Rehabilitation training robot for compound motion of upper limbs of hemiplegia patient

Abstract

A robot for the recovery training to combined upper limibs movements of hemiplegia patient is composed of chair, vertical post installed at side of chair, mechanical arm installed to and moving along said vertical post and consisting of mechanical upper and lower arms, bracket for wrist, and elbow joint hanger. Its advantage is high recovery effect.

Description

Technical field [0001] The invention relates to a rehabilitation training robot, in particular to a rehabilitation training robot that performs multi-joint and large-scale compound movements on the upper limbs of hemiplegic patients, and belongs to the technical field of auxiliary medical rehabilitation training equipment. Background technique [0002] At present, 1.2-1.5 million people suffer from stroke each year in my country, and half of them have serious sequelae that affect the quality of life. Moreover, as countries around the world have entered aging countries one after another, stroke patients are bound to increase. Among the sequelae of many patients caused by stroke, hemiplegia ranks first. Hemiplegia caused by stroke often has psychological and other impacts on the patient and his family. Society and families need to spend a great price to treat and care for these patients, causing a great waste of social resources. Therefore, seeking effective rehabilitation methods ...

AI Technical Summary

Problems solved by technology

[0005] But the shortcoming of this known hemiplegic upper limb rehabilitation training robot is: the robot can only drive the patient's affected limb to do small movements, and the range of motion is limited to the small area directly in front of the patient's body, and cannot drive the patient's affected limb to move toward the side of the body. Extensive stretching over a wide range of motion does not adequately provide the exercise stimulation required for CNS rehabilitation

Moreover, the robot can only drive the patient's affected limb to move in the horizontal plane, and cannot train on multiple motion planes, and there are fewer types of training actions that can be realized

Secondly, the robot is placed in a position opposite to the patient, and the movement of the robotic arm is opposite to that of the affected limb, which is not conducive to the control of the movement of the robotic arm and the realization of the algorithm in the program

Furthermore, the elbow joint support bracket of the robot is not flexible enough, and has only a single support function, which cannot allow the patient to perform autonomous support according to different situations, which is not conducive to the patient's remaining function of the affected limb

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