Finger joint rehabilitation training evaluation method and system

Abstract

The invention relates to a finger joint rehabilitation training evaluation method. On the basis of a soft glove with pneumatic structures on finger joint positions respectively, various rehabilitationtraining methods are designed through high-precision tracking of hand movement postures, and the active and passive combined rehabilitation training is realized for an affected side hand of a hemiplegic patient from multiple aspects. Meanwhile, a system of the finger joint rehabilitation training evaluation method is designed, an optical motion capture module based on binocular vision is provided, the movement range measurement and calculation can be performed on palm fingers, far-end finger joints and wrist joint of a hand of the patient to obtain a hand movement state, and the calculation date serve as data support of the hand movement state, and can serve as the real-time input of movement signals of the affected side soft glove. Meanwhile, a grip strength sensor and a finger pinchingforce sensor are added at the same time, so that the evaluation of hand muscle strength and movement of the patient is realized, and the closed-loop rehabilitation treatment of performing evaluation,performing training and then performing evaluation in the rehabilitation training is completed.

Description

technical field [0001] The invention relates to a finger joint rehabilitation training evaluation method and system, belonging to the technical field of upper limb exoskeleton rehabilitation robots. Background technique [0002] According to epidemiological statistics, stroke has a large number of people and a high disability rate, and the limb dysfunction it brings often has a serious impact on the lives of patients, especially the sequelae of hand dysfunction, which is difficult in the rehabilitation process. Slow progress. However, looking at home and abroad, the treatment and assessment of hand function after stroke have shown inaccurate and incomplete conditions. [0003] At present, in order to obtain the quantitative motion data of the patient's hand, it is basically divided into two categories: wearable sensor solutions and non-contact vision solutions. The sensor solutions based on various wearable modules mainly use electronic measurement chips such as accelerati...

AI Technical Summary

Problems solved by technology

The advantage is that the calculation is relatively simple, and the accuracy of the information such as acceleration is high. The disadvantage is that it cannot meet the accuracy requirements for the relatively high evaluation requirements in hand function rehabilitation such as spatial positioning, and it cannot be achieved due to differences in patient age and gender. The uniformity of the wearable devices makes it impossible to achieve consistent and comparable evaluation data. At the same time, the evaluation and treatment are not combined. In the treatment, manual therapy or mechanical finger CPM equipment is used to assist the treatment, which has high cost and secondary problems. High secondary injury rate, low safety and other related issues

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