Hydrotherapy equipment control method and system for rehabilitation treatment and storage device

Abstract

According to the hydrotherapy equipment control method and system for rehabilitation treatment and the storage device, the identity of the user is recognized through the image recognition technology when the user enters the hydrotherapy area, a personalized treatment scheme is formulated according to the archive information and historical treatment data of the user, and after the hydrotherapy equipment is started, the treatment scheme is stored in the hydrotherapy area. The equipment enters a standby state and is initialized according to preset parameters, the personalized treatment capability is enhanced by using the biological feedback sensor so as to accurately monitor the physiological indexes and feedback of the user, and the controller accurately controls operation according to the physiological indexes of the user monitored in real time and the set parameters, so that the user experience is improved. The controller continuously monitors the operation state of the hydrotherapy equipment and the physiological reaction of a user and adjusts the working mode of the underwater equipment at any time so as to respond to the demand change of the user, and when the water flow is abnormal or a patient overflows, the flow sensor can immediately detect and trigger an alarm to remind the user to pay attention to safety in time, and potential risks are effectively prevented.

Description

Technical Field

[0001] The present invention relates to the field of rehabilitation therapy control technology, and more specifically, to a control method, system and storage device of hydrotherapy equipment for rehabilitation therapy. Background Art

[0002] As a rehabilitation treatment method, hydrotherapy has a significant effect on the patient's physical recovery due to its unique physical properties, such as buoyancy, pressure, temperature, etc. It is widely used in the rehabilitation of the musculoskeletal system, nervous system and cardiopulmonary function. Although hydrotherapy is widely used in the field of rehabilitation, existing hydrotherapy equipment has many problems that limit its use efficiency and therapeutic effect.

[0003] Existing hydrotherapy equipment lacks the ability to provide personalized treatment plans based on the specific health conditions and treatment needs of individual users, and also lacks real-time monitoring and feedback of users' physiological indicators and overflow warnings. Summary of the invention

[0004] In order to overcome the defects of the prior art, the present invention designs a control method, system and storage device of hydrotherapy equipment for rehabilitation treatment, which can effectively solve the problems of the prior art.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0006] A method for controlling a hydrotherapy device for rehabilitation treatment comprises the following steps:

[0007] S1. When a user enters the spa area, the user's identity is identified through image recognition technology, and a personalized treatment plan is formulated based on the user's profile information and historical treatment data;

[0008] S2, the user starts the hydrotherapy device, and the hydrotherapy device is initialized and enters a standby state;

[0009] S3, setting the temperature range, cycle time interval, filtration time interval and flow range parameters of the hydrotherapy equipment;

[0010] S4, placing the biofeedback sensor on the user and ensuring that it has good contact;

[0011] S5, the controller controls the operation of the heater, water pump and filter according to the set parameters;

[0012] S6. During the hydrotherapy process, the controller monitors the operating status of the hydrotherapy equipment and the physiological indicators of the user;

[0013] S7, the controller adjusts the operation of the underwater equipment according to the user's needs and changes in physiological indicators;

[0014] S8. When the flow sensor detects that the water flow is too large or the patient is overflowing with water, the controller sounds an alarm to remind the user to pay attention to safety.

[0015] Preferably, the step S1 comprises the following steps:

[0016] S11. When the user enters the spa area, the front image of the user is automatically captured by a high-definition camera;

[0017] S12, preprocessing the captured image, using the face detection algorithm MTCNN to locate the facial area in the preprocessed frontal image;

[0018] S13, extracting key feature points from the detected facial area, including the positions of eyes, nose and mouth;

[0019] S14, using the deep learning model VGGFace to encode the extracted facial region features into a feature value vector;

[0020] S15, matching the encoded feature value vector with the user's facial feature value vector stored in a database to determine the user's identity;

[0021] S16, formulating a personalized hydrotherapy treatment plan based on the identified user identity and the user's profile information and historical treatment data;

[0022] The step S14 further comprises the following steps:

[0023] S14.1. Set up the pre-trained VGGFace model and its weights, and initialize a Keras framework;

[0024] S14.2, prepare a facial region image dataset, and preprocess each facial region image;

[0025] S14.3, input the preprocessed facial region image into the VGGFace model, and obtain the output of the second-to-last fully connected layer as the facial feature representation, wherein the second-to-last fully connected layer contains high-level semantic information, and the output is a feature value vector;

[0026] S14.4, associating the feature value vector of each facial region image with corresponding label or identity information;

[0027] S14.5. Save the characteristic value vector into a database or a file.

[0028] Preferably, the biofeedback sensor in step S4 includes a heart rate sensor, a skin electrical sensor and a brain wave sensor;

[0029] The heart rate sensor is used to monitor the user's heart rate changes and reflect the user's physical and mental state;

[0030] The galvanic skin sensor detects changes in skin resistance and indicates the user's relaxation level;

[0031] The brain wave sensor captures the user's brain activity and identifies the user's state of relaxation or concentration.

[0032] Preferably, the step S8 of overflow detection specifically includes the following steps:

[0033] S81, using Gaussian mixture model to separate human posture from background in spa equipment;

[0034] S82. Use the key point detection algorithm OpenPose to process the segmented human body image to identify and locate the key parts of the human body;

[0035] S83. Utilize the detected key point information to estimate the patient's specific posture through posture estimation based on minimizing the direct key point distance.

[0036] The step S81 further comprises the following steps:

[0037] S81.1. Use a camera or sensor to obtain image or video data of a person's posture and background in a spa device;

[0038] S81.2. extracting color features of the human body posture and background in water by using a color histogram;

[0039] S81.3, use the texture analysis method LBP to extract the texture features of the human body posture and background in water;

[0040] S81.4. Extract motion features of human body posture in water by optical flow method;

[0041] S81.5. Determine the parameters of the Gaussian mixture model, including the number of Gaussian distributions and the type of covariance matrix;

[0042] S81.6, using the extracted human posture and background feature data in water as input, training a Gaussian mixture model to fit the probability distribution of the data;

[0043] S81.7. Use the trained Gaussian mixture model to perform probabilistic inference on the new underwater image data and separate the parts of the image belonging to the human body posture and the background.

[0044] The step S82 further comprises:

[0045] S82.1, obtaining the human body image segmented in step S81, and retaining the human body part in the image;

[0046] S82.2, taking each segmented human body part image as input, processing the image through the OpenPose algorithm to detect and locate key parts of the human body;

[0047] S82.3. Verify and calibrate the key points detected by OpenPose, and perform pose estimation by connecting the detected key points to obtain the pose information of the human body;

[0048] S82.4. Convert the detected key point information into numerical values ​​of the coordinate position and posture angle of the posture.

[0049] The step S83 further comprises:

[0050] S83.1. Initialize posture parameters, including joint angles or other features describing posture;

[0051] S83.2. For each pair of key points, calculate the distance between them using the Euclidean distance;

[0052] S83.3. Construct an objective function that measures the difference between the current estimated posture and the actual key points; the objective function is a weighted sum of the distances of all key points;

[0053] S83.4. Use the gradient descent optimization algorithm to minimize the objective function;

[0054] S83.5. Use the evaluation metric root mean square error to quantify the difference between the estimated result and the true pose.

[0055] A hydrotherapy equipment control system for rehabilitation treatment, comprising a user management module, a hydrotherapy equipment control module, a parameter setting module, a physiological index monitoring module, a controller module, a water flow detection module and a visual display module;

[0056] The user management module is used to identify the user of the hydrotherapy equipment and formulate a personalized treatment and rehabilitation program according to the user's physical condition and needs;

[0057] The equipment control module is used to control the start and stop of the hydrotherapy equipment.

[0058] The parameter setting module is used to set the temperature range, cycle time interval, filtration time interval and flow range parameters of the hydrotherapy equipment;

[0059] The physiological index monitoring module is used to monitor the user's physiological indexes, including heart rate, skin electricity and brain waves, to evaluate the user's physical condition and rehabilitation progress;

[0060] The controller module is used to control the operation of each module of the system;

[0061] The water flow detection module is used to monitor the water flow of the hydrotherapy equipment through a water flow sensor;

[0062] The visual display module is used to display the operating status of the hydrotherapy equipment and the user's physiological index information so that the user can understand the treatment effect.

[0063] Preferably, the user management module includes an image recognition submodule and a plan formulation submodule;

[0064] The image recognition submodule captures the user image through a camera and uses image recognition technology to identify the user identity;

[0065] The program formulation submodule formulates a personalized treatment and rehabilitation program based on user information and historical data using machine learning and deep learning algorithms.

[0066] Preferably, the hydrotherapy equipment control module includes a water flow control submodule, a temperature control submodule and a water overflow warning submodule;

[0067] The water flow control submodule is used to control the water pump to adjust the water flow speed and direction of the hydrotherapy device to adapt to different treatment needs and user preferences;

[0068] The temperature control submodule controls the output of the heater to adjust the water temperature of the hydrotherapy pool to meet the treatment requirements;

[0069] The overflow warning submodule is used to continuously monitor the status of the spa equipment, detect any abnormal conditions, and issue a warning in a timely manner when a situation that affects the safety of the user is detected;

[0070] The parameter setting module includes a temperature setting submodule, a cycle time interval setting submodule, a filtering time interval setting submodule and a flow range setting submodule;

[0071] The temperature setting submodule is used by the user to set the water temperature range of the hydrotherapy pool to ensure that the water temperature is adapted to different treatment needs and user comfort;

[0072] The cycle time interval setting submodule is used to set the time interval of water circulation of the hydrotherapy equipment, that is, the cycle period of the water flow;

[0073] The filtering time interval setting submodule is used to set the time interval for the spa equipment to perform water filtering;

[0074] The flow range setting submodule is used to set the water flow range of the hydrotherapy equipment, including minimum and maximum flow limits, and parameters for adjusting the water flow.

[0075] Preferably, the physiological index monitoring module includes a heart rate sensor submodule, a skin electrical sensor submodule and a brain wave sensor submodule;

[0076] The heart rate sensor submodule is used to monitor the user's heart rate changes in real time;

[0077] The galvanic skin sensor submodule is used to measure the galvanic skin response, that is, the change of skin resistance or conductance;

[0078] The brain wave sensor submodule is used to monitor the user's brain wave activities in real time.

[0079] Preferably, the water flow detection module includes a flow collection submodule, a flow analysis submodule and an abnormal flow detection submodule;

[0080] The flow collection submodule is used to collect water flow data in the hydrotherapy equipment in real time, including key information such as flow rate, flow velocity, flow direction, etc.;

[0081] The flow analysis submodule is used to analyze the data provided by the flow acquisition submodule to determine whether the water flow meets the preset treatment parameters;

[0082] The abnormal flow detection submodule is used to monitor and identify abnormal flow conditions that may affect treatment effects or equipment safety.

[0083] A storage device having computer program instructions stored thereon, characterized in that when the computer instructions are called, they are used to execute the above-mentioned method for controlling a spa equipment for rehabilitation treatment or a control system for a spa equipment for rehabilitation treatment.

[0084] Compared with the prior art, the beneficial effects of the technical solution of the present invention are as follows: the present invention designs a hydrotherapy equipment control method, system and storage device for rehabilitation treatment, and its main design concept is: through image recognition technology and user profile information, the user identity is identified and combined with historical treatment data, a targeted treatment plan is formulated to ensure the targeted and effectiveness of the treatment, avoiding a one-size-fits-all treatment method, and improving the treatment effect and user satisfaction; through biofeedback sensors and controllers, the user's physiological indicators, including changes in heart rate, skin temperature, etc., can be monitored, and the working parameters of the hydrotherapy equipment can be adjusted in real time, which can ensure the safety and effectiveness of the treatment process and avoid discomfort or risks to the user. The flow sensor also detects abnormal water flow or overflow, and issues an alarm in time, which can prevent the occurrence of accidents and ensure the safety of the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived based on the provided drawings without paying any creative work.

[0086] Figure 1 This is a structural diagram of a hydrotherapy equipment control system used for rehabilitation treatment;

[0087] Figure 2 A step diagram of a method for controlling a hydrotherapy device for rehabilitation treatment;

[0088] Among them, 1. User management module; 2. Spa equipment control module; 3. Parameter setting module; 4. Physiological indicator monitoring module; 5. Controller module; 6. Water flow detection module; 7. Visual display module; 11. Image recognition submodule; 12. Program formulation submodule; 21. Water flow control submodule; 22. Temperature control submodule; 23. Overflow warning submodule; 31. Temperature setting submodule; 32. Cycle time interval setting submodule; 33. Filter time interval setting submodule; 34. Flow range setting submodule; 42. Heart rate sensor submodule; 42. Skin electrical sensor submodule; 43. Brain wave sensor submodule; 61. Flow acquisition submodule; 62. Flow analysis submodule; 63. Abnormal flow detection submodule. DETAILED DESCRIPTION

[0089] The drawings are for illustrative purposes only and should not be construed as limiting the present patent;

[0090] In order to better illustrate the present embodiment, some parts in the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0091] It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0092] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0093] Example 1

[0094] A method for controlling a hydrotherapy device for rehabilitation treatment, such as Figure 2 As shown, the following steps are included:

[0095] S1. When a user enters the spa area, the user's identity is identified through image recognition technology, and a personalized treatment plan is formulated based on the user's profile information and historical treatment data;

[0096] S2, the user starts the hydrotherapy device, and the hydrotherapy device is initialized and enters a standby state;

[0097] S3, setting the temperature range, cycle time interval, filtration time interval and flow range parameters of the hydrotherapy equipment;

[0098] S4, placing the biofeedback sensor on the user and ensuring that it has good contact;

[0099] S5, the controller controls the operation of the heater, water pump and filter according to the set parameters;

[0100] S6. During the hydrotherapy process, the controller monitors the operating status of the hydrotherapy equipment and the physiological indicators of the user;

[0101] S7, the controller adjusts the operation of the underwater equipment according to the user's needs and changes in physiological indicators;

[0102] S8. When the flow sensor detects that the water flow is too large or the patient is overflowing with water, the controller sounds an alarm to remind the user to pay attention to safety.

[0103] The step S1 comprises the following steps:

[0104] S11. When the user enters the spa area, the front image of the user is automatically captured by a high-definition camera;

[0105] S12, preprocessing the captured image, using the face detection algorithm MTCNN to locate the facial area in the preprocessed frontal image;

[0106] S13, extracting key feature points from the detected facial area, including the positions of eyes, nose and mouth;

[0107] S14, using the deep learning model VGGFace to encode the extracted facial region features into a feature value vector;

[0108] S15, matching the encoded feature value vector with the user's facial feature value vector stored in a database to determine the user's identity;

[0109] S16, formulating a personalized hydrotherapy treatment plan based on the identified user identity and the user's profile information and historical treatment data;

[0110] The step S14 further comprises the following steps:

[0111] S14.1. Set up the pre-trained VGGFace model and its weights, and initialize a Keras framework;

[0112] S14.2, prepare a facial region image dataset, and preprocess each facial region image;

[0113] S14.3, input the preprocessed facial region image into the VGGFace model, and obtain the output of the second-to-last fully connected layer as the facial feature representation, wherein the second-to-last fully connected layer contains high-level semantic information, and the output is a feature value vector;

[0114] S14.4, associating the feature value vector of each facial region image with corresponding label or identity information;

[0115] S14.5. Save the characteristic value vector into a database or a file.

[0116] The biofeedback sensor in step S4 includes a heart rate sensor, a skin electrical sensor and a brain wave sensor;

[0117] The heart rate sensor is used to monitor the user's heart rate changes and reflect the user's physical and mental state;

[0118] The galvanic skin sensor detects changes in skin resistance and indicates the user's relaxation level;

[0119] The brain wave sensor captures the user's brain activity and identifies the user's state of relaxation or concentration.

[0120] The step S8 of overflow detection specifically includes the following steps:

[0121] S81, using Gaussian mixture model to separate human posture from background in spa equipment;

[0122] S82. Use the key point detection algorithm OpenPose to process the segmented human body image to identify and locate the key parts of the human body;

[0123] S83. Utilize the detected key point information to estimate the patient's specific posture through posture estimation based on minimizing the direct key point distance.

[0124] The step S81 further comprises the following steps:

[0125] S81.1. Use a camera or sensor to obtain image or video data of a person's posture and background in a spa device;

[0126] S81.2. extracting color features of the human body posture and background in water by using a color histogram;

[0127] S81.3, use the texture analysis method LBP to extract the texture features of the human body posture and background in water;

[0128] S81.4. Extract motion features of human body posture in water by optical flow method;

[0129] S81.5. Determine the parameters of the Gaussian mixture model, including the number of Gaussian distributions and the type of covariance matrix;

[0130] S81.6, using the extracted human posture and background feature data in water as input, training a Gaussian mixture model to fit the probability distribution of the data;

[0131] S81.7. Use the trained Gaussian mixture model to perform probabilistic inference on the new underwater image data and separate the parts of the image belonging to the human body posture and the background.

[0132] The step S82 further comprises:

[0133] S82.1, obtaining the human body image segmented in step S81, and retaining the human body part in the image;

[0134] S82.2, taking each segmented human body part image as input, processing the image through the OpenPose algorithm to detect and locate key parts of the human body;

[0135] S82.3. Verify and calibrate the key points detected by OpenPose, and perform pose estimation by connecting the detected key points to obtain the pose information of the human body;

[0136] S82.4. Convert the detected key point information into numerical values ​​of the coordinate position and posture angle of the posture.

[0137] The step S83 further comprises:

[0138] S83.1. Initialize posture parameters, including joint angles or other features describing posture;

[0139] S83.2. For each pair of key points, calculate the distance between them using the Euclidean distance;

[0140] S83.3. Construct an objective function that measures the difference between the current estimated posture and the actual key points; the objective function is a weighted sum of the distances of all key points;

[0141] S83.4. Use the gradient descent optimization algorithm to minimize the objective function;

[0142] S83.5. Use the evaluation metric root mean square error to quantify the difference between the estimated result and the true pose.

[0143] The system uses image recognition technology to identify the user's identity when the user enters the spa area. The system can develop a personalized treatment plan based on the individual's profile information and historical treatment data to ensure the targeted and effective treatment. After the user starts the spa equipment, the equipment enters the standby state and initializes the settings according to the preset parameters, including key parameters such as temperature, cycle time, filtration time and water flow. The use of biofeedback sensors further enhances the ability of personalized treatment, ensuring good contact between sensors to accurately monitor the user's physiological indicators and feedback. The controller accurately controls the operation of the heater, water pump and filter based on the real-time monitored user's physiological indicators and set parameters to ensure stability and effectiveness during the treatment process. During the treatment process, the controller continuously monitors the operating status of the spa equipment and the user's physiological response, and adjusts the working mode of the underwater equipment at any time to respond to changes in user needs. At critical moments, such as abnormal water flow or overflow of the patient, the flow sensor will immediately detect and trigger an alarm, reminding the user to pay attention to safety in a timely manner and effectively prevent potential risks.

[0144] Example 2

[0145] A hydrotherapy equipment control system for rehabilitation treatment, such as Figure 1 As shown, it includes a user management module 1, a hydrotherapy equipment control module 2, a parameter setting module 3, a physiological index monitoring module 4, a controller module 5, a water flow detection module 6 and a visual display module 7;

[0146] The user management module 1 is used to identify the user of the hydrotherapy equipment and formulate a personalized treatment and rehabilitation plan according to the user's physical condition and needs;

[0147] The equipment control module 2 is used to control the start and stop of the hydrotherapy equipment.

[0148] The parameter setting module 3 is used to set the temperature range, cycle time interval, filtration time interval and flow range parameters of the hydrotherapy equipment;

[0149] The physiological index monitoring module 4 is used to monitor the user's physiological indexes, including heart rate, skin electricity and brain waves, to evaluate the user's physical condition and rehabilitation progress;

[0150] The controller module 5 is used to control the operation of each module of the system;

[0151] The water flow detection module 6 is used to monitor the water flow of the hydrotherapy equipment through a water flow sensor;

[0152] The visual display module 7 is used to display the operating status of the hydrotherapy equipment and the user's physiological index information so that the user can understand the treatment effect.

[0153] The user management module 1 includes an image recognition submodule 11 and a plan formulation submodule 12;

[0154] The image recognition submodule 11 captures the user image through a camera and uses image recognition technology to identify the user identity;

[0155] The program formulation submodule 12 formulates a personalized treatment and rehabilitation program based on user information and historical data using machine learning and deep learning algorithms.

[0156] The hydrotherapy equipment control module 2 includes a water flow control submodule 21, a temperature control submodule 22 and a water overflow warning submodule 23;

[0157] The water flow control submodule 21 is used to control the water pump to adjust the water flow speed and direction of the hydrotherapy device to meet different treatment needs and user preferences;

[0158] The temperature control submodule 22 controls the output of the heater to adjust the water temperature of the hydrotherapy pool to meet the treatment requirements;

[0159] The overflow warning submodule 23 is used to continuously monitor the status of the hydrotherapy equipment, detect any abnormal conditions, and issue a warning in a timely manner when a condition that affects the safety of the user is detected;

[0160] The parameter setting module 3 includes a temperature setting submodule 31, a cycle time interval setting submodule 32, a filtering time interval setting submodule 33 and a flow range setting submodule 34;

[0161] The temperature setting submodule 31 is used by the user to set the water temperature range of the hydrotherapy pool to ensure that the water temperature is adapted to different treatment needs and user comfort;

[0162] The cycle time interval setting submodule 32 is used to set the time interval of water circulation of the hydrotherapy equipment, that is, the cycle period of the water flow;

[0163] The filtering time interval setting submodule 33 is used to set the time interval for the spa equipment to perform water filtering;

[0164] The flow range setting submodule 34 is used to set the water flow range of the hydrotherapy device, including minimum and maximum flow limits, and parameters for adjusting the water flow.

[0165] The physiological index monitoring module 4 includes a heart rate sensor submodule 41, a skin electrical sensor submodule 42 and a brain wave sensor submodule 43;

[0166] The heart rate sensor submodule 41 is used to monitor the user's heart rate changes in real time;

[0167] The skin electrical sensor submodule 42 is used to measure the skin electrical response, that is, the change of skin resistance or conductance;

[0168] The brain wave sensor submodule 43 is used to monitor the user's brain wave activities in real time.

[0169] The water flow detection module 6 includes a flow collection submodule 61, a flow analysis submodule 62 and an abnormal flow detection submodule 63;

[0170] The flow collection submodule 61 is used to collect water flow data in the hydrotherapy equipment in real time, including key information such as flow rate, flow velocity, flow direction, etc.;

[0171] The flow analysis submodule 62 is used to analyze the data provided by the flow acquisition submodule to determine whether the water flow meets the preset treatment parameters;

[0172] The abnormal flow detection submodule 63 is used to monitor and identify abnormal flow conditions that may affect treatment effects or equipment safety.

[0173] The beneficial effect of the technical solution of the present invention is that the present invention designs a hydrotherapy equipment control method, system and storage device for rehabilitation treatment, which identifies the user identity through the image recognition technology and user profile information of the user management module 1 and combines the historical treatment data to formulate a targeted treatment plan to ensure the targetedness and effectiveness of the treatment, avoid a one-size-fits-all treatment method, and improve the treatment effect and user satisfaction; the biofeedback sensor and controller of the physiological indicator monitoring module 4 monitor the user's physiological indicators, including changes in heart rate, skin temperature, etc., and can adjust the working parameters of the hydrotherapy equipment in real time, which can ensure the safety and effectiveness of the treatment process and avoid discomfort or risks to the user; the flow sensor of the water flow detection module 6 detects abnormal water flow or overflow, and issues an alarm in time, which can prevent the occurrence of accidents and ensure the safety of the user.

[0174] A storage device having computer program instructions stored thereon, characterized in that when the computer instructions are called, they are used to execute a spa equipment control method for rehabilitation treatment or a spa equipment control system for rehabilitation treatment as described in any one of claims 1-9.

[0175] The same or similar reference numerals correspond to the same or similar components;

[0176] The terms used in the drawings to describe positional relationships are only used for illustrative purposes and should not be construed as limiting this patent;

[0177] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made on the basis of the above description. It is not necessary and impossible to list all the implementation methods here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A method for controlling a hydrotherapy device for rehabilitation treatment, characterized in that: The following steps are involved: S1. When a user enters the spa area, the user's identity is identified through image recognition technology, and a personalized treatment plan is formulated based on the user's profile information and historical treatment data; S2, the user starts the hydrotherapy device, and the hydrotherapy device is initialized and enters a standby state; S3, setting the temperature range, cycle time interval, filtration time interval and flow range parameters of the hydrotherapy equipment; S4, placing the biofeedback sensor on the user and ensuring that it has good contact; S5, the controller controls the operation of the heater, water pump and filter according to the set parameters; S6. During the hydrotherapy process, the controller monitors the operating status of the hydrotherapy equipment and the physiological indicators of the user; S7, the controller adjusts the operation of the underwater equipment according to the user's needs and changes in physiological indicators; S8. When the flow sensor detects that the water flow is too large or the patient is overflowing with water, the controller sounds an alarm to remind the user to pay attention to safety.

2. A method for controlling a hydrotherapy device for rehabilitation treatment according to claim 1, characterized in that: The step S1 comprises the following steps: S11. When the user enters the spa area, the front image of the user is automatically captured by a high-definition camera; S12, preprocessing the captured image, using the face detection algorithm MTCNN to locate the facial area in the preprocessed frontal image; S13, extracting key feature points from the detected facial area, including the positions of eyes, nose and mouth; S14, using the deep learning model VGGFace to encode the extracted facial region features into a feature value vector; S15, matching the encoded feature value vector with the user's facial feature value vector stored in a database to determine the user's identity; S16, formulating a personalized hydrotherapy treatment plan based on the identified user identity and the user's profile information and historical treatment data; The step S14 further comprises the following steps: S14.

1. Set up the pre-trained VGGFace model and its weights, and initialize a Keras framework; S14.2, prepare a facial region image dataset, and preprocess each facial region image; S14.3, input the preprocessed facial region image into the VGGFace model, and obtain the output of the second-to-last fully connected layer as the facial feature representation, wherein the second-to-last fully connected layer contains high-level semantic information, and the output is a feature value vector; S14.4, associating the feature value vector of each facial region image with corresponding label or identity information; S14.

5. Save the characteristic value vector into a database or a file.

3. A method for controlling a hydrotherapy device for rehabilitation treatment according to claim 1, characterized in that: The biofeedback sensor in step S4 includes a heart rate sensor, a skin electrical sensor and a brain wave sensor; The heart rate sensor is used to monitor the user's heart rate changes and reflect the user's physical and mental state; The galvanic skin sensor detects changes in skin resistance and indicates the user's relaxation level; The brain wave sensor captures the user's brain activity and identifies the user's state of relaxation or concentration.

4. A method for controlling a hydrotherapy device for rehabilitation treatment according to claim 1, characterized in that: The step S8 of overflow detection specifically includes the following steps: S81, using Gaussian mixture model to separate human posture from background in spa equipment; S82. Use the key point detection algorithm OpenPose to process the segmented human body image to identify and locate the key parts of the human body; S83, using the detected key point information to estimate the patient's specific posture through posture estimation based on minimization of direct key point distance; The step S81 further comprises the following steps: S81.

1. Use a camera or sensor to obtain image or video data of a person's posture and background in a spa device; S81.

2. extracting color features of the human body posture and background in water by using a color histogram; S81.3, use the texture analysis method LBP to extract the texture features of the human body posture and background in water; S81.

4. Extract motion features of human body posture in water by optical flow method; S81.

5. Determine the parameters of the Gaussian mixture model, including the number of Gaussian distributions and the type of covariance matrix; S81.6, using the extracted human posture and background feature data in water as input, training a Gaussian mixture model to fit the probability distribution of the data; S81.7, using the trained Gaussian mixture model, perform probabilistic inference on the new underwater image data to separate the parts of the image belonging to the human body posture and the background; The step S82 further comprises: S82.1, obtaining the human body image segmented in step S81, and retaining the human body part in the image; S82.2, taking each segmented human body part image as input, processing the image through the OpenPose algorithm to detect and locate key parts of the human body; S82.

3. Verify and calibrate the key points detected by OpenPose, and perform pose estimation by connecting the detected key points to obtain the pose information of the human body; S82.

4. Convert the detected key point information into numerical values ​​of the coordinate position and posture angle of the posture; The step S83 further comprises: S83.

1. Initialize posture parameters, including joint angles or other features describing posture; S83.

2. For each pair of key points, calculate the distance between them using the Euclidean distance; S83.

3. Construct an objective function that measures the difference between the current estimated pose and the actual key points; S83.

4. Use the gradient descent optimization algorithm to minimize the objective function; S83.

5. Use the evaluation metric root mean square error to quantify the difference between the estimated result and the true pose.

5. A hydrotherapy equipment control system for rehabilitation treatment, characterized in that: It comprises a user management module (1), a hydrotherapy equipment control module (2), a parameter setting module (3), a physiological index monitoring module (4), a controller module (5), a water flow detection module (6) and a visual display module (7); The user management module (1) is used to identify the user of the hydrotherapy equipment and formulate a personalized treatment and rehabilitation program according to the user's physical condition and needs; The equipment control module (2) is used to control the start and stop of the hydrotherapy equipment. The parameter setting module (3) is used to set the temperature range, cycle time interval, filtration time interval and flow range parameters of the hydrotherapy equipment; The physiological index monitoring module (4) is used to monitor the user's physiological indexes, including heart rate, skin electricity and brain waves, so as to evaluate the user's physical condition and rehabilitation progress; The controller module (5) is used to control the operation of each module of the system; The water flow detection module (6) is used to monitor the water flow of the hydrotherapy equipment through a water flow sensor; The visual display module (7) is used to display the operating status of the hydrotherapy equipment and the user's physiological index information so that the user can understand the treatment effect.

6. A hydrotherapy equipment control system for rehabilitation treatment according to claim 5, characterized in that: The user management module (1) comprises an image recognition submodule (11) and a plan formulation submodule (12); The image recognition submodule (11) captures the user image through a camera and uses image recognition technology to identify the user identity; The program formulation submodule (12) formulates a personalized treatment and rehabilitation program based on user information and historical data using machine learning and deep learning algorithms.

7. A hydrotherapy equipment control system for rehabilitation treatment according to claim 5, characterized in that: The hydrotherapy equipment control module (2) comprises a water flow control submodule (21), a temperature control submodule (22) and a water overflow warning submodule (23); The water flow control submodule (21) is used to control the water pump to adjust the water flow speed and direction of the hydrotherapy equipment to meet different treatment needs and user preferences; The temperature control submodule (22) controls the output of the heater to adjust the water temperature of the hydrotherapy pool to meet the treatment requirements; The overflow warning submodule (23) is used to continuously monitor the status of the hydrotherapy equipment, detect any abnormal situation, and issue a warning in time when a situation that affects the safety of the user is detected; The parameter setting module (3) comprises a temperature setting submodule (31), a cycle time interval setting submodule (32), a filtering time interval setting submodule (33) and a flow range setting submodule (34); The temperature setting submodule (31) is used for the user to set the water temperature range of the hydrotherapy pool to ensure that the water temperature is adapted to different treatment needs and user comfort; The cycle time interval setting submodule (32) is used to set the time interval of water circulation of the hydrotherapy equipment, that is, the cycle period of the water flow; The filtering time interval setting submodule (33) is used to set the time interval for the hydrotherapy equipment to perform water filtering; The flow range setting submodule (34) is used to set the water flow range of the hydrotherapy equipment, including minimum and maximum flow limits, and parameters for adjusting the water flow.

8. A hydrotherapy equipment control system for rehabilitation treatment according to claim 5, characterized in that: The physiological index monitoring module (4) comprises a heart rate sensor submodule (41), a skin electrical sensor submodule (42) and a brain wave sensor submodule (43); The heart rate sensor submodule (41) is used to monitor the user's heart rate changes in real time; The skin electrical sensor submodule (42) is used to measure skin electrical response, that is, changes in skin resistance or conductance; The brain wave sensor submodule (43) is used to monitor the user's brain wave activities in real time.

9. A hydrotherapy equipment control system for rehabilitation treatment according to claim 5, characterized in that: The water flow detection module (6) comprises a flow collection submodule (61), a flow analysis submodule (62) and an abnormal flow detection submodule (63); The flow collection submodule (61) is used to collect water flow data in the hydrotherapy equipment in real time, including key information such as flow rate, flow velocity, flow direction, etc.; The flow analysis submodule (62) is used to analyze the data provided by the flow acquisition submodule to determine whether the water flow meets the preset treatment parameters; The abnormal flow detection submodule (63) is used to monitor and identify abnormal flow conditions that may affect treatment effects or equipment safety.

10. A storage device having computer program instructions stored thereon, characterized in that: When the computer instructions are called, they are used to execute a method for controlling a spa equipment for rehabilitation treatment or a control system for a spa equipment for rehabilitation treatment as described in any one of claims 1 to 9.

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