Cerebral stroke patient symmetric gait-oriented lower limb motion function assessment method and system

By collecting and analyzing electromyographic signals from the lower limbs of stroke patients, a multimodal feature fusion dataset was constructed, and a lightweight gradient booster algorithm was used to evaluate the model. This solved the subjectivity problem in the assessment of lower limb motor function in existing technologies, and enabled quantitative assessment of lower limb motor function and the development of personalized rehabilitation plans for stroke patients.

CN122074967APending Publication Date: 2026-05-26CHANGCHUN UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHANGCHUN UNIV OF TECH
Filing Date
2026-04-23
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing lower limb motor function assessment techniques suffer from strong subjectivity and a lack of quantitative analysis, making it difficult to accurately assess the rehabilitation progress of stroke patients and develop personalized intervention strategies.

Method used

By collecting lower limb surface electromyography signals from stroke patients and healthy subjects, feature extraction and quantification were performed to construct a multimodal feature fusion dataset. A lightweight gradient booster algorithm was used to build an evaluation model, and the contribution of each feature was quantified using the Shapley additive interpretation method to achieve qualitative classification and functional scoring of the subjects' pathological and normal movement patterns.

Benefits of technology

It enables an effective and comprehensive quantitative assessment of lower limb motor function in stroke patients, providing quantitative evidence, laying the foundation for the development of personalized rehabilitation training plans, and improving the scientific nature and accuracy of the assessment.

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Abstract

The invention relates to the field of lower limb motion function evaluation, and particularly discloses a lower limb motion function evaluation method and system for symmetrical gaits of a stroke patient. The lower limb motion function assessment method is designed for solving the problem of subjectivity of motion function assessment of a stroke patient. The method comprises the following steps that S101, lower limb surface electromyogram signals of a subject in the target task movement process are collected; step S102, preprocessing the electromyographic signals; s103, extracting time domain features, symmetry features and muscle collaborative quantitative features of the preprocessed surface electromyogram signals, and constructing a feature fusion data set; step S104, building a lower limb motion function evaluation model by using a lightweight gradient lifting mechanism; and S105, classifying the pathology and normal motion modes of the subject according to the evaluation model, outputting motion function scores, and quantifying the contribution of the characteristics through a summer-Part explanation method.
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Citation Information

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