Intelligent orthopedic rehabilitation training monitoring system based on multi-modal sensing

By collecting joint angle and torque data through multimodal sensors, and combining Savitsky-Gorye filters and defensive contraction discrimination modules, the activity boundaries are dynamically adjusted, solving the problem of insufficient loosening and mechanical characteristic recognition in existing monitoring systems, and improving the safety and accuracy of intelligent orthopedic rehabilitation training.

CN121647658AActive Publication Date: 2026-03-13NANTONG UNIV
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Patent Information

Application Number
CN202610164491.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-02-05
Publication Date
2026-03-13
Estimated Expiration
2046-02-05

AI Technical Summary

Technical Problem

Existing intelligent orthopedic rehabilitation training monitoring systems rely on inertial sensors and flexible bandages for mechanical fixation, which are prone to loosening or displacement. They cannot accurately identify sudden changes in the mechanical properties of the joint, especially when muscle spasms or pain trigger physiological antagonistic responses, resulting in insufficient training safety.

Method used

Multimodal sensors are used to synchronously collect joint angle and torque data. The data is then processed by a Savitsky-Gorye filter to identify instantaneous dynamic stiffness changes. Combined with a defensive contraction discrimination module, the activity boundary is dynamically adjusted to generate a reverse braking command to protect the joint.

Benefits of technology

It enables multidimensional biomechanical state perception of patients' real-time physiological feedback, automatically adjusts activity boundaries, prevents secondary damage caused by forcibly exceeding pain thresholds, and improves the safety and accuracy of training.

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Abstract

The invention relates to the technical field of monitoring and alarming, in particular to an intelligent orthopedic rehabilitation training monitoring system based on multi-modal sensing, which comprises a basic data synchronous acquisition module, a dynamic stiffness differential analysis module, a defensive contraction judgment module and a load boundary dynamic reconstruction module. According to the method, a time sequence is constructed by synchronously collecting joint angle and moment data, an instantaneous dynamic stiffness change trend is analyzed by combining a moment and angle difference value, a Savitz-golay filter is used for carrying out second-order differential processing on dynamic stiffness to capture a stiffness second-order derivative mutation point, and the critical moment when defensive contraction pain occurs to the joint of a patient is recognized. The maximum activity angle upper limit is dynamically reconstructed based on the critical angle and the safety buffering difference value, a control instruction is directly fed back to a driving end to execute reverse braking, crossing from single-position monitoring to multi-dimensional mechanical state sensing is achieved, it is ensured that the activity boundary is automatically adjusted according to real-time physiological feedback of a patient, and the safety performance of the patient is improved. And secondary injury caused by forcibly breaking through a pain threshold value is prevented.
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