Electromagnetic interference-free ultrashort wave intelligent physiotherapy self-adaptive regulation and control system based on biofeedback

By combining biofeedback monitoring and neural network models, personalized adaptive control of treatment parameters of ultra-shortwave therapy equipment has been achieved, solving the problem that traditional equipment cannot be adjusted in real time, and improving treatment effectiveness and safety.

CN121754810AInactive Publication Date: 2026-03-31SECOND MEDICAL CENT OF CHINESE PLA GENERAL HOSPITAL
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Patent Information

Application Number
CN202511926955.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-19
Publication Date
2026-03-31
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Traditional shortwave diathermy equipment cannot adjust treatment parameters in real time according to the individual physiological response of patients, resulting in large individual differences in treatment effects. Furthermore, it lacks an effective biofeedback mechanism, making precise control difficult.

Method used

The biofeedback-based electromagnetic interference-free ultra-shortwave intelligent physiotherapy system monitors target area physiological data non-contactly, predicts tissue response using neural network models, and assesses treatment parameters using Pareto front plots, thereby achieving personalized adaptive adjustment of treatment parameters.

Benefits of technology

It enables precise treatment based on individual patient characteristics and real-time physiological data, improving treatment effectiveness and patient satisfaction, reducing the risk of overtreatment, and ensuring the dynamic adaptability and safety of the treatment process.

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Abstract

The invention discloses an electromagnetic interference-free ultrashort wave intelligent physiotherapy self-adaptive regulation and control system based on biofeedback, and belongs to the technical field of medical physiotherapy. The system solves the problems that an existing system cannot carry out real-time adjustment according to the physiological reaction of a patient individual, and treatment parameters are difficult to accurately regulate and control, and auxiliary features are generated by obtaining the individual features and real-time physiological data of the patient and combining context features; predicting probability distribution of tissue reaction by using a neural network model, calculating a confidence interval of the probability distribution, and automatically generating an initial treatment mode by comparing the confidence interval with a threshold value; the treatment effect is simulated, and possible complications and adverse reactions are predicted; evaluating curative effects and risks under different treatment parameter combinations by combining a Pareto frontier map, and automatically generating an optimal treatment parameter combination; treatment parameters are adjusted in time according to the real-time response of the patient, and the dynamic adaptability of the treatment process is ensured, so that personalized treatment is realized, and the treatment effect and the patient satisfaction are improved.
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