Biological motion information based upper limb shoulder elbow wrist joint motion function evaluation method

Abstract

The invention provides a biological motion information based upper limb shoulder elbow wrist joint motion function evaluation method. The method includes: choosing acceleration signals and myoelectric signals as biological motion information of upper limb motion; performing feature extraction to the acceleration signals and the myoelectric signals; on the basis, screening feature values from two aspects: screening features according to typicality and distinguishability of signal features and aiming at actions of different types and different action executing abilities; utilizing different advantages of two kinds of signals to combine the feature values of the two kinds; and taking a short form Fug1-Meyer scoring value as a standard to construct a linear regression model for optimized combination of multiple signal features, and using the optimized combination to serve as upper limb shoulder elbow wrist joint motion function evaluation index criteria. By the method, online real-time information extraction and score detection can be realized, and conventional upper limb motion function evaluation method can be substituted to quantitatively score upper limb motion functions more deeply.

Description

technical field [0001] The invention belongs to the field of signal processing, and relates to a method for evaluating the motion function of shoulder, elbow, and wrist joints of upper limbs based on biological motion information. Background technique [0002] The current research on the evaluation of motor function of patients with neuromuscular injuries is mainly in the fields of clinical medicine and information engineering, and usually uses some movement or motion characteristic parameters that reflect the executive ability of limb movement to carry out the evaluation of motor function. [0003] Evaluation methods commonly used in clinical medicine include Fugl-Meyer evaluation scale, motor function status score MSS, Barthel index, functional independence evaluation scale FIM, MAS, etc. These methods have shortcomings such as being affected by the subjective factors of the testers, and too many movements are detected, and because most of them are scale-based, they cannot...

AI Technical Summary

Problems solved by technology

[0004] The evaluation method of upper limb motor function has been widely used in clinical practice, and has good information feedback and practical experience. However, there are shortcomings such as being affected by the subjective factors of the test personnel, too many detection movem

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