Upper limb rehabilitation robot rehabilitation training motion function assessment method

Abstract

An upper limb rehabilitation robot rehabilitation training motion function assessment method is provided. A self-correcting AHP-fuzzy analysis evaluation method is adopted, clinic motion function assessment contents are converted into an indicator system of assessment of an upper limb rehabilitation robot, and by utilizing a data collection function of the upper limb rehabilitation robot, motion function assessment indicators of the upper limb rehabilitation robot are quantified, and assessment criteria of the assessment indicators are given; a recurison order hierarchy and a review system of the upper limb rehabilitation robot assessment indicators are determined on the above bases, and an upper limb rehabilitation robot motion function assessment model is established; and upper limb rehabilitation robot rehabilitation training motion functions are assessed. According to the method provided by the present invention, the clinic motion function assessment contents are converted into the indicator system of assessment of the upper limb rehabilitation robot, the self-correcting AHP-fuzzy analysis evaluation method is very practical and effective in upper limb rehabilitation assessment, and results obtained by the method are matched with clinic motion function assessment results. The upper limb rehabilitation robot rehabilitation training motion function assessment method has predictable large economic and social values.

Description

technical field [0001] The invention relates to the technical field of medical device design and application, and in particular provides a method for evaluating motor function of an upper limb rehabilitation robot for rehabilitation training. Background technique [0002] In the prior art, the rehabilitation evaluation of hemiplegia after stroke is mainly carried out by evaluating the patient's movement, speech, psychology, and daily life functions. [J]. Chinese Journal of Rehabilitation Medicine, 2004, 19(3): 232-233], briefly described as follows: [0003] (1) Evaluation of motor function: master the abnormal movement patterns of hemiplegic patients, and use the main clinical methods for evaluating motor function of hemiplegic patients according to the evaluation content; (2) Evaluation of speech and language functions: comprehensive aphasia examination, dysarthria examination , speech apraxia test, speech disorder test, dementia aphasia test and other aspects of speech f...

AI Technical Summary

Problems solved by technology

None of them are quantitative calculations and the sensitivity and accuracy are not high, and there are shortcomings such as too many detection actions, time-consuming detection and data statistics, and patients are prone to fatigue.

In addition, in the evaluation process, in order to ensure the accuracy of the results, the evaluation is often ca

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