in the training method of simulating rehabilitation physicians in terms of force and movement, ignoring the patient's own physiological and psychological state factors, let alone "communicating" with people like rehabilitation physicians , unable to provide appropriate personalized training prescriptions, resulting in low efficiency of robot-assisted rehabilitation training

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