Intelligent wearable system for monitoring moisture of heart failure patient
By designing an intelligent wearable system that integrates sensors and deep learning technology, it solves the problem that it is difficult for heart failure patients to monitor and manage water intake, and realizes accurate monitoring of water in patients with heart failure and personalized health management to prevent water retention and improve quality of life.
Patent Information
- Application Number
- CN202411675940.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-22
- Publication Date
- 2025-03-07
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
It is difficult for patients with heart failure to effectively monitor and manage water intake, resulting in serious consequences such as water retention.
An intelligent wearable system for moisture monitoring in patients with heart failure is designed, including sensors, data acquisition and transmission units, personalized suggestions generation units, real-time monitoring and feedback units, and daily information recording units. The system uses pressure sensors, humidity sensors, temperature sensors and heart rate monitors to monitor the moisture intake of heart failure patients in real time, and uses deep learning and pattern recognition technology to extract and identify features to generate personalized moisture intake suggestions.
Accurate monitoring of water in patients with heart failure has been achieved, helping patients better control water intake, prevent the occurrence of water retention, and provide patients with personalized health management services to improve quality of life and prevent the occurrence of complications.
Smart Images
Figure CN119564156A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of smart wearable systems, and in particular to a smart wearable system for monitoring moisture content in patients with heart failure. Background Art
[0002] Heart failure is a serious cardiovascular disease. Its main pathophysiological feature is the weakening of the heart's pumping function, which leads to ischemia and hypoxia of tissues and organs throughout the body. Water retention is one of the common complications in patients with heart failure, which in severe cases can lead to serious consequences such as pulmonary edema and pericardial effusion.
[0003] Therefore, it is crucial to monitor and manage water intake in patients with heart failure.
[0004] In view of this, this patent proposes an intelligent wearable system for water monitoring in patients with heart failure. Summary of the invention
[0005] The embodiment of the present application provides a smart wearable system for monitoring moisture content in patients with heart failure to solve the above-mentioned technical problems.
[0006] The present application provides an intelligent wearable system for monitoring water content in patients with heart failure, comprising a sensor, a data acquisition and transmission unit, a personalized suggestion generation unit, a real-time monitoring and feedback unit, and a daily information recording unit, wherein the sensor comprises a pressure sensor and a wearable device, wherein the wearable device comprises a humidity sensor, a temperature sensor, and a heart rate monitor, the wearable device is worn on the patient with heart failure, and the pressure sensor is placed at the bottom of the water dispenser of the patient with heart failure; wherein the humidity sensor is used to monitor the sweat evaporation of the patient with heart failure, and the temperature sensor is used to monitor the body temperature of the patient with heart failure; the pressure sensor is used to monitor the amount of water drunk by the patient with heart failure, and the heart rate monitor is used to monitor the heart rate of the patient with heart failure; the pressure sensor establishes a wireless communication connection with the data acquisition and transmission unit, and the wireless communication connection is established between the wearable device and the data acquisition and transmission unit; the data acquisition and transmission unit is used to collect the The real-time moisture data monitored by the pressure sensor and the wearable device, and feature extraction and identification of the real-time moisture data based on deep learning and pattern recognition, so as to analyze the water intake of the heart failure patient; the personalized suggestion generation unit is used to generate personalized water intake suggestions for the heart failure patient according to the water intake of the heart failure patient, the physiological characteristics of the heart failure patient, and the medical history of the heart failure patient analyzed by the data acquisition and transmission unit; the real-time monitoring and feedback unit is used to send the water intake of the heart failure patient collected by the data acquisition and transmission unit to the doctor in real time, and to feed back the personalized water intake suggestions to the heart failure patient; the daily information recording unit is used to record and transmit the activity level, sleep quality and body mass index of the heart failure patient to the doctor, so as to serve as reference data for the doctor to formulate a treatment plan and adjust the drug dosage for the heart failure patient.
[0007] Furthermore, the feature extraction and recognition of the real-time water data based on deep learning and pattern recognition to analyze the water intake of the heart failure patient includes: The real-time moisture data is trained by a deep learning algorithm to extract node features and edge point features of the real-time moisture data, wherein the global domain overlapping feature in the edge point feature refers to the number of paths with different path lengths between two nodes; Based on the node features and the edge features of the real-time moisture data, the water loss and water intake of the heart failure patient are identified through a pattern recognition algorithm; wherein, the identification of the water loss and water intake of the heart failure patient through a pattern recognition algorithm includes: calculating an offset based on the PID parameters output by an automatic correction PID algorithm; determining the water loss and water intake of the heart failure patient based on the offset and the node features and the edge features of the real-time moisture data.
[0008] Further, the determining of the water loss and water intake of the heart failure patient based on the offset and the node features and the edge features of the real-time water data includes: Standardizing the offset and the node features and edge point features of the real-time moisture data;
[0009] The standardized offset and the node features and the edge features of the real-time moisture data are used as the input layer, and the moisture loss and the moisture intake of the heart failure patient are used as the output layer, and a neural network is used for training. When the parameters inside the neural network prediction model make the prediction accuracy greater than or equal to the preset accuracy, it is determined that the neural network training is completed; The neural network is divided into an input layer, a hidden layer and an output layer. The number of units in the input layer is the number of input parameter data. The activation function used in the hidden layer is a sigmoid function.
[0010] Furthermore, the hidden layer includes multiple layers, wherein the number of nodes in the first hidden layer is equal to twice the number of units in the input layer, and the number of nodes in each subsequent hidden layer is gradually reduced by half.
[0011] Furthermore, the output manipulated variable calculated based on the automatic correction PID algorithm is the sum of the proportional term, the integral term and the differential term.
[0012] Further, the data acquisition and transmission unit includes a heart rate data correction module; Among them, the heart rate data correction module is used to correct the collected heart rate data of the heart failure patient using a bidirectional long short-term memory network based on the activity level, sleep quality and body mass index of the heart failure patient.
[0013] Furthermore, the wireless communication connection includes one or more of Bluetooth connection, NFC connection, Wi-Fi connection, ZigBee connection, 2G connection, 3G connection, 4G connection, 5G connection or UWB connection.
[0014] Furthermore, the smart wearable system for monitoring water intake for heart failure patients also includes a wearable device interaction interface, which is used for the heart failure patient to view the water intake status and the personalized water intake recommendations, and for the heart failure patient to perform interactive operations, wherein the interactive operations include setting reminder functions and recording water intake.
[0015] Furthermore, the smart wearable system for monitoring moisture content in heart failure patients also includes an alarm module, which is used to send the abnormal heart rate alarm message to the doctor side when receiving the abnormal heart rate alarm message sent by the data acquisition and transmission unit, wherein the abnormal heart rate alarm message carries the real-time location information of the heart failure patient.
[0016] Based on the embodiments provided by the present application, in combination with sensors, data acquisition and transmission units, personalized suggestion generation units, real-time monitoring and feedback units, and daily information recording units, real-time intelligent monitoring and management of water intake is provided for heart failure patients, and accurate monitoring of water intake in heart failure patients is achieved, helping heart failure patients to better control water intake and prevent water retention. At the same time, the smart wearable water monitoring system for heart failure patients provided by the present application can also, that is, the smart wearable water monitoring system for heart failure patients provided by the present application provides patients with personalized health management services to improve the quality of life of heart failure patients and prevent the occurrence of complications. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] The drawings described herein are used to provide a further understanding of the embodiments of the present invention and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 This is a structural diagram of an optional smart wearable system for monitoring moisture in patients with heart failure according to an embodiment of the present application; Figure 2 This is an optional flowchart for feature extraction and recognition of real-time moisture data based on deep learning and pattern recognition according to an embodiment of the present application.
[0018] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION
[0019] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.
[0020] Alternatively, if Figure 1As shown, the present application provides a smart wearable system for monitoring moisture in patients with heart failure, characterized in that it includes a sensor 101, a data acquisition and transmission unit 102, a personalized suggestion generation unit 103, a real-time monitoring and feedback unit 104, and a daily information recording unit 105; The sensor 101 includes a pressure sensor and a wearable device, wherein the wearable device includes a humidity sensor, a temperature sensor and a heart rate monitor, the wearable device is worn on a heart failure patient, and the pressure sensor is placed at the bottom of a water dispenser of the heart failure patient; Among them, the humidity sensor is used to monitor the sweat evaporation of the heart failure patient, and the temperature sensor is used to monitor the body temperature of the heart failure patient; the pressure sensor is used to monitor the water intake of the heart failure patient, and the heart rate monitor is used to monitor the heart rate of the heart failure patient; the pressure sensor establishes a wireless communication connection with the data acquisition and transmission unit 102, and the wearable device establishes a wireless communication connection with the data acquisition and transmission unit 102; The data acquisition and transmission unit 102 is used to collect real-time water data monitored by the pressure sensor and the wearable device, and to extract and identify features of the real-time water data based on deep learning and pattern recognition to analyze the water intake of heart failure patients; The personalized suggestion generating unit 103 is used to generate personalized water intake suggestions for the heart failure patient according to the water intake of the heart failure patient, the physiological characteristics of the heart failure patient, and the medical history of the heart failure patient analyzed by the data collecting and transmitting unit 102; The real-time monitoring and feedback unit 104 is used to send the water intake of the heart failure patient collected by the data collection and transmission unit 102 to the doctor in real time, and to feed back personalized water intake suggestions to the heart failure patient; The daily information recording unit 105 is used to record and transmit the activity level, sleep quality and body mass index of the heart failure patient to the doctor side, so as to serve as reference data for the doctor side to formulate treatment plans and adjust drug dosages for the heart failure patient.
[0021] In some embodiments of the present application, the wearable device can display the heart rate data of the heart failure patient in real time, so that the heart failure patient can keep an eye on his or her health status at any time. Since it is a wearable device, the heart failure patient can use it anytime and anywhere, without being restricted by time and place. In addition, the wearable device can be connected to other devices such as smartphones to transmit the monitoring data to the mobile application of the heart failure patient for further analysis and management.
[0022] Based on the embodiments provided by the present application, in combination with sensors, data acquisition and transmission units, personalized suggestion generation units, real-time monitoring and feedback units, and daily information recording units, real-time intelligent monitoring and management of water intake is provided for heart failure patients, and accurate monitoring of water intake in heart failure patients is achieved, helping heart failure patients to better control water intake and prevent water retention. At the same time, the smart wearable water monitoring system for heart failure patients provided by the present application can also, that is, the smart wearable water monitoring system for heart failure patients provided by the present application provides patients with personalized health management services to improve the quality of life of heart failure patients and prevent the occurrence of complications.
[0023] Furthermore, if Figure 2 As shown in the figure, the real-time water data is extracted and identified based on deep learning and pattern recognition to analyze the water intake of heart failure patients, including: S201, training the real-time moisture data through a deep learning algorithm to extract node features and edge features of the real-time moisture data, wherein the global domain overlapping feature in the edge feature refers to the number of paths with different path lengths between two nodes; S202, based on the node characteristics and edge point characteristics of the real-time moisture data, the amount of water loss and water intake of the heart failure patient is identified through a pattern recognition algorithm; wherein, the amount of water loss and water intake of the heart failure patient is identified through a pattern recognition algorithm, including: calculating an offset based on the PID parameters output by an automatic correction PID algorithm; determining the amount of water loss and water intake of the heart failure patient based on the offset and the node characteristics and edge point characteristics of the real-time moisture data.
[0024] Among them, the automatic correction PID algorithm can output PID parameters based on the following expression: = ; in, is the PID parameter at the kth sampling moment, is the actual offset obtained by the automatic correction PID algorithm at the kth sampling moment, is the actual offset obtained by the automatic correction PID algorithm at the (k-1)th sampling moment, is the proportionality coefficient, is the integration coefficient, is the differential coefficient.
[0025] Furthermore, the global domain overlap feature I is calculated based on the following expression: ; Among them, A is the adjacency matrix, S represents the number of paths with different path lengths between two nodes, and B is the adjustment factor.
[0026] Furthermore, based on the offset and the node features and edge features of the real-time water data, the water loss and water intake of the heart failure patient are determined, including: Standardize the node and edge features of offset and real-time moisture data; The standardized offset and the node features and edge features of the real-time water data are used as the input layer, and the water loss and water intake of the heart failure patients are used as the output layer. The neural network is used for training. When the parameters inside the neural network prediction model make the prediction accuracy greater than or equal to the preset accuracy, the neural network training is determined to be completed. The neural network is divided into an input layer, a hidden layer, and an output layer. The number of units in the input layer is the number of input parameter data. The activation function used in the hidden layer is the sigmoid function. The formula of the sigmoid function is as follows: ; In the formula, is the category index value, and the j specific indicators corresponding to the i-th category layer indicator are fused through the sigmoid average formula; , ,..., is the index value that needs to be fused by the sigmoid formula, 1≤j≤k; ( ) is the inverse function of f( ).
[0027] Furthermore, the hidden layer includes multiple layers, wherein the number of nodes in the first hidden layer is equal to twice the number of units in the input layer, and the number of nodes in each subsequent hidden layer is gradually reduced by half.
[0028] Furthermore, the output manipulated variable calculated based on the automatic correction PID algorithm is the sum of the proportional term, the integral term and the differential term.
[0029] Further, the data acquisition and transmission unit includes a heart rate data correction module; Among them, the heart rate data correction module is used to correct the collected heart rate data of heart failure patients based on the activity level, sleep quality and body mass index of heart failure patients using a bidirectional long short-term memory network.
[0030] Further, the wireless communication connection includes one or more of Bluetooth connection, NFC connection, Wi-Fi connection, ZigBee connection, 2G connection, 3G connection, 4G connection, 5G connection or UWB connection.
[0031] Furthermore, the smart wearable system for monitoring water intake in heart failure patients also includes a wearable device interaction interface, which is used for heart failure patients to view their water intake status and personalized water intake recommendations, and for heart failure patients to perform interactive operations, wherein the interactive operations include setting reminder functions and recording water intake.
[0032] Furthermore, the smart wearable system for monitoring moisture content in heart failure patients also includes an alarm module, which is used to send an abnormal heart rate alarm message to the doctor when receiving the abnormal heart rate alarm message sent by the data acquisition and transmission unit, wherein the abnormal heart rate alarm message carries the real-time location information of the heart failure patient.
[0033] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.
Claims
1. A smart wearable system for monitoring moisture in patients with heart failure, characterized in that: It includes sensors, data collection and transmission units, personalized suggestion generation units, real-time monitoring and feedback units, and daily information recording units; The sensor includes a pressure sensor and a wearable device, wherein the wearable device includes a humidity sensor, a temperature sensor and a heart rate monitor, the wearable device is worn on a heart failure patient, and the pressure sensor is placed at the bottom of a water dispenser of the heart failure patient; Wherein, the humidity sensor is used to monitor the sweat evaporation of the heart failure patient, and the temperature sensor is used to monitor the body temperature of the heart failure patient; the pressure sensor is used to monitor the amount of water drunk by the heart failure patient, and the heart rate monitor is used to monitor the heart rate of the heart failure patient; the pressure sensor establishes a wireless communication connection with the data acquisition and transmission unit, and the wearable device establishes the wireless communication connection with the data acquisition and transmission unit; The data acquisition and transmission unit is used to collect the real-time moisture data monitored by the pressure sensor and the wearable device, and perform feature extraction and recognition on the real-time moisture data based on deep learning and pattern recognition to analyze the moisture intake of the heart failure patient; The personalized suggestion generating unit is used to generate personalized water intake suggestions for the heart failure patient according to the water intake of the heart failure patient, the physiological characteristics of the heart failure patient, and the medical history of the heart failure patient obtained by the data acquisition and transmission unit analysis; The real-time monitoring and feedback unit is used to send the water intake of the heart failure patient collected by the data collection and transmission unit to the doctor in real time, and to feed back the personalized water intake recommendation to the heart failure patient; The daily information recording unit is used to record and transmit the activity level, sleep quality and body mass index of the heart failure patient to the doctor side, so as to serve as reference data for the doctor side to formulate a treatment plan and adjust the drug dosage for the heart failure patient.
2. The smart wearable system for monitoring moisture in patients with heart failure according to claim 1, characterized in that: The feature extraction and recognition of the real-time water data based on deep learning and pattern recognition to analyze the water intake of the heart failure patient includes: The real-time moisture data is trained by a deep learning algorithm to extract node features and edge point features of the real-time moisture data, wherein the global domain overlapping feature in the edge point feature refers to the number of paths with different path lengths between two nodes; Based on the node features and the edge features of the real-time moisture data, the water loss and water intake of the heart failure patient are identified through a pattern recognition algorithm; wherein, the identification of the water loss and water intake of the heart failure patient through a pattern recognition algorithm includes: calculating an offset based on the PID parameters output by an automatic correction PID algorithm; determining the water loss and water intake of the heart failure patient based on the offset and the node features and the edge features of the real-time moisture data.
3. The smart wearable system for monitoring moisture in patients with heart failure according to claim 2, characterized in that: The step of determining the water loss and water intake of the heart failure patient based on the offset and the node features and the edge features of the real-time water data includes: Standardizing the offset and the node features and edge point features of the real-time moisture data; The standardized offset and the node features and the edge features of the real-time moisture data are used as the input layer, and the moisture loss and the moisture intake of the heart failure patient are used as the output layer, and a neural network is used for training. When the parameters inside the neural network prediction model make the prediction accuracy greater than or equal to the preset accuracy, it is determined that the neural network training is completed; The neural network is divided into an input layer, a hidden layer and an output layer. The number of units in the input layer is the number of input parameter data. The activation function used in the hidden layer is a sigmoid function.
4. The smart wearable system for monitoring moisture in patients with heart failure according to claim 3, characterized in that: The hidden layer includes multiple layers, wherein the number of nodes in the first hidden layer is equal to twice the number of units in the input layer, and the number of nodes in each subsequent hidden layer is gradually reduced by half.
5. The smart wearable system for monitoring moisture in patients with heart failure according to claim 2, characterized in that: The output manipulated variable calculated based on the automatic correction PID algorithm is the sum of the proportional term, the integral term and the differential term.
6. The smart wearable system for monitoring moisture in patients with heart failure according to claim 1, characterized in that: The data acquisition and transmission unit includes a heart rate data correction module; Among them, the heart rate data correction module is used to correct the collected heart rate data of the heart failure patient using a bidirectional long short-term memory network based on the activity level, sleep quality and body mass index of the heart failure patient.
7. The smart wearable system for monitoring moisture in patients with heart failure according to claim 1, characterized in that: The wireless communication connection includes one or more of a Bluetooth connection, an NFC connection, a Wi-Fi connection, a ZigBee connection, a 2G connection, a 3G connection, a 4G connection, a 5G connection, or a UWB connection.
8. The smart wearable system for monitoring moisture in patients with heart failure according to claim 1, characterized in that: The smart wearable system for monitoring water intake in heart failure patients also includes a wearable device interaction interface, which is used to provide the heart failure patient with a method of viewing the water intake status and the personalized water intake recommendations, and to provide the heart failure patient with a method of performing interactive operations, wherein the interactive operations include setting a reminder function and recording the amount of water drunk.
9. The smart wearable system for monitoring moisture in patients with heart failure according to claim 1, characterized in that: The smart wearable system for monitoring moisture in patients with heart failure also includes an alarm module, which is used to send the abnormal heart rate alarm message to the doctor end when receiving the abnormal heart rate alarm message sent by the data acquisition and transmission unit; Wherein, the abnormal heart rate alarm message carries the real-time location information of the heart failure patient.