A heated air therapy device with diagnostic function

Abstract

This application provides a heated air therapy device with diagnostic capabilities. The diagnostic device can collect physiological information from the target area of ​​the patient and obtain a thrombosis diagnosis result based on this information. The airbag includes multiple airbag cavities, each with a heating layer connected to a heating module. An air pump delivers gas to the airbag. Each airbag cavity acts on the target area to apply pressure and transfer heat. A valve assembly controls the on / off state of the gas passage between the air pump, each airbag cavity, and the vent. A control device determines the treatment mode for the target area based on the thrombosis diagnosis result and controls the operation of the air pump, valve assembly, and heating module in each airbag cavity according to the treatment mode. This enhances the therapeutic effect of the device.

Description

Technical Field

[0001] The present application relates to the field of medical health technology, and in particular to a heating air therapy device with diagnostic function. Background Art

[0002] In the medical field, air pressure therapy devices, as a non-invasive physical therapy device, are widely used to promote blood circulation, reduce tissue edema, prevent and treat deep vein thrombosis (DVT), etc. Traditional air pressure therapy devices mainly generate pressure through air pumps, and apply periodic pressure to the peripheral tissues of the human body through air bags, thereby promoting blood circulation and lymphatic return. However, these devices are relatively simple in function, often only have basic inflation and deflation functions, and have poor treatment effects. Summary of the invention

[0003] The technical problem to be solved by this application is to provide a heated air therapy device with diagnostic function, which can improve the therapeutic effect of the therapy device. The specific solution is as follows:

[0004] A heated air therapy device with diagnostic function, comprising:

[0005] A diagnostic device, an air pump, a valve assembly, an airbag, a heating module, and a control device; the airbag includes a plurality of airbag cavities, each of which is provided with a heating layer, and the heating layer is connected to the heating module; the diagnostic device includes a first acquisition assembly, a second acquisition assembly, and a diagnostic assembly;

[0006] The first acquisition component is used to obtain first physiological information of the target object's area to be diagnosed; the first physiological information includes at least one of D-dimer and prothrombin time;

[0007] The second acquisition component is used to obtain second physiological information of the target object's area to be diagnosed; the second physiological information includes at least one of heart rate information, blood pressure information, blood oxygen saturation and body temperature information;

[0008] The diagnostic component is used to determine a thrombus diagnosis result based on the first physiological information and the second physiological information;

[0009] The air pump is used to deliver gas to the airbag;

[0010] The heating module is used to output heat to the airbag;

[0011] Each of the airbag cavities is used to act on the area to be diagnosed of the target object to apply pressure and transfer heat to the area to be diagnosed of the target object;

[0012] The valve assembly is used to control the on / off state of the gas passage between the air pump, each of the airbag cavities and the air release port;

[0013] The control device is used to determine the treatment mode of the area to be diagnosed according to the thrombus diagnosis result of the area to be diagnosed; and control the operation of the air pump, the valve assembly and the heating module according to the treatment mode.

[0014] The above-mentioned heated air therapy device, optionally, the first acquisition component includes:

[0015] The first collection component includes a blood sampling module and a blood analysis module;

[0016] The blood sampling module is used to obtain a blood sample from the target object and transmit the blood sample to the blood analysis module;

[0017] The blood analysis module is used to detect the blood pressure sample to obtain the first physiological information.

[0018] The above-mentioned heated air therapy device, optionally, the diagnostic component is used for:

[0019] Inputting the first physiological information into a pre-trained gradient boosting tree (GBT) model to obtain an initial thrombus recognition result of the area to be diagnosed;

[0020] The initial thrombus identification result and the second physiological information are input into a pre-trained logistic regression model to obtain a thrombus diagnosis result of the area to be diagnosed.

[0021] The above-mentioned heated air therapy device, optionally, the control device is used to:

[0022] Determine the operation parameters corresponding to the treatment mode, wherein the operation parameters include pressure control information and temperature control information of each of the airbag cavities; the pressure control information of each of the airbag cavities includes multiple target pressures and operation time information; the temperature control information includes a target temperature; the operation time information includes at least one of a working time, a pressure holding time, and an interval time;

[0023] Controlling the operation of the air pump and the valve assembly according to the pressure control information;

[0024] The heating module is controlled to operate according to the temperature control information.

[0025] The above-mentioned heated air therapy device, optionally, each of the airbag cavities includes a pressure sensor for collecting the pressure applied by the airbag cavity to the target object;

[0026] The control device is used for:

[0027] The output power of the air pump and the opening degree of the valve assembly are controlled according to the pressure collected by the pressure sensor and the pressure control information.

[0028] The above-mentioned heating air therapy device, optionally, the airbag cavity includes a temperature sensor for collecting the temperature of the airbag cavity acting on the target object;

[0029] The control device is used for:

[0030] The output power of the heating module is controlled according to the temperature collected by the temperature sensor and the temperature control information.

[0031] The above-mentioned heating air therapy device, optionally, the airbag includes a first airbag cavity, a second airbag cavity and a third airbag cavity; each of the airbag cavities of the airbag acts on different parts of the area to be diagnosed.

[0032] The above-mentioned heated air therapy device, optionally, the thrombosis diagnosis result includes a thrombosis risk score;

[0033] The control device is used for:

[0034] Determining the thrombosis risk level of the area to be diagnosed according to the thrombosis risk score;

[0035] A treatment mode for the area to be diagnosed is determined according to the thrombosis risk level of the area to be diagnosed.

[0036] The above-mentioned heated air therapy device may optionally further include: a display module;

[0037] The display module is used to display the thrombosis diagnosis result and the treatment mode.

[0038] The above-mentioned heated air therapy device, optionally, the control device is also used for:

[0039] When receiving a treatment mode switching instruction, determining a target treatment mode corresponding to the treatment mode switching instruction;

[0040] The air pump, the valve assembly and the heating module are controlled to operate according to the target treatment mode.

[0041] Based on the above-mentioned implementation of the present application, a heating air therapy device with diagnostic function is provided, including: a diagnostic device, an air pump, a valve assembly, an airbag and a control device; the airbag includes a plurality of airbag cavities, each of which is provided with a heating layer, and the heating layer is connected to the heating module; the diagnostic device is used to collect physiological information of the target object's area to be diagnosed, and obtain the thrombosis diagnosis result of the target object's area to be diagnosed according to the physiological information; the air pump is used to deliver gas to the airbag; each of the airbag cavities is used to act on the target object's area to be diagnosed, so as to apply pressure and transfer heat to the target object's area to be diagnosed; the valve assembly is used to control the on-off state of the gas passage between the air pump, each of the airbag cavities and the air vent; the control device is used to determine the treatment mode of the area to be diagnosed according to the thrombosis diagnosis result of the area to be diagnosed; and the air pump, the valve assembly and the heating module are controlled to operate according to the treatment mode. The solution provided by the embodiment of the present application can improve the treatment effect of the therapeutic device. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0043] Figure 1 A schematic diagram of the structure of a heating air therapy device with diagnostic function provided in this application;

[0044] Figure 2 A schematic diagram of the structure of a diagnostic device provided in this application;

[0045] Figure 3 A schematic diagram of the structure of another heating air therapy device with diagnostic function provided in this application. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0047] In this application, the terms "comprises", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element.

[0048] See also Figure 1 , a structural schematic diagram of a heating air therapy device with a diagnostic function is provided for an embodiment of the present application, and the heating air therapy device with a diagnostic function includes: a diagnostic device 101, an air pump 102, a heating module 103, a valve assembly 104, an airbag 105 and a control device 106; the airbag 105 includes a plurality of airbag cavities, each of which is provided with a heating layer, and the heating layer is connected to the heating module 103.

[0049] Optional, such as Figure 2 As shown, the diagnostic device 101 includes: a first acquisition component 1011 , a second acquisition component 1012 and a diagnostic component 1013 .

[0050] The first acquisition component 1011 is used to obtain first physiological information of the target object's area to be diagnosed; the first physiological information includes at least one of D-dimer and prothrombin time.

[0051] The second acquisition component 1012 is used to obtain the second physiological information of the target object's area to be diagnosed; the second physiological information includes at least one of heart rate information, blood pressure information, blood oxygen saturation and body temperature information; in this embodiment, the second acquisition component may include various types of sensors, and the second physiological information of the target object can be acquired through each sensor, and the second physiological information is sent to the diagnosis component.

[0052] The diagnostic component 1013 is used to determine a thrombosis diagnosis result according to the first physiological information and the second physiological information. In this embodiment, the thrombosis diagnosis result can represent the thrombosis risk level of the target object.

[0053] The air pump 102 is used to deliver gas to the airbag.

[0054] The heating module 103 is used to output heat to the airbag.

[0055] Each of the airbag cavities of the airbag 105 is used to act on the to-be-diagnosed area of ​​the target object to apply pressure and transfer heat to the to-be-diagnosed area of ​​the target object. In this embodiment, the airbag is divided into a first airbag package and a second airbag package; the first airbag package includes a first airbag cavity, and the second airbag package includes a second airbag cavity and a third airbag cavity.

[0056] Optionally, the airbag is composed of three layers of material, the inner layer is polyvinyl chloride (PVC) or polyurethane (TPU) fabric, the middle layer is a graphene heating layer, and the outer layer is a waterproof textile fiber fabric, and the three layers of material are combined by high-frequency heat sealing technology.

[0057] The valve assembly 104 is used to control the on / off state of the gas passage between the air pump, each of the airbag cavities and the air release port. In this embodiment, the valve assembly can be a solenoid valve.

[0058] The control device 106 is used to determine a treatment mode for the area to be diagnosed according to the thrombus diagnosis result of the area to be diagnosed; and control the operation of the air pump, the valve assembly and the heating module according to the treatment mode.

[0059] In this embodiment, the control device determines the treatment mode of the area to be diagnosed according to the thrombus diagnosis result, including the pressure control information and temperature control information of each airbag cavity. The pressure control information includes multiple target pressures and operation time information (such as working time, pressure holding time and interval time). The temperature control information includes the target temperature. The control device controls the operation of the air pump and valve assembly according to the pressure control information to realize the inflation and deflation process of the airbag. The control device controls the operation of the heating module according to the temperature control information to adjust the temperature of the airbag.

[0060] Applying the solution provided in the embodiments of the present application can improve the therapeutic effect of the therapeutic device.

[0061] In an embodiment provided in the present application, based on the above solution, optionally, the first collection component includes: a blood sampling module and a blood analysis module;

[0062] The blood sampling module is used to obtain a blood sample from the target object and transport the blood sample to the blood analysis module. In this embodiment, the blood sampling module may include a blood collection needle and a blood collection needle transport device, wherein the blood collection needle is used to collect a blood sample from the target object, and the blood collection needle transport device can transport the blood sample to the blood analysis module.

[0063] The blood analysis module is used to detect the blood pressure sample to obtain the first physiological information. In this embodiment, the blood analysis module can be a coagulation analyzer, specifically a device for measuring blood coagulation parameters, and the coagulation analyzer can perform corresponding measurement operations to obtain at least one of D-dimer and prothrombin time.

[0064] Optionally, the blood analysis module can dilute the specific antibody for D-dimer and add it to each well of the microplate so that the antibody is attached to the well wall to form a coating. Fill the sites not occupied by the antibody with a protein (such as bovine serum albumin BSA). Add the pretreated blood sample to the blocked microwell so that the D-dimer in the sample specifically binds to the coated antibody to obtain a complex. Wash the microplate with a buffer to ensure that only the specifically bound complex is left. Add a secondary antibody of horseradish peroxidase HRP or alkaline phosphatase AP so that the secondary antibody binds to the previously formed complex to obtain a target complex, and wash the microplate again with a buffer. Add a substrate solution to convert the target complex into a colored product, add a stop solution (such as sulfuric acid) after a preset time, and then measure the absorbance value of each well with a spectrophotometer or an enzyme plate reader, and calculate the actual concentration of D-dimer in the sample based on the absorbance value and the standard curve. The standard curve includes the corresponding relationship between the absorbance value and the D-dimer concentration.

[0065] Optionally, the blood analysis module can centrifuge the blood sample, add tissue thromboplastin reagent to the centrifuged blood sample, and start timing until fibrin clot formation is detected to obtain prothrombin time. In this embodiment, clot formation can be detected by optical density changes.

[0066] In this embodiment, after obtaining the first physiological information, the blood analysis module sends the first physiological information to the diagnosis component.

[0067] In an embodiment provided in the present application, based on the above solution, optionally, the diagnosis component 1013 is used to:

[0068] Inputting the first physiological information into a pre-trained gradient boosting tree (GBT) model to obtain an initial thrombus recognition result of the area to be diagnosed;

[0069] The initial thrombus identification result and the second physiological information are input into a pre-trained logistic regression model to obtain a thrombus diagnosis result of the area to be diagnosed.

[0070] In this embodiment, the input of the GBT model includes D-dimer and prothrombin time (PT), where D-dimer is an indicator of fibrinolytic activity in the blood. Prothrombin time (PT) is a measure of the time required for blood coagulation and is used to evaluate the function of the extrinsic coagulation pathway. These two features are biomarkers directly related to the mechanism of thrombosis, and they are very important for the initial screening of high-risk patients. The GBT model predicts each sample, and the output can be a continuous risk score or a probability distribution belonging to a certain category (such as "high risk" or "low risk"). This output will be added to the second stage dataset as a new feature.

[0071] In this embodiment, the input of the logistic regression model includes heart rate, blood pressure, blood oxygen saturation temperature, and the output of the GBT model. These features plus the output of the GBT model together constitute a more comprehensive feature set that can better capture the patient's overall health status. The output of the logistic regression model is the final diagnosis result (thrombosis risk score or risk level): the logistic regression model gives the final thrombosis risk score or risk level based on the input feature set. This may be a continuous value (such as a score between 0 and 1) or a discrete classification label (such as "no risk", "low risk", "medium risk", "high risk").

[0072] In some embodiments, the training process of the GBT model is as follows:

[0073] 1. Set the initial prediction value: It can be initialized to the average of all training sample labels (for regression problems) or class probabilities (for classification problems). This can be regarded as the prediction of the first weak learner.

[0074] 2. Data preparation:

[0075] Feature selection: Key features were extracted from the dataset as input, specifically D-dimer and prothrombin time (PT).

[0076] Preprocessing: Perform necessary preprocessing on these features, such as missing value processing, standardization or normalization.

[0077] 3. Set hyperparameters:

[0078] Number of trees (n_estimators): Determines how many trees to build. More trees may improve performance but also increase computational cost.

[0079] Maximum depth (max_depth): Controls the maximum depth of each tree to prevent overfitting.

[0080] Learning rate (learning_rate): Controls how much influence each tree has on the final prediction. A lower learning rate means more trees are needed to achieve the same improvement, but generally leads to better generalization.

[0081] Minimum number of sample splits (min_samples_split) and minimum number of sample leaf nodes (min_samples_leaf): used to control the growth of the tree and avoid overfitting.

[0082] Loss function: defines how to measure the prediction error. The loss function is specifically the mean square error (MSE) function.

[0083] 4. Divide the data: Divide the dataset into a training set (about 70%-80%) and a validation set (about 20%-30%) to evaluate model performance.

[0084] 5. Iterative training:

[0085] Calculate the residual: For each training sample in the current iteration, calculate the difference (i.e., residual) between its true label and the current model prediction. This is calculated based on the selected loss function, which can be a mean square error function.

[0086] Fit a new tree: Train a new decision tree using the residuals as the target variable. The goal of this new tree is to fit these residuals as accurately as possible.

[0087] Update prediction: Update the model's prediction value based on the prediction results of the new tree. The update formula is as follows:

[0088]

[0089] Among them, is the predicted value after the mth iteration, is the predicted value of the previous iteration, η is the learning rate, is the predicted value of the new tree.

[0090] 6. Hyperparameter Tuning:

[0091] Grid Search / Random Search: Use cross-validation combined with grid search or random search to find the best hyperparameter combination.

[0092] Evaluate performance: Evaluate model performance on the validation set and adjust hyperparameters to improve the generalization ability of the model.

[0093] 7. Generate intermediate features:

[0094] Predict risk score: Use the trained GBT model to predict all samples and obtain the risk score or other intermediate features of each sample. This output will be added to the second stage dataset as a new feature.

[0095] 8. Final evaluation and optimization:

[0096] Performance evaluation: Use accuracy, AUC-ROC curve, F1 score and other evaluation indicators to evaluate the overall performance of the model.

[0097] Error analysis: Conduct in-depth analysis of cases where the model made incorrect predictions, identify possible causes, and attempt to improve them.

[0098] Continuous optimization: Adjust the model structure or feature engineering strategy based on the results of error analysis, and iterate until a satisfactory performance level is achieved.

[0099] In this embodiment, the training process of the GBT model is an iterative process, which continuously improves the performance of the model by gradually adding new decision trees. In each iteration, the model focuses on reducing the previous prediction error, thereby gradually approaching the true label value. This gradual improvement method enables GBT to capture complex nonlinear relationships and has strong predictive capabilities. At the same time, reasonable hyperparameter setting and tuning are also the key to ensuring model performance.

[0100] In some embodiments, the training process of the logistic regression model is as follows:

[0101] Data preparation: Obtain a data set containing features such as patient blood pressure, blood oxygen saturation, temperature, and risk scores generated by the first model, and perform necessary cleaning and preprocessing. The preprocessing step also includes standardizing or normalizing numerical features, and one-hot encoding or label encoding of categorical variables.

[0102] Data partitioning: The data set is divided into a training set and a validation set, where the training set is used to train the logistic regression model and the validation set is used to evaluate the model performance.

[0103] Model initialization: Set the initial parameters of the logistic regression model, including weights and biases, and select Log Loss as the loss function.

[0104] Training model: Use gradient descent or its variants (such as stochastic gradient descent or mini-batch gradient descent) to minimize the loss function, and iteratively update the model parameters to optimize the prediction performance. In particular, the optimization algorithm used in the training model step is mini-batch gradient descent, and each iteration uses a small batch of samples to calculate the gradient and update the parameters to balance the computational efficiency and model convergence speed.

[0105] Hyperparameter tuning: Use grid search or random search combined with cross validation to find the best regularization strength and other hyperparameters to ensure that the model has good generalization ability. The hyperparameter tuning step uses k-fold cross validation (such as 5-fold or 10-fold) to ensure the stability and reliability of the model on unseen data.

[0106] Model evaluation: Use evaluation indicators such as accuracy, precision, recall, F1 score, and AUC-ROC curve to evaluate the performance of the trained model, and adjust the model structure or feature engineering strategy as needed.

[0107] Deployment and monitoring: Deploy the trained logistic regression model to the actual application environment, and establish a monitoring system to continuously track the performance of the model to ensure its stability on new data; update the model regularly, including retraining the model or adjusting the feature engineering steps. The specific training process of the logistic regression model includes data preparation, model initialization, parameter optimization, hyperparameter tuning, model evaluation and deployment. Through reasonable data preprocessing, selection of appropriate loss functions and optimization algorithms, logistic regression can effectively learn the relationship between input features and target labels, and provide intuitive probability output, which is very suitable for risk assessment tasks in the medical field.

[0108] In an embodiment provided in the present application, based on the above solution, optionally, the control device 106 is used to:

[0109] Determine the operation parameters corresponding to the treatment mode, wherein the operation parameters include pressure control information and temperature control information of each of the airbag cavities; the pressure control information of each of the airbag cavities includes multiple target pressures and operation time information; the temperature control information includes a target temperature; the operation time information includes at least one of a working time, a pressure holding time, and an interval time;

[0110] Controlling the operation of the air pump and the valve assembly according to the pressure control information;

[0111] The heating module is controlled to operate according to the temperature control information.

[0112] In an embodiment provided in the present application, based on the above solution, optionally, each of the airbag cavities includes a pressure sensor for collecting the pressure applied by the airbag cavity to the target object;

[0113] The control device 106 is used to:

[0114] The output power of the air pump and the opening degree of the valve assembly are controlled according to the pressure collected by the pressure sensor and the pressure control information.

[0115] In an embodiment provided in the present application, based on the above solution, optionally, the airbag cavity includes a temperature sensor for collecting the temperature of the airbag cavity acting on the target object;

[0116] The control device 106 is used to:

[0117] The output power of the heating module is controlled according to the temperature collected by the temperature sensor and the temperature control information.

[0118] In an embodiment provided in the present application, based on the above-mentioned scheme, optionally, the airbag includes a first airbag cavity, a second airbag cavity and a third airbag cavity; each of the airbag cavities of the airbag acts on different parts of the area to be diagnosed.

[0119] In an embodiment provided in the present application, based on the above scheme, optionally, the thrombosis diagnosis result includes a thrombosis risk score;

[0120] The control device 106 is used to:

[0121] Determining the thrombosis risk level of the area to be diagnosed according to the thrombosis risk score;

[0122] A treatment mode for the area to be diagnosed is determined according to the thrombosis risk level of the area to be diagnosed.

[0123] In this embodiment, the treatment modes may include multiple types, for example, a mild treatment mode, an intensive treatment mode, a custom treatment mode, and the like.

[0124] In some embodiments, in a gentle mode (suitable for low to moderate risk patients), the target pressure can be 20-30 mmHg. The hold time can be 5-10 seconds after each inflation. The interval time can be a longer interval time, such as a cycle every 30 seconds. The target temperature can be set in a comfortable range, such as between 37°C and 40°C, to avoid discomfort caused by overheating.

[0125] Optionally, the operation time information may include the working time and the total treatment time. The working time may be 1 minute per cycle, including the inflation, pressure maintenance and deflation processes. The total treatment time may be 30 minutes per day, which may be adjusted according to the patient's condition.

[0126] In this embodiment, after the control device is started, if the treatment mode is the gentle mode, the output power of the air pump and the opening of the valve assembly are first controlled so that the airbag cavity is slowly inflated to a predetermined pressure, and then the pressure is maintained for a period of time. Then the air is gradually deflated to restore the airbag to its initial state. While waiting for the next cycle, the heating module continues to provide a warm feeling but does not apply additional pressure. During the whole process, the control device monitors the pressure and temperature in real time through the built-in sensor to ensure safety and effectiveness. By controlling the operation of the therapeutic device in the gentle treatment mode, blood circulation can be slightly promoted, thrombosis can be prevented, and the patient's comfort can be ensured. Suitable for daily preventive care or patients with mild symptoms.

[0127] In some embodiments, in intensive mode (suitable for high-risk patients), the target pressure can be 40-60 mmHg. The holding time can maintain pressure for 15-20 seconds after each inflation. The interval time can be a shorter interval time, such as a cycle every 15 seconds. The target temperature can be set at a slightly higher range, such as 40°C to 42°C, to enhance the vasodilation effect. The working time can be set to 2 minutes per cycle, including inflation, holding and deflation processes. The total treatment time can be set to 60 minutes per day, which can be extended or shortened.

[0128] In this embodiment, after the control device is started, if the treatment mode is the enhanced mode, it is quickly inflated to a predetermined high pressure and then maintained stably for a period of time. During this period, the heating module synchronously provides a higher temperature to help relax muscles and promote blood flow. The deflation speed is relatively fast so that the pressure can be immediately relieved and prepared for the next cycle. During the whole process, the control device strictly monitors the pressure and temperature changes and automatically adjusts them when necessary to ensure the safety and effect of the treatment. It significantly improves blood circulation and actively prevents or relieves the formed thrombus. It is suitable for patients with a higher risk of thrombosis or mild thrombosis symptoms.

[0129] In some embodiments, the risk score interval in which the thrombosis risk score is located can be determined, and the thrombosis risk level corresponding to the risk score interval can be determined, and different thrombosis risk levels correspond to different risk score intervals; after determining the thrombosis risk level, the thrombosis risk level can be used to query a preset configuration file to obtain a treatment mode corresponding to the thrombosis risk level.

[0130] In an embodiment provided in the present application, based on the above solution, optionally, see Figure 3 , the heated air therapy device with diagnostic function further includes: a display module 107;

[0131] The display module 107 is used to display the thrombus diagnosis result and the treatment mode.

[0132] In an embodiment provided in the present application, based on the above solution, optionally, the control device 106 is further used for:

[0133] When receiving a treatment mode switching instruction, determining a target treatment mode corresponding to the treatment mode switching instruction;

[0134] The air pump, the valve assembly and the heating module are controlled to operate according to the target treatment mode.

[0135] In some embodiments, a heated air pressure therapy device includes: a host, which includes a frame, an air pump, a solenoid valve, a power module, a control device, a display module, a heating module and software; an inflatable hose connected between the host and the airbag for transmitting gas; the airbag is divided into a thigh airbag bag and a calf airbag bag, the thigh airbag bag is a single-cavity structure, and the calf airbag bag is a double-cavity structure. The airbag is composed of three layers of materials, the inner layer is polyvinyl chloride (PVC) or polyurethane (TPU) fabric, the middle layer is a graphene heating layer, and the outer layer is a waterproof textile fiber fabric. The three layers of materials are combined by high-frequency heat sealing technology; wherein the control device controls the operation of the air pump and the solenoid valve to realize the inflation and deflation function of the airbag, and sets and displays the treatment parameters through the display module; the heating module heats the airbag by controlling the power supply voltage according to the signal of the temperature sensor. The frame includes a control chassis and an accessory chassis, and the control chassis can be suspended or moved by a carrying trolley.

[0136] Optionally, the display module includes a touch screen and physical buttons, the touch screen is used to set specific parameters, and the physical buttons are used as shortcut keys for commonly used functions and emergency buttons.

[0137] Optionally, the heating module includes a graphene silicone heating film group, a temperature sensor and a power control module. The temperature sensor senses the patient's body temperature. When the body temperature drops, the power control module adjusts the power supply voltage according to the signal of the temperature sensor to heat the airbag.

[0138] Optionally, the device has a preset working mode, and the user can select the preset working mode through the display module or directly set specific parameters such as airbag pressure, holding time, interval time, working time, etc.

[0139] Optionally, the air pump generates a stable high pressure, the pressure sensor monitors the real-time air pressure in the pipeline, the solenoid valve sends an air pressure control signal by the control module according to the set air pressure and the pressure sensor monitoring signal, and the solenoid valve controls the on and off of the air circuit after receiving the signal, thereby realizing the inflation and deflation control of different airbags.

[0140] Optionally, the device uses an air pump to inflate, squeeze, and deflate the airbag in an orderly and rhythmic manner, forming a circulatory pressure from the distal end to the proximal end of the limb, promoting the return of venous blood and lymph, reducing the pressure in the extremity tissue, accelerating blood flow, and preventing the formation of deep vein thrombosis.

[0141] Optionally, the device is particularly suitable for surgical patients, bedridden patients, and patients with low body temperature, excessive heat dissipation, and prone to thrombosis in the lower limbs.

[0142] The specific principles and execution processes of each unit and module in the heating air therapy device system with diagnostic function disclosed in the above-mentioned embodiment of the present application are the same as the heating air therapy device method with diagnostic function disclosed in the above-mentioned embodiment of the present application. Please refer to the corresponding parts of the heating air therapy device method with diagnostic function provided in the above-mentioned embodiment of the present application, and no further details will be given here.

[0143] It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other. For system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0144] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0145] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0146] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present application or certain parts of the embodiments.

[0147] The above is a detailed introduction to a heating air therapy device method with diagnostic function provided by the present application. This article uses specific examples to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A heating air therapy device with diagnostic function, characterized in that: include: A diagnostic device, an air pump, a valve assembly, an airbag, a heating module, and a control device; the airbag includes a plurality of airbag cavities, each of which is provided with a heating layer, and the heating layer is connected to the heating module; the diagnostic device includes a first acquisition assembly, a second acquisition assembly, and a diagnostic assembly; The first acquisition component is used to obtain first physiological information of the target object's area to be diagnosed; the first physiological information includes at least one of D-dimer and prothrombin time; The second acquisition component is used to obtain second physiological information of the to-be-diagnosed area of ​​the target object; The second physiological information includes at least one of heart rate information, blood pressure information, blood oxygen saturation and body temperature information; The diagnostic component is used to input the first physiological information into a pre-trained gradient boosting tree (GBT) model to obtain an initial thrombus recognition result of the area to be diagnosed; Inputting the initial thrombus identification result and the second physiological information into a pre-trained logistic regression model to obtain a thrombus diagnosis result of the area to be diagnosed; The air pump is used to deliver gas to the airbag; The heating module is used to output heat to the airbag; Each of the airbag cavities is used to act on the area to be diagnosed of the target object to apply pressure and transfer heat to the area to be diagnosed of the target object; The valve assembly is used to control the on / off state of the gas passage between the air pump, each of the airbag cavities and the air release port; The control device is used to determine the treatment mode of the area to be diagnosed according to the thrombus diagnosis result of the area to be diagnosed; and control the operation of the air pump, the valve assembly and the heating module according to the treatment mode.

2. The heated air therapy device according to claim 1, characterized in that: The first acquisition component includes: The first collection component includes a blood sampling module and a blood analysis module; The blood sampling module is used to obtain a blood sample from the target object and transmit the blood sample to the blood analysis module; The blood analysis module is used to detect the blood pressure sample to obtain the first physiological information.

3. The heated air therapy device according to claim 1, characterized in that: The control device is used for: Determine the operation parameters corresponding to the treatment mode, wherein the operation parameters include pressure control information and temperature control information of each of the airbag cavities; the pressure control information of each of the airbag cavities includes multiple target pressures and operation time information; the temperature control information includes a target temperature; the operation time information includes at least one of a working time, a pressure holding time, and an interval time; Controlling the operation of the air pump and the valve assembly according to the pressure control information; The heating module is controlled to operate according to the temperature control information.

4. The heated air therapy device according to claim 3, characterized in that: Each of the airbag cavities includes a pressure sensor for collecting the pressure applied by the airbag cavity to the target object; The control device is used for: The output power of the air pump and the opening degree of the valve assembly are controlled according to the pressure collected by the pressure sensor and the pressure control information.

5. The heated air therapy device according to claim 3, characterized in that: The airbag cavity includes a temperature sensor for collecting the temperature of the airbag cavity acting on the target object; The control device is used for: The output power of the heating module is controlled according to the temperature collected by the temperature sensor and the temperature control information.

6. The heated air therapy device according to claim 1, characterized in that: The airbag comprises a first airbag cavity, a second airbag cavity and a third airbag cavity; each of the airbag cavities acts on a different part of the area to be diagnosed.

7. The heated air therapy device according to claim 1, characterized in that: The thrombosis diagnosis result includes a thrombosis risk score; The control device is used for: Determining the thrombosis risk level of the area to be diagnosed according to the thrombosis risk score; A treatment mode for the area to be diagnosed is determined according to the thrombosis risk level of the area to be diagnosed.

8. The heated air therapy device according to claim 7, characterized in that: Also includes: Display module; The display module is used to display the thrombosis diagnosis result and the treatment mode.

9. The heated air therapy device according to claim 8, characterized in that: The control device is also used for: When receiving a treatment mode switching instruction, determining a target treatment mode corresponding to the treatment mode switching instruction; The air pump, the valve assembly and the heating module are controlled to operate according to the target treatment mode.

Images