CN-122005186-A - Control system of intelligent shoulder-neck crotch thermal therapy equipment based on multi-mode feedback

CN122005186ACN 122005186 ACN122005186 ACN 122005186ACN-122005186-A

Abstract

The invention discloses a control system of intelligent shoulder, neck and crotch thermotherapy equipment based on multi-mode feedback, which relates to the technical field of medical appliances and comprises a multi-mode sensing module, a central processing unit and an execution module; according to the invention, an adaptive heat treatment scheme can be automatically generated according to physiological data of a user and heat treatment rehabilitation courses, a doctor is assisted to carry out heat treatment operation, and then intelligent linkage and self-adaptive adjustment of a plurality of heat treatment modules such as shoulders, necks and crotch are realized through a cooperative control module, intelligent linkage and self-adaptive adjustment of the plurality of heat treatment modules are realized, the pertinence and comfort degree of heat treatment are remarkably improved, meanwhile, the multipoint fusion temperature monitoring technology is adopted, the advantages of a non-contact type sensor and a contact type sensor are combined, the accurate control of a temperature field is realized, the local overheating or insufficient heating is effectively avoided, the safety is high, the problem of instruction conflict of multi-channel operation is solved, the uniqueness and the safety of system response are ensured, and the man-machine interaction experience is optimized.

Inventors

Ge Luping
Zhan Tingjun
ZHANG BIN

Assignees

南京从景生物技术有限公司

Dates

Publication Date: 20260512
Application Date: 20260227

Claims (6)

1. The control system of the intelligent shoulder and neck crotch thermotherapy equipment based on the multi-mode feedback is characterized by comprising a multi-mode sensing module, a central processing unit, a thermotherapy execution module and a doctor end, wherein: the multi-mode sensing module is used for acquiring multi-point temperature feedback signals, historical thermal therapy data and real-time physiological data of a user and user operation instruction signals in real time and sending the signals to the central processing unit; the central processing unit is electrically connected to the multi-mode sensing module and is configured to run a plurality of functional logic modules; the functional logic module operated by the central processing unit comprises a temperature parameter generating module, a multipoint fusion temperature monitoring module, an operation arbitration module and a cooperative control module, wherein: The temperature parameter generation module is used for acquiring historical heat treatment data and real-time physiological data of a user, constructing a scheme generation model based on a deep learning algorithm, generating a current heat treatment scheme by combining the historical heat treatment data, sending the current heat treatment scheme to a doctor end, generating an executable heat treatment scheme according to a judgment result of the doctor end, further generating a heat treatment operation instruction, sending the heat treatment operation instruction to the operation arbitration module, adaptively optimizing the executable heat treatment scheme based on the real-time physiological data, generating an optimized operation instruction and sending the optimized operation instruction to the operation arbitration module; the multipoint fusion temperature monitoring module is used for acquiring real-time temperature data, generating high-precision real-time temperature field distribution based on a fusion algorithm, and combining a PID control algorithm to realize accurate closed-loop temperature control of the thermal therapy execution module; The operation arbitration module is used for acquiring the thermotherapy operation instruction, receiving user operation instructions from different channels, performing operation arbitration according to a preset safety priority rule when instruction conflict is detected, and outputting a unique effective execution instruction to the cooperative control module; The cooperative control module is used for synthesizing the temperature data provided by the multipoint fusion temperature monitoring module according to the effective execution instruction output by the operation arbitration module, dynamically adjusting the working parameters of each thermal therapy execution module, and realizing the intelligent and personalized cooperative work of the multiple modules.
2. The control system of a multi-modal feedback-based intelligent shoulder-neck crotch hyperthermia device according to claim 1, wherein the hyperthermia execution module is electrically connected to the central processing unit, comprising a shoulder heating unit, a neck heating unit and a crotch heating unit.
3. The control system of the intelligent shoulder, neck and crotch hyperthermia device based on the multi-modal feedback according to claim 1, wherein the doctor side is configured to obtain an executable hyperthermia scheme, the executable hyperthermia scheme includes a target temperature curve, a heating duration, a heating rate and a hyperthermia mode, empirically determine the executable hyperthermia scheme based on historical hyperthermia data of a patient, and make an auxiliary correction on the executable hyperthermia scheme, obtain an optimized executable hyperthermia scheme, generate a hyperthermia operation instruction based on the optimized executable hyperthermia scheme, and send the instruction to the operation arbitration module.
4. The control system of a multi-modal feedback based intelligent shoulder-neck crotch hyperthermia device according to claim 1, characterized in that the specific procedure of obtaining an executable hyperthermia solution and generating optimized operation instructions is as follows: S101, acquiring historical heat treatment data and real-time physiological data of a user, wherein the historical heat treatment data comprises identification information of the user, a historical heat treatment scheme and feedback data after heat treatment, and the historical heat treatment scheme specifically comprises a target temperature curve, heating duration, heating rate and a heat treatment mode; the real-time physiological data are collected in real time through a PPG photoelectric volume pulse wave sensor and a GSR skin conductance sensor which are integrated on the intelligent shoulder, neck and crotch thermotherapy equipment, and the real-time physiological data comprise heart rate, heart rate variability and skin conductance; s102, a model is generated based on a long-short-time memory network construction scheme, and a training sample is obtained by integrating a history thermal therapy scheme after normalization treatment, wherein the specific training process is as follows: Training input, which comprises identification information of a user, a history heat treatment scheme, feedback data after heat treatment and physiological data at the initial stage of a treatment course; Training the label, namely acquiring an optimal heat treatment scheme which is defined as a heat treatment parameter curve with highest doctor score, highest subjective comfort level of a patient and most obvious pain relief improvement on the premise of ensuring safety; training targets, namely learning a complex nonlinear mapping relation from a patient state to an optimal thermal therapy scheme; S103, the historical heat treatment data of the patient are called, real-time physiological data before the heat treatment is started are collected to be used as a base line value, the data are input into a trained scheme generating model, and a multi-dimensional current heat treatment scheme is output; S104, continuously receiving the real-time physiological data stream from the multi-mode sensing module by the temperature parameter generating module during the execution of the current hyperthermia scheme, and continuously comparing the real-time physiological data with a baseline value acquired before the start of the current hyperthermia; s105, setting an optimization logic based on an adaptive optimization rule of physiological feedback, evaluating a comparison result according to the optimization logic, and generating an optimization operation instruction according to the comparison result.
5. The control system of the intelligent shoulder, neck and crotch hyperthermia device based on multi-modal feedback according to claim 1, characterized in that the specific process of realizing the accurate closed-loop temperature control of the hyperthermia execution module is as follows: S201, acquiring real-time temperature data, wherein the real-time temperature data comprises thermal treatment temperature data and body surface temperature data, the thermal treatment temperature data are acquired through contact sensors integrated on a substrate of the thermal treatment execution module, and the body surface temperature data are acquired by adopting a non-contact temperature sensor arranged between intelligent shoulder, neck and crotch thermal treatment equipment and a skin contact surface of a user; s202, acquiring equipment parameters of intelligent shoulder and neck crotch thermotherapy equipment, establishing a thermal control physical model based on heat conduction, and taking body surface temperature data as target temperature data, wherein the thermal control physical model is used for evaluating time and attenuation required by heat transfer from a thermotherapy execution module to a body surface; s203, inputting the hyperthermia temperature data of the thermal execution unit at the time k-1 into a thermal control physical model at the time k to obtain a body surface temperature predicted value at the time k; S204, calculating Kalman gain between the body surface temperature predicted value and the body surface temperature data based on a Kalman filtering algorithm, obtaining fusion temperature at the k moment based on Kalman gain weighted combination, namely an optimal target temperature value, and performing temperature adjustment on the thermal therapy execution module according to the optimal target temperature value to realize accurate closed-loop temperature control.
6. The control system of a multi-modal feedback-based intelligent shoulder-neck-crotch hyperthermia device according to claim 1, characterized in that the specific process of outputting the only effective execution instruction is as follows: S301, acquiring a thermal therapy operation instruction and user operation instructions from different channels, and generating corresponding instruction labels according to instruction contents, wherein the instruction labels comprise a highest priority P1, a user safety rejection P2, a doctor professional instruction P3 and a user comfort request P4; The thermal therapy operation instruction is generated by the temperature parameter generation module, and is audited, confirmed or modified by a doctor end and then issued, and the content of the thermal therapy operation instruction is a professional adjustment level; S302, presetting a safety priority rule, wherein the safety priority rule is used for defining direct processing sequences of different instruction labels, and specifically: the highest priority P1 is a system-level emergency stop, and the triggering condition of the system-level emergency stop is that a physical emergency stop button and hardware over-temperature protection signals sent by other modules; the arbitration logic is immediate execution, i.e., the highest priority instruction unconditionally denies any other instructions being executed or waiting to be executed; The user safety overrule P2 has the triggering condition that the overrule instruction initiated by the user is issued; The arbitration logic is executed immediately, so that the immediate safety and the comfortable body feeling priority of the user are ensured; The doctor specialized instruction P3 is that the triggering condition is that the AI generates and takes the heat treatment confirmed by the doctor as the instruction; Arbitration logic is executed as a base protocol for hyperthermia, defining a baseline and upper safety limit for a course of treatment; The user comfort request P4 is triggered by a comfort request instruction initiated by a user; The arbitration logic is constrained execution, compares the constraint execution with the safety upper limit set by the doctor specialized instruction P3 instruction, and gives way to the doctor specialized instruction; s303, carrying out conflict detection based on an event triggering and time window arbitration mechanism, wherein the instant conflict comprises instant conflict and state conflict, wherein the instant conflict is that two or more instructions which come from different sources and have the same target parameters are received in a preset time window, and the state conflict is that the received instructions are in conflict with the safety upper limit set by the professional instructions of a doctor; s304, generating a winning instruction in each preset arbitration period after the arbitration logic, wherein the winning instruction is formatted into a standardized instruction set which can be understood by the cooperative control module, namely a unique effective execution instruction.

Description

Control system of intelligent shoulder-neck crotch thermal therapy equipment based on multi-mode feedback Technical Field The invention relates to the technical field of medical appliances, in particular to a control system of intelligent shoulder, neck and crotch thermotherapy equipment based on multi-mode feedback. Background In recent years, with the improvement of health consciousness of people, intelligent thermal therapeutic equipment for relieving muscle fatigue and soreness of the neck, shoulder, waist and crotch and the like has been widely used. The existing thermal therapy equipment usually integrates a plurality of functional modules such as heating, massaging, body position adjusting and the like. Short wave (frequency 3-30 MHz) and ultrashort wave (frequency 30-300 MHz) hyperthermia are key technologies for realizing deep tissue heating, and the core principle is that the electromagnetic waves penetrate through tissues to enable internal ions and polar molecules to vibrate and rub at high speed, heat is directly generated in the deep parts of the tissues, the traditional shoulder hyperthermia has limitations in depth, control precision and regional partition, the short wave and ultrashort wave provide stronger deep heat and regional control capability, and more uniform and safe individuation treatment can be realized by combining closed loop temperature control; however, the control system of the thermal therapeutic apparatus in the prior art still has a plurality of technical defects in practical application: 1. The existing control system generally performs independent control or simple linkage on each module, lacks intelligent cooperative strategies under changeable user states and environments, for example, when a user adjusts the gesture, each heating module cannot adaptively adjust the output power and the hot compress area in real time, so that the thermal therapy effect is poor; 2. The traditional equipment adopts single-point contact type temperature sensors or relies on preset heating curves, so that the real temperature distribution of the body surface of a user and the surface of the equipment is difficult to accurately reflect, and the problems of local overheating or insufficient heating are easily caused; 3. The motion safety and positioning detection are unreliable, namely, some devices lack effective detection on the sitting state, the gesture and the abnormal motion of a user, when the user performs a large-amplitude motion or leaves on the device, if the system fails to respond in time, energy waste can be caused, and even the device continues to heat or operate during the abnormal motion, so that potential safety hazards are brought; 4. The operation experience and conflict processing are insufficient, modern equipment often supports a plurality of operation modes such as a touch screen, voice, a remote controller and the like, when a plurality of instructions are simultaneously generated, the existing system lacks clear operation arbitration logic, operation conflict and system response confusion are easy to cause, and the user experience and safety are reduced; In view of the technical drawbacks described above, solutions are now proposed. Disclosure of Invention The invention aims to automatically generate an adaptive heat treatment scheme according to physiological data of a user and heat treatment rehabilitation treatment courses, assist doctors to carry out heat treatment operation, further integrate multi-mode feedback through a cooperative control module, realize intelligent linkage and self-adaptive adjustment of a plurality of heat treatment modules such as shoulders, necks and crotch, and remarkably improve the pertinence and comfort level of heat treatment. In order to achieve the aim, the control system of the intelligent shoulder, neck and crotch thermotherapy equipment based on multi-mode feedback comprises a multi-mode sensing module, a central processing unit, a thermotherapy execution module and a doctor end, wherein: the multi-mode sensing module is used for acquiring multi-point temperature feedback signals, historical thermal therapy data and real-time physiological data of a user and user operation instruction signals in real time and sending the signals to the central processing unit; the central processing unit is electrically connected to the multi-mode sensing module and is configured to run a plurality of functional logic modules; the functional logic module operated by the central processing unit comprises a temperature parameter generating module, a multipoint fusion temperature monitoring module, an operation arbitration module and a cooperative control module, wherein: The temperature parameter generation module is used for acquiring historical heat treatment data and real-time physiological data of a user, constructing a scheme generation model based on a deep learning algorithm, generating a current heat treatment scheme by combining the his