Limb rehabilitation exercise data evaluation system based on wearable device

By using phase space reconstruction and multi-dimensional feature fusion technology, the problem of misjudgment in the assessment of limb movement data in existing technologies has been solved, enabling accurate identification of limb movements and personalized rehabilitation assessment, thereby improving the safety and effectiveness of rehabilitation training.

CN121725985AActive Publication Date: 2026-03-24CHONGQING QING ER TECH CO LTD
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Patent Information

Application Number
CN202610228834.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-02-26
Publication Date
2026-03-24
Estimated Expiration
2046-02-26

AI Technical Summary

Technical Problem

Existing technologies struggle to deeply analyze the dynamic characteristics of limb movement data, leading to misjudgments of rehabilitation status, an inability to effectively distinguish between pathological tremors and rigid convergence states, and difficulty in identifying stable compensatory movements, thus failing to meet the needs of personalized and precise rehabilitation.

Method used

The phase space reconstruction unit acquires limb movement time series data, and uses the mutual information method and the spurious neighbor method to calculate the optimal delay time and embedding dimension. The state vector is constructed and mapped to the high-dimensional phase space. Combined with trajectory deviation analysis and nonlinear stability analysis, a rehabilitation exercise quality assessment report is generated. The compensation type and pathological state are identified through multi-dimensional feature fusion calculation.

Benefits of technology

It achieves precise decoupling and recognition of limb movements, improves the reliability and personalized matching of assessments, ensures dynamic adjustment of rehabilitation standards to patients' actual abilities, and enhances the safety and effectiveness of rehabilitation training.

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Abstract

The invention relates to the technical field of medical rehabilitation monitoring and data processing, in particular to a limb rehabilitation exercise data evaluation system based on wearable equipment, which comprises a phase-space reconstruction unit for fusing inertial data to construct a state vector and mapping to generate a phase-space state track; the trajectory deviation analysis unit is used for projecting the point cloud to a standard reference trajectory and quantifying a distribution state to generate a trajectory cross-border index; the nonlinear stability analysis unit is used for calculating a maximum Lyapunov index based on trajectory evolution and generating a motion stability classification label; the multi-dimensional feature fusion evaluation unit is used for fusing indexes and labels to decouple and identify compensation and pathology, and triggering real-time feedback; the reference parameter self-adaptive updating unit is used for updating pipeline parameters by utilizing topological characteristics; according to the method, accurate decoupling and personalized evaluation of the rehabilitation exercise quality are realized.
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