Intelligent adjusting method and equipment for rehabilitation treatment equipment

Abstract

The invention discloses an intelligent adjustment method of rehabilitation treatment equipment and the equipment. The method comprises the following steps: S1, connecting an auxiliary diagnosis system, collecting clinical diagnosis and treatment data, preprocessing the clinical diagnosis and treatment data, extracting key features from the preprocessed data, and identifying the symptom type and rehabilitation training type of a patient; s2, according to the recognition result of the rehabilitation training type of the patient, a treatment instruction suitable for the current stage of the patient is generated and sent; s3, the treatment instruction is received and executed, auxiliary treatment measures are provided for patients in different treatment stages according to the treatment instruction, and the patients are guided to conduct rehabilitation training; s4, creating an electronic file for each patient, and collecting and storing rehabilitation treatment training progress data of the patient from various sensors; and S5, providing an API (Application Program Interface), allowing remote medical professionals to access and monitor rehabilitation treatment training progress data in the rehabilitation treatment training process of the patient through a user interface, and providing treatment suggestions for the patient.

Description

Technical Field

[0001] The present invention belongs to the technical field of rehabilitation therapy, and specifically refers to an intelligent adjustment method and device for rehabilitation therapy equipment. Background Art

[0002] With the continuous improvement of people's living standards, people pay more and more attention to their physical and mental health. When dealing with symptoms such as sprained feet, muscle strain and recovery after stroke, some existing rehabilitation treatment methods face some significant limitations. In order to meet the urgent needs of the general public, it is imperative to design an intelligent adjustment rehabilitation treatment device with powerful functions, advanced equipment and thoughtful services. The service models of some existing rehabilitation treatment methods may not be flexible and comprehensive enough to meet the specific symptoms and rehabilitation needs of patients, generate personalized treatment instructions and provide sufficient rehabilitation training measures for auxiliary rehabilitation. Some traditional rehabilitation treatment equipment cannot dynamically adjust the rehabilitation training plan for auxiliary rehabilitation according to the changes in the patient's treatment stage, which limits the optimization of the treatment effect. Summary of the invention

[0003] In order to solve the above problems in the prior art, the technical solution adopted by the present invention is as follows:

[0004] An intelligent adjustment method for rehabilitation treatment equipment comprises the following steps:

[0005] S1: Connect to the auxiliary diagnosis system, collect clinical diagnosis and treatment data, pre-process the clinical diagnosis and treatment data, extract key features from the pre-processed data, identify the patient's symptom type and rehabilitation training type, thereby significantly improving the personalization and treatment effect of rehabilitation treatment, and bringing substantial benefits to the patient's rehabilitation process;

[0006] S2: Generate and send treatment instructions suitable for the patient's current stage based on the identification results of the patient's rehabilitation training type. By accurately identifying the rehabilitation training type and generating appropriate treatment instructions, the effect and efficiency of treatment are improved;

[0007] S3: receiving and executing the treatment instruction, providing auxiliary treatment measures for patients at different treatment stages according to the treatment instruction, and guiding the patients to perform rehabilitation training. The personalized guidance can better meet the rehabilitation needs of the patients and improve the effect and efficiency of rehabilitation training;

[0008] S4: The patient file management module creates an electronic file for each patient, collects and stores the patient's rehabilitation training progress data from various sensors. The data accumulation helps to evaluate the durability and long-term effectiveness of the treatment effect, and provides valuable reference and basis for future rehabilitation management;

[0009] S5: The remote monitoring module is used to provide an API interface, allowing remote medical professionals to access and monitor the rehabilitation training progress data of patients during rehabilitation training through the user interface, and provide treatment suggestions to patients. Remote monitoring reduces the geographical distance between patients and doctors. Medical professionals can access patients' data anytime and anywhere without real-time face-to-face contact, thereby saving time and cost in the treatment process, which is particularly important for patients who require long-term monitoring.

[0010] Furthermore, the step S1 comprises:

[0011] S1-1: Preprocess the clinical diagnosis and treatment data, and extract key features from the preprocessed data. The key features include physiological index features, activity ability features, pain assessment features, motor function features, neurological function features, psychological state features, and biomechanical features. Comprehensive analysis of these features can tailor a personalized treatment plan for each patient;

[0012] S1-2: Find the activity ability characteristics, motor function characteristics and neurological function characteristics in the clinical diagnosis and treatment data according to the preset Fourier transform algorithm, and identify the patient's symptom type according to the activity ability characteristics, motor function characteristics and neurological function characteristics, wherein the symptom type includes leg sprain, muscle strain and post-stroke recovery treatment. The algorithm can quickly process and analyze a large amount of data, shorten the time from data collection to symptom identification, and improve the efficiency of the diagnosis process;

[0013] S1-3: A portion of clinical diagnosis and treatment data is labeled as training data set and validation data set according to the built-in rehabilitation training classification standard. By using standardized rehabilitation training classification standards, the accuracy of model recognition and classification of different rehabilitation needs can be improved;

[0014] S1-4: training the model with the extracted key features and the labeled clinical diagnosis and treatment data, thereby obtaining a rehabilitation training type recognition model capable of identifying the type of rehabilitation training required by the patient;

[0015] S1-5: The patient's symptom type is input into the trained rehabilitation training type recognition model for real-time rehabilitation training type recognition. Based on the output of the model, the rehabilitation training type information required by the patient is determined, and the rehabilitation training type information includes leg sprain rehabilitation training, muscle strain rehabilitation training and post-stroke recovery treatment rehabilitation training. The most appropriate rehabilitation training plan is accurately matched according to the symptom type to improve rehabilitation efficiency and effectiveness.

[0016] Furthermore, the step S2 comprises:

[0017] S2-1: Generate and send treatment instructions for adjusting the lifting height of the lifting platform, adjusting the water temperature of the hydrotherapy pool, adjusting the water flow parameters of the booster, and voice guiding swimming training based on the identification result of the patient who needs leg sprain rehabilitation training;

[0018] S2-2: generating and sending treatment instructions for the lifting height of the lifting platform, adjusting the water temperature of the hydrotherapy pool, and voice-guided gait training according to the identification result of the patient who needs post-stroke rehabilitation treatment and rehabilitation training;

[0019] S2-3: Based on the identification results of the patients who need to undergo muscle strain rehabilitation training, generate and send treatment instructions for adjusting the lifting height of the lifting platform, adjusting the water temperature of the hydrotherapy pool, and voice-guiding the patients to perform underwater sports training, so as to accelerate the patients' rehabilitation process through customized and multi-modal rehabilitation training.

[0020] Furthermore, the step S3 comprises:

[0021] S3-1: According to the treatment instructions, the hydraulic lifting rod is controlled to adjust the lifting height of the lifting platform to adapt to patients of different heights. The same device can meet the various treatment needs of patients of different heights, which increases the flexibility and practicality of the device;

[0022] S3-2: The water temperature of the hydrotherapy pool is adjusted according to treatment instructions to adapt to different treatment needs and patient comfort. The warm water temperature helps relax muscles and reduce muscle tension and pain, especially in the rehabilitation of muscle strain and leg sprain;

[0023] S3-3: According to the treatment instruction, the working parameters of the booster are set to control the speed and direction of the water flow output by the water pump, so as to adjust the resistance of the patient swimming in the water, help the patient to carry out targeted rehabilitation training, and help the patient improve the perception of body position and movement through the touch of the water flow, which is conducive to the recovery of movement control and coordination;

[0024] S3-4: According to the treatment instructions, the patient selects the swimming training movements for the current rehabilitation stage, controls the voice device to provide voice guidance, and guides the user to perform swimming training. The swimming training movements include basic kicking, paddling and breathing techniques, and guides the user to adjust the swimming rhythm. According to the patient's specific rehabilitation stage and needs, personalized swimming training movements are provided to improve the pertinence and effectiveness of the training;

[0025] S3-5: According to the patient's rehabilitation training stage and treatment instructions, collect and analyze the patient's gait data on the treadmill, control the voice device to provide language feedback to help the patient adjust his gait, the gait data includes the step length, pace, gait cycle and treadmill contact pattern during walking, and help the patient improve movement coordination and balance through gait training and voice guidance;

[0026] S3-6: According to the patient's rehabilitation training stage and treatment instructions, voice prompts the patient to correct abnormal underwater exercise training patterns, guide the patient to complete underwater exercise training, conduct underwater exercise training in a hydrotherapy environment, use the buoyancy of water to reduce the pressure of body weight on muscles, and exercise muscles at the same time, help patients relieve pain and promote blood circulation, accelerate recovery after stroke treatment, and voice guidance helps patients exercise muscles evenly and restore muscle imbalances and joint problems.

[0027] Furthermore, the step S3-1 includes:

[0028] S3-1-1: Collect the patient's height data detected by the infrared sensor, and control the motor to drive the hydraulic lifting rod to lift the lifting platform to a specified position according to the patient's height data, so as to ensure that the lifting platform is adjusted to a suitable height according to the patient's precise height, thereby improving the adaptability of rehabilitation training;

[0029] S3-1-2: adjusting the motor operating parameters according to the patient's weight data, the motor operating parameters including speed, acceleration and force, ensuring that the lifting platform moves smoothly during the ascent and descent process, reducing vibration and impact, and automatically adjusting the motor parameters according to the patient's weight to ensure that the lifting platform can adapt to patients of different weights;

[0030] S3-1-3: After the lifting platform reaches the desired height, the locking mechanism is controlled to lock the lifting platform to prevent accidental sliding or movement. The locking mechanism allows the platform to adapt to different treatment needs, such as standing training, water exercise, etc.

[0031] Furthermore, the step S3-2 includes:

[0032] S3-2-1: Real-time acquisition of water temperature data of the spa pool detected by the temperature sensor, allowing rapid response to water temperature changes and timely adjustment of the heating or cooling system to maintain an ideal water temperature;

[0033] S3-2-2: According to the patient's rehabilitation training stage and treatment instructions, control the operation of the heating and cooling system and adjust the water temperature of the hydrotherapy pool in real time. For patients with muscle strain and leg sprain, warmer water temperature is required to promote blood circulation and muscle relaxation, while for recovery after stroke, the water temperature needs to be moderate.

[0034] Further, the step S3-3 includes:

[0035] S3-3-1: According to the treatment data analysis results, adjust the working parameters of the booster, including water flow intensity and water flow pattern, and adjust the water flow intensity and pattern to adapt to the patient's training stage and physical fitness level to ensure the suitability of the training;

[0036] S3-3-2: setting a water flow mode of the booster, wherein the water flow mode includes pulse, continuous and intermittent water flow. Appropriate water flow stimulation can help improve muscle reaction ability and coordination, especially for the rehabilitation of muscle strain and leg sprain;

[0037] S3-3-3: Control the booster to generate water flow to provide necessary power for hydrotherapy;

[0038] S3-3-4: According to treatment needs, the output power of the water outlet pump is adjusted to adjust the intensity of the water flow.

[0039] Furthermore, the step S3-6 includes:

[0040] S3-6-1: acquiring the patient's motion data within a preset time period from various monitoring sensors integrated in the rehabilitation treatment equipment, and preprocessing the acquired motion data, wherein the sensors are used to monitor the patient's rehabilitation treatment underwater motion training data;

[0041] S3-6-2: Obtain muscle rehabilitation exercise data stored in the clinical standard exercise training model database to ensure that the collected exercise data is accurate and provide reliable raw data for subsequent analysis;

[0042] S3-6-3: Matching the patient's rehabilitation therapy exercise training data with the muscle rehabilitation therapy exercise data in the exercise pattern database to identify standard and abnormal exercise patterns;

[0043] S3-6-4: Extract key features from patient rehabilitation exercise training data, including joint angle, velocity, acceleration and range of motion;

[0044] S3-6-5: Convert the extracted features into vector form for comparison with patterns in the motion pattern database;

[0045] S3-6-6: Calculate the similarity between the patient's motion feature vector and the pattern in the motion pattern database using the cosine similarity algorithm;

[0046] S3-6-7: Apply a preset classification algorithm to identify the exercise training pattern that matches the patient, identify the exercise training pattern that is significantly different from the pattern in the standard pattern library, and indicate it as irregular exercise training. After identifying the abnormal exercise pattern, feedback can be provided immediately to remind the patient to adjust the exercise training pattern to ensure the correctness of the rehabilitation training;

[0047] S3-6-8: Control the voice device to guide the patient to correct abnormal movement training patterns.

[0048] Furthermore, the step S5 comprises:

[0049] S5-1: Provide a secure API interface to allow remote medical professionals to monitor rehabilitation training progress data through the user interface. The data is obtained during the rehabilitation training process assisted by the rehabilitation equipment;

[0050] S5-2: Allow medical professionals to perform remote diagnosis based on monitoring data and provide treatment recommendations to patients through a user interface. Through remote monitoring, medical resources can be more efficiently allocated to patients who need immediate attention.

[0051] Furthermore, a rehabilitation therapy device executes the above-mentioned intelligent adjustment method of a rehabilitation therapy device.

[0052] The beneficial effects of the intelligent adjustment method and device of a rehabilitation therapy device of the present invention are as follows: the intelligent rehabilitation therapy device can collect clinical diagnosis and treatment data in real time by connecting to an auxiliary diagnosis system, and perform preprocessing and feature extraction, so as to accurately identify the patient's symptom type and suitable rehabilitation training type; and generate personalized treatment instructions according to the patient's specific symptoms and rehabilitation needs, and has the ability to dynamically adjust according to changes in the patient's treatment stage. The intelligent rehabilitation therapy device allows remote medical professionals to access the patient's rehabilitation therapy training progress data and provide timely treatment suggestions for the patient. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A schematic diagram of a flow chart of an intelligent adjustment method of a rehabilitation treatment device according to the present invention;

[0054] Figure 2 A schematic diagram of the system structure of an intelligent adjustment method for rehabilitation treatment equipment according to the present invention;

[0055] Figure 3 A schematic diagram of the system structure of a lifting platform control submodule of an intelligent adjustment method for rehabilitation treatment equipment of the present invention;

[0056] Figure 4 A schematic diagram of the system structure of a hydrotherapy pool temperature regulating submodule of an intelligent regulating method for rehabilitation therapy equipment of the present invention;

[0057] Figure 5 A schematic diagram of the system structure of a water flow regulating submodule of an intelligent regulating method for rehabilitation treatment equipment according to the present invention;

[0058] Figure 6 A schematic diagram of the system structure of an underwater sports training guidance submodule of an intelligent adjustment method for a rehabilitation treatment device according to the present invention;

[0059] Figure 7 The figure is a schematic diagram of the three-dimensional structure of a rehabilitation treatment device of the present invention.

[0060] Among them, 1-communication interface module, 11-feature extraction submodule, 12-symptom type recognition module, 13-data set division module, 14-model training module, 15-rehabilitation training type recognition module, 2-treatment instruction sending module, 3-instruction execution module, 31-lifting platform control submodule, 32-spa temperature adjustment submodule, 33-water flow adjustment submodule, 34-swimming training guidance submodule, 35-gait analysis and adjustment submodule, 36-underwater sports training guidance submodule, 4-patient file management module, 5-remote monitoring module, 51-interface submodule, 52-remote advice and diagnosis and treatment submodule, 21 lifting platform, 22-spa, 23-booster, 37-hydraulic lifting rod, 38-treadmill, 39-motor. DETAILED DESCRIPTION

[0061] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] like Figure 1-7As shown, the present invention is an intelligent adjustment method for rehabilitation treatment equipment, including a communication interface module 1, a treatment instruction sending module 2, an instruction execution module 3, a patient file management module 4 and a remote monitoring module 5, wherein the input end of the treatment instruction sending module 2 is connected to the output end of the communication interface module 1, the input end of the instruction execution module 3 is connected to the output end of the communication interface module 1 and the treatment instruction sending module 2, the input end of the patient file management module 4 is connected to the output end of the instruction execution module 3, and the input end of the remote monitoring module 5 is connected to the output end of the patient file management module 4, comprising the following steps: S1: the communication interface module 1 is used to connect to the auxiliary diagnosis system, collect clinical diagnosis and treatment data, pre-process the clinical diagnosis and treatment data, extract key features from the pre-processed data, identify the patient's symptom type and rehabilitation training type, thereby significantly improving the personalization of rehabilitation treatment and the treatment effect, and bringing substantial benefits to the patient's rehabilitation process; S2: the treatment instruction sending module 2 is based on the identification of the patient's rehabilitation training type. The result is identified, and treatment instructions suitable for the patient's current stage are generated and sent, and the patient is monitored and treated. By accurately identifying the type of rehabilitation training and generating appropriate treatment instructions, the effect and efficiency of the treatment are improved; S3: The instruction execution module 3 is used to receive and execute the treatment instructions, provide auxiliary treatment measures for patients at different treatment stages according to the treatment instructions, and guide the patient to conduct rehabilitation training. The personalized guidance can better meet the patient's rehabilitation needs and improve the effect and efficiency of rehabilitation training; S4: The patient file management module 4 creates an electronic file for each patient, collects and stores the patient's rehabilitation training progress data from various sensors, and the data accumulation helps to evaluate the persistence and long-term effectiveness of the treatment effect, and provides valuable reference and basis for future rehabilitation management; S5: The remote monitoring module 5 is used to provide an API interface, allowing remote medical professionals to access the rehabilitation training progress data of the patient's rehabilitation training process through the user interface, provide treatment advice to the patient, and remote monitoring reduces the geographical distance limit between the patient and the doctor. Medical professionals can access the patient's data anytime and anywhere without real-time face-to-face contact, thereby saving time and cost in the treatment process, which is particularly important for patients who need long-term monitoring.

[0063] The communication interface module 1 includes a feature extraction submodule 11, a symptom type identification module 12, a data set division module 13, a model training module 14 and a rehabilitation training type identification module 15, and the step S1 includes: S1-1: the feature extraction submodule 11 is used to pre-process the clinical diagnosis and treatment data, and extract key features from the pre-processed data. The key features include physiological indicator features, activity features, pain assessment features, motor function features, neurological function features, psychological state features and biomechanical features. The comprehensive analysis of these features can tailor a personalized treatment plan for each patient; S1-2: the symptom type identification module 12 searches for activity features, motor function features and neurological function features in the clinical diagnosis and treatment data according to a preset Fourier transform algorithm, and identifies the patient's symptom type according to the activity features, motor function features and neurological function features. The symptom types include leg sprains, muscle strains and post-stroke recovery treatment. The algorithm quickly processes and analyzes a large amount of data, shortening the time from data collection. The time of symptom recognition is shortened, which improves the efficiency of the diagnosis process; S1-3: the data set division module 13 marks a part of the clinical diagnosis and treatment data as a training data set and a verification data set according to the built-in rehabilitation training classification standard. By using the standardized rehabilitation training classification standard, the accuracy of model recognition and classification of different rehabilitation needs can be improved; S1-4: the model training module 14 trains the model with the key features extracted by the feature extraction submodule and the labeled clinical diagnosis and treatment data, so as to obtain a rehabilitation training type recognition model that can identify the type of rehabilitation training required by the patient; S1-5: the rehabilitation training type recognition module 15 inputs the patient's symptom type into the trained rehabilitation training type recognition model for real-time rehabilitation training type recognition, and determines the rehabilitation training type information required by the patient according to the output of the model, the rehabilitation training type information includes leg sprain rehabilitation training, muscle strain rehabilitation training and post-stroke recovery treatment rehabilitation training, and accurately matches the most suitable rehabilitation training plan according to the symptom type to improve rehabilitation efficiency and effect.

[0064] The step S2 includes: S2-1: based on the identification results of patients who need to undergo rehabilitation training for leg sprains, generating and sending treatment instructions for adjusting the lifting height of the lifting platform 21, adjusting the water temperature of the hydrotherapy pool 22, adjusting the water flow parameters of the booster 23, and voice guiding swimming training; S2-2: based on the identification results of patients who need post-stroke recovery treatment and rehabilitation training, generating and sending treatment instructions for the lifting height of the lifting platform 21, adjusting the water temperature of the hydrotherapy pool 22, and voice guiding gait training; S2-3: based on the identification results of patients who need to undergo rehabilitation training for muscle strains, generating and sending treatment instructions for the lifting height of the lifting platform 21, adjusting the water temperature of the hydrotherapy pool 22, and voice guiding patients to perform underwater sports training, thereby accelerating the patient's rehabilitation process through customized and multi-modal rehabilitation training.

[0065] The instruction execution module 3 includes a lifting platform control submodule 31, a hydrotherapy pool temperature adjustment submodule 32, a water flow adjustment submodule 33, a swimming training guidance submodule 34, a gait analysis and adjustment submodule 35 and an underwater sports training guidance submodule 36. The step S3 includes: S3-1: the lifting platform control submodule 31 is used to control the hydraulic lifting rod 37 to adjust the lifting height of the lifting platform 21 according to the treatment instruction to adapt to patients of different heights. The same device can adapt to the various treatment needs of patients of different heights, which increases the flexibility and practicality of the device and ensures that patients can safely and conveniently enter and leave the hydrotherapy pool 22; S3-2: the hydrotherapy pool temperature adjustment Submodule 32 is used to adjust the water temperature of the hydrotherapy pool 22 according to the treatment instructions to adapt to different treatment needs and patient comfort. The warm water temperature helps to relax muscles, reduce muscle tension and pain, especially in the rehabilitation of muscle strain and leg sprain; S3-3: The water flow adjustment submodule 33 is used to set the speed and direction of the water flow output by the water outlet pump controlled by the working parameters of the booster 23 according to the treatment instructions, adjust the resistance of the patient's swimming in the water, help the patient to carry out targeted rehabilitation training, assist the patient to complete swimming rehabilitation training, so as to adapt to the motor ability and rehabilitation stage of different patients, provide personalized swimming training movements according to the patient's specific rehabilitation stage and needs, and improve the targeted training. The swimming training guidance submodule 34 is used to select the swimming training movements of the patient's current rehabilitation stage according to the treatment instructions, control the voice device to provide voice guidance, and guide the user to perform swimming training. The swimming training movements include basic kicking, paddling and breathing techniques, and guide the user to adjust the swimming rhythm. According to the patient's specific rehabilitation stage and needs, personalized swimming training movements are provided to improve the pertinence and effect of the training; S3-5: The gait analysis and adjustment submodule 35 is used to collect and analyze the patient's gait data on the treadmill 38 according to the patient's rehabilitation training stage and treatment instructions, and control the voice device to provide language feedback to help the patient adjust his gait. The gait data include stride length, stride speed, gait cycle and treadmill contact pattern during walking, and help patients improve movement coordination and balance through gait training and voice guidance; S3-6: The underwater sports training guidance submodule 36 is used to voice prompt the patient to correct abnormal underwater sports training patterns according to the patient's rehabilitation training stage and treatment instructions, guide the patient to complete underwater sports training, conduct underwater sports training in a hydrotherapy environment, use the buoyancy of water to reduce the pressure of body weight on muscles, and exercise muscles at the same time, help patients relieve pain and promote blood circulation, accelerate recovery after stroke treatment, and voice guidance helps patients exercise muscles evenly and restore muscle imbalance and joint problems.

[0066] The lifting platform control submodule 31 includes an automatic height detection unit 311, a smooth motion control unit 312 and a safety locking mechanism unit 313. The step S3-1 includes: S3-1-1: The automatic height detection unit 311 is used to collect the patient's height data detected by the infrared sensor, and control the motor 39 to drive the hydraulic lifting rod 37 to lift the lifting platform 21 to a specified position according to the patient's height data, so as to ensure that the lifting platform is adjusted to a suitable height according to the patient's precise height, thereby improving the adaptability of rehabilitation therapy training; S3-1-2: The smooth motion control unit 312 is used to adjust the operating parameters of the motor 39 according to the patient's weight data. The operating parameters of the motor 39 include speed, acceleration and force, so as to ensure that the lifting platform 21 moves smoothly during the ascent and descent process, reduce vibration and impact, and automatically adjust the motor parameters according to the patient's weight to ensure that the lifting platform is suitable for patients of different weights; S3-1-3: The safety locking mechanism unit 313 is used to control the locking mechanism to lock the lifting platform 21 after the lifting platform 21 reaches the required height to prevent accidental sliding or movement. The locking mechanism allows the platform to adapt to different treatment needs, such as standing training, water exercise, etc.

[0067] The hydrotherapy pool temperature adjustment submodule 32 includes a temperature sensor unit 321 and a temperature adjustment unit 322, and the step S3-2 includes: S3-2-1: the temperature sensor unit 321 is used to obtain the water temperature data of the hydrotherapy pool 22 detected by the temperature sensor in real time, allowing a rapid response to water temperature changes, and timely adjustment of the heating or cooling system to maintain an ideal water temperature; S3-2-2: the temperature adjustment unit 322 is used to control the operation of the heating and cooling systems according to the patient's rehabilitation training stage and treatment instructions, and adjust the real-time water temperature of the hydrotherapy pool 22 to provide rehabilitation hydrotherapy with accurate and uniform water temperature that meets the treatment needs of different patients. For patients with muscle strain and leg sprains, warmer water temperature is required to promote blood circulation and muscle relaxation, while for recovery after a stroke, the water temperature needs to be moderate to balance comfort and treatment effect, and improve the treatment effect and patient comfort.

[0068] The water flow regulating submodule 33 includes a water flow intensity regulating unit 331, a water flow mode selecting unit 332, a water pump control unit 333 and a valve regulating unit 334. The step S3-3 includes: S3-3-1: the water flow intensity regulating unit 331 is used to adjust the working parameters of the booster 23, including the water flow intensity and the water flow mode, according to the treatment data analysis results, and adjust the water flow intensity and mode to adapt to the patient's training stage and physical fitness level to ensure the suitability of the training; S3-3-2: the water flow mode selecting unit 332 is used to set the water flow mode of the booster 23, and the water flow mode includes pulse, continuous and intermittent water flow. Appropriate water flow stimulation can help improve muscle reaction ability and coordination, especially for the rehabilitation of muscle strain and leg sprain; S3-3-3: The water pump control unit 333 is used to control the booster 23 to generate water flow and provide necessary power for hydrotherapy; S3-3-4: The valve adjustment unit 334 is used to adjust the output power of the water outlet pump according to treatment needs, thereby adjusting the intensity of the water flow.

[0069] The underwater sports training guidance submodule 36 includes an underwater sports training data monitoring unit 361, a motion pattern library unit 362, a pattern matching unit 363, a feature extraction unit 364, a feature vectorization unit 365, a similarity calculation unit 366, a pattern recognition unit 367 and a motion pattern guidance unit 368. The step S3-6 includes: S3-6-1: The underwater sports training data monitoring unit 361 obtains the patient's motion data within a preset time period from various monitoring sensors integrated in the rehabilitation treatment equipment, and pre-processes the acquired motion data. The sensor is used to monitor the patient's rehabilitation treatment underwater sports training data; S3-6-2: The motion pattern library unit 362 is used to obtain and store the muscle rehabilitation treatment motion data in the clinical standard motion training pattern database to ensure that the collected motion data is accurate and provide reliable original data for subsequent analysis; S3-6-3: The pattern matching unit 363 is used to match the patient's rehabilitation treatment motion training data with the muscle rehabilitation treatment motion data in the motion pattern database. to identify standard and abnormal movement patterns; S3-6-4: the feature extraction unit 364 is used to extract key features from the patient's rehabilitation therapy movement training data, and the key features include joint angles, speeds, accelerations and movement amplitudes; S3-6-5: the feature vectorization unit 365 is used to convert the extracted features into vector form for comparison with the patterns in the movement pattern database; S3-6-6: the similarity calculation unit 366 uses the cosine similarity algorithm to calculate the similarity between the patient's movement feature vector and the pattern in the movement pattern database; S3-6-7: the pattern recognition unit 367 applies a preset classification algorithm to identify the movement training pattern that matches the patient, identifies the movement training pattern that is significantly different from the pattern in the standard pattern library, and indicates it as non-standard movement training. After identifying the abnormal movement pattern, feedback can be provided immediately and the patient can be reminded to adjust the movement training pattern to ensure the correctness of the rehabilitation training; S3-6-8: the movement pattern guidance unit 368 is used to control the voice device to guide the patient to correct the abnormal movement training pattern.

[0070] The remote monitoring module 5 includes an interface submodule 51 and a remote diagnosis and suggestion submodule 52, and the step S5 includes: S5-1: the interface submodule 51 is used to provide a secure API interface, providing a secure API interface, allowing remote medical professionals to monitor rehabilitation training progress data through a user interface, and the data is obtained during the rehabilitation training process of patients assisted by rehabilitation equipment; S5-2: the remote diagnosis and suggestion submodule 52 is used to allow medical professionals to perform remote diagnosis based on monitoring data, and provide treatment suggestions to patients through the user interface. Through remote monitoring, medical resources can be more effectively allocated to patients who need immediate attention.

[0071] A rehabilitation treatment device executes the above-mentioned intelligent adjustment method for rehabilitation treatment device.

[0072] The beneficial effects of the intelligent adjustment method and device of a rehabilitation therapy device of the present invention are as follows: the intelligent rehabilitation therapy device can collect clinical diagnosis and treatment data in real time by connecting to an auxiliary diagnosis system, and perform preprocessing and feature extraction, so as to accurately identify the patient's symptom type and suitable rehabilitation training type; and generate personalized treatment instructions according to the patient's specific symptoms and rehabilitation needs, and has the ability to dynamically adjust according to changes in the patient's treatment stage. The intelligent rehabilitation therapy device allows remote medical professionals to access the patient's rehabilitation therapy training progress data and provide timely treatment suggestions for the patient.

[0073] The present invention and its embodiments are described above, which is not restrictive. What is shown in the accompanying drawings is only one of the embodiments of the present invention, and the actual content is not limited to this. In short, if ordinary technicians in this field are inspired by it and do not deviate from the purpose of the invention, they can creatively design structural methods and embodiments similar to the technical scheme, which should all fall within the scope of protection of the present invention.

Claims

1. An intelligent adjustment method for rehabilitation treatment equipment, characterized in that: The following steps are involved: S1: Connect to the auxiliary diagnosis system, collect clinical diagnosis and treatment data, pre-process the clinical diagnosis and treatment data, extract key features from the pre-processed data, and identify the patient's symptom type and rehabilitation training type; S2: Generate and send treatment instructions suitable for the patient's current stage based on the identification result of the patient's rehabilitation training type; S3: receiving and executing the treatment instruction, providing auxiliary treatment measures for patients at different treatment stages according to the treatment instruction, and guiding the patients to perform rehabilitation training; S4: Create an electronic file for each patient, collect and store the patient's rehabilitation training progress data from various sensors; S5: Provide an API interface to allow remote medical professionals to access the rehabilitation training progress data of patients during rehabilitation training through the user interface and provide treatment recommendations to patients.

2. The intelligent adjustment method of a rehabilitation treatment device according to claim 1, characterized in that: The step S1 comprises: S1-1: Preprocess the clinical diagnosis and treatment data, and extract key features from the preprocessed data, wherein the key features include physiological index features, activity ability features, pain assessment features, motor function features, neurological function features, psychological state features, and biomechanical features; S1-2: searching for activity characteristics, motor function characteristics and nerve function characteristics in the clinical diagnosis and treatment data according to a preset Fourier transform algorithm, and identifying the patient's symptom type according to the activity characteristics, motor function characteristics and nerve function characteristics, wherein the symptom type includes leg sprain, muscle strain and post-stroke recovery treatment; S1-3: Label a portion of clinical diagnosis and treatment data as training data set and validation data set according to the built-in rehabilitation training classification standard; S1-4: training the model with the extracted key features and the labeled clinical diagnosis and treatment data, thereby obtaining a rehabilitation training type recognition model capable of identifying the type of rehabilitation training required by the patient; S1-5: Input the patient's symptom type into the trained rehabilitation training type recognition model for real-time rehabilitation training type recognition, and determine the rehabilitation training type information required by the patient based on the output of the model. The rehabilitation training type information includes leg sprain rehabilitation training, muscle strain rehabilitation training and post-stroke recovery treatment rehabilitation training.

3. The intelligent adjustment method of a rehabilitation treatment device according to claim 2, characterized in that: The step S2 comprises: S2-1: Based on the identification result of the patient who needs to undergo leg sprain rehabilitation training, generating and sending treatment instructions for adjusting the lifting height of the lifting platform (21), adjusting the water temperature of the hydrotherapy pool (22), adjusting the water flow parameters of the booster (23) and voice guiding swimming training; S2-2: generating and sending treatment instructions for the lifting height of the lifting platform (21), adjusting the water temperature of the hydrotherapy pool (22), and voice-guided gait training based on the identification result of the patient who needs post-stroke recovery treatment and rehabilitation training; S2-3: Based on the identification result of the patient who needs to undergo muscle strain rehabilitation training, generate and send treatment instructions for adjusting the lifting height of the lifting platform (21), adjusting the water temperature of the hydrotherapy pool (22), and voice guiding the patient to perform underwater sports training.

4. The intelligent adjustment method of a rehabilitation treatment device according to claim 3, characterized in that: The step S3 comprises: S3-1: controlling the hydraulic lifting rod (37) to adjust the lifting height of the lifting platform (21) according to the treatment instruction to accommodate patients of different heights; S3-2: adjusting the water temperature of the hydrotherapy pool (22) according to the treatment instructions to adapt to different treatment needs and patient comfort; S3-3: according to the treatment instruction, the working parameters of the booster (23) are set to control the speed and direction of the water flow output by the water outlet pump, so as to adjust the resistance of the patient swimming in the water and help the patient to carry out targeted rehabilitation training; S3-4: Select the swimming training movements for the patient's current rehabilitation stage according to the treatment instructions, control the voice device to provide voice guidance, and guide the user to perform swimming training. The swimming training movements include basic kicking, paddling and breathing techniques, and guide the user to adjust the swimming rhythm; S3-5: According to the patient's rehabilitation training stage and treatment instructions, collect and analyze the patient's gait data on the treadmill (38), and control the voice device to provide language feedback to help the patient adjust his gait, wherein the gait data includes step length, step speed, gait cycle and treadmill contact pattern during walking; S3-6: According to the patient's rehabilitation training stage and treatment instructions, voice prompts the patient to correct abnormal underwater exercise training patterns and guide the patient to complete underwater exercise training.

5. The intelligent adjustment method of a rehabilitation treatment device according to claim 4, characterized in that: The step S3-1 comprises: S3-1-1: collecting patient height data detected by the infrared sensor, and controlling the motor (39) to drive the hydraulic lifting rod (37) to lift the lifting platform (21) to a specified position according to the patient height data; S3-1-2: adjusting the operating parameters of the motor (39) according to the patient's weight data, wherein the operating parameters of the motor (39) include speed, acceleration and force, so as to ensure that the lifting platform (21) moves smoothly during the ascent and descent process and reduce vibration and impact; S3-1-3: After the lifting platform (21) reaches a desired height, the locking mechanism is controlled to lock the lifting platform (21) to prevent accidental sliding or movement.

6. The intelligent adjustment method of a rehabilitation treatment device according to claim 4, characterized in that: The step S3-2 comprises: S3-2-1: acquiring water temperature data of the hydrotherapy pool (22) detected by a temperature sensor in real time; S3-2-2: According to the patient's rehabilitation training stage and treatment instructions, the operation of the heating and cooling system is controlled to adjust the water temperature of the hydrotherapy pool (22) in real time. For patients with muscle strain and leg sprain, warmer water temperature is required to promote blood circulation and muscle relaxation, while for recovery after stroke, the water temperature needs to be moderate.

7. The intelligent adjustment method of a rehabilitation treatment device according to claim 4, characterized in that: The step S3-3 comprises: S3-3-1: adjusting the working parameters of the booster (23), including water flow intensity and water flow pattern, according to the treatment data analysis results; S3-3-2: setting a water flow mode of the booster (23) outputting water, wherein the water flow mode includes pulse, continuous and intermittent water flow; S3-3-3: Control the booster (23) to generate water flow to provide necessary power for hydrotherapy; S3-3-4: According to treatment needs, adjust the output power of the water outlet pump to adjust the intensity of the water flow.

8. The intelligent adjustment method of a rehabilitation treatment device according to claim 4, characterized in that: The step S3-6 comprises: S3-6-1: acquiring the patient's motion data within a preset time period from various monitoring sensors integrated in the rehabilitation treatment equipment, and preprocessing the acquired motion data, wherein the sensors are used to monitor the patient's rehabilitation treatment underwater motion training data; S3-6-2: Acquire muscle rehabilitation therapy exercise data stored in a clinical standard exercise training pattern database; S3-6-3: Matching the patient's rehabilitation therapy exercise training data with the muscle rehabilitation therapy exercise data in the exercise pattern database to identify standard and abnormal exercise patterns; S3-6-4: Extract key features from patient rehabilitation exercise training data, including joint angle, velocity, acceleration and range of motion; S3-6-5: Convert the extracted features into vector form for comparison with patterns in the motion pattern database; S3-6-6: Calculate the similarity between the patient's motion feature vector and the pattern in the motion pattern database using the cosine similarity algorithm; S3-6-7: Apply a preset classification algorithm to identify the exercise training pattern that matches the patient, identify the exercise training pattern that is significantly different from the pattern in the standard pattern library, and indicate it as non-standard exercise training; S3-6-8: Control the voice device to guide the patient to correct abnormal exercise training patterns.

9. The intelligent adjustment method of a rehabilitation treatment device according to claim 1, characterized in that: The step S5 comprises: S5-1: Provide a secure API interface to allow remote medical professionals to monitor rehabilitation training progress data through the user interface. The data is obtained during the rehabilitation training process assisted by the rehabilitation equipment; S5-2: Allow medical professionals to perform remote diagnosis based on monitoring data and provide treatment recommendations to patients through a user interface.

10. A rehabilitation treatment device, characterized in that: Execute an intelligent adjustment method for rehabilitation treatment equipment as described in any one of claims 1-9.

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