Health monitoring method and system for smart pension, terminal and storage medium

Abstract

The invention provides a health monitoring method and system for smart old-age care, a terminal and a storage medium, and the method comprises the steps: collecting health data of a target user through health monitoring equipment, and reporting the health data to a side controller; performing data cleaning on the health data by using the side controller to obtain first health data of a target user; and sending the first health data of the target user to a trained health analysis model, processing the first health data by the health analysis model, and outputting a health analysis result of the target user. The health monitoring device collects the health data of the target user and then automatically reports the health data to the side controller, the side controller processes the health data to generate the first health data and sends the first health data to the health analysis model, and the health analysis model processes the first health data to generate the health analysis result. And the health monitoring efficiency of the old people in the nursing home is effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of information monitoring technology, and in particular to a health monitoring method, system, terminal and storage medium for smart elderly care. Background Art

[0002] In the existing technology, the health monitoring methods for the elderly in nursing homes mainly rely on medical staff to manually collect and record various health data, such as blood pressure, blood sugar, etc., and then organize them into paper files, and then doctors will analyze the health of the elderly based on the paper files. This method is not only time-consuming and laborious, but also difficult to achieve timely update, sharing and retrieval of data, resulting in low efficiency of health monitoring for the elderly in nursing homes.

[0003] Therefore, the prior art has defects and needs to be improved and developed. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a health monitoring method, device, terminal and storage medium for smart elderly care in view of the above-mentioned defects of the prior art, aiming to solve the problem of low efficiency of health monitoring of the elderly in nursing homes in the prior art.

[0005] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0006] In a first aspect, an embodiment of the present invention provides a health monitoring method for smart elderly care, the method comprising:

[0007] Using health monitoring equipment to collect health data of target users and report the health data to the side controller;

[0008] Using the edge controller to clean the health data to obtain first health data of the target user;

[0009] The first health data of the target user is sent to a trained health analysis model, and the health analysis result of the target user is output after being processed by the health analysis model.

[0010] In one embodiment, the health monitoring device includes a smart blood pressure meter, a smart blood glucose meter, a smart pillow, a smart thermometer, and a smart blood oximeter; the health monitoring device is used to collect health data of the target user, and the health data is reported to the side controller, including:

[0011] The smart blood pressure meter is used to collect the systolic and diastolic blood pressure of the target user, and the systolic and diastolic blood pressure are reported as health data to the side controller;

[0012] The smart blood glucose meter is used to collect the fasting blood glucose value of the target user, and the fasting blood glucose value is reported to the side controller as health data;

[0013] The intelligent thermometer is used to collect the body temperature of the target user, and the body temperature is reported to the side controller;

[0014] The smart oximeter is used to collect the blood oxygen saturation and pulse rate of the target user, and the blood oxygen saturation and pulse rate are reported to the side controller as health data.

[0015] In one implementation, the health analysis model is a multi-layer perceptron model; sending the first health data of the target user to a trained health analysis model, processing the health analysis model, and outputting a health analysis result of the target user includes:

[0016] Sending the first health data to an input layer of a trained multi-layer perceptron model, and transmitting the first health data to a hidden layer of the multi-layer perceptron model via the input layer;

[0017] Processing the first health data using the hidden layer to obtain a first health feature;

[0018] The first health feature is input into the output layer of the multi-layer perceptron model, and is processed by the output layer to obtain a health analysis result of the target user.

[0019] In one embodiment, the training step of the health analysis model includes:

[0020] Constructing an initial health analysis model, wherein the initial health analysis model is a multi-layer perceptron model;

[0021] Acquire a training data set, wherein the training data set includes systolic blood pressure, diastolic blood pressure, fasting blood glucose value, body temperature, blood oxygen saturation and pulse rate of multiple users;

[0022] The initial health analysis model is trained using the training data set until the loss function converges to a preset value, thereby obtaining a trained health analysis model.

[0023] In one embodiment, the method further comprises:

[0024] Generate a health report by combining the health analysis result and the health data of the target user;

[0025] The health report is sent to the target user's contacts via email, text message or app notification.

[0026] In one embodiment, the method further comprises:

[0027] Generate health recommendations for target users based on historical health analysis results and historical health data of target users;

[0028] The health advice is sent to the target user's corresponding medical staff via email, text message or application notification.

[0029] In one implementation, the health monitoring device and the side controller are connected via a distributed soft bus.

[0030] In a second aspect, an embodiment of the present invention further provides a health monitoring system for smart elderly care, including:

[0031] An information collection and reporting module is used to collect health data of target users using health monitoring equipment and report the health data to the side controller;

[0032] A data processing module, used for performing data cleaning on the health data using the edge controller to obtain first health data of a target user;

[0033] The result generation module is used to send the first health data of the target user to a trained health analysis model, and output the health analysis result of the target user after being processed by the health analysis model.

[0034] In a third aspect, an embodiment of the present invention further provides a terminal, comprising: a memory, a processor, and a health monitoring program for smart elderly care stored in the memory and executable on the processor, wherein the health monitoring program for smart elderly care implements the steps of the health monitoring method for smart elderly care as described above when executed by the processor.

[0035] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, which stores a health monitoring program for smart elderly care, and the health monitoring program for smart elderly care can be executed to implement the steps of the health monitoring method for smart elderly care as described above.

[0036] Beneficial effects of the present invention: The present invention collects the health data of the target user by using the health monitoring device, and reports the health data to the side controller; uses the side controller to clean the health data to obtain the first health data of the target user; sends the first health data of the target user to the trained health analysis model, and outputs the health analysis result of the target user after being processed by the health analysis model. The present invention collects the health data of the target user by the health monitoring device and automatically reports it to the side controller, and the side controller generates the first health data after processing and sends it to the health analysis model, and uses the health analysis model to process the first health data to generate the health analysis result, which effectively improves the efficiency of nursing homes in health monitoring of the elderly. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a flow chart of a preferred embodiment of the health monitoring method for smart elderly care in the present invention.

[0038] Figure 2 It is a functional principle block diagram of a preferred embodiment of the health monitoring system for smart elderly care in the present invention.

[0039] Figure 3 It is a terminal principle block diagram of the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0041] In the existing technology, the health monitoring methods for the elderly in nursing homes mainly rely on medical staff to manually collect and record various health data, such as blood pressure, blood sugar, etc., and then organize them into paper files, and then doctors will analyze the health of the elderly based on the paper files. This method is not only time-consuming and laborious, but also difficult to achieve timely update, sharing and retrieval of data, resulting in low efficiency of health monitoring for the elderly in nursing homes.

[0042] In view of the above-mentioned defects of the prior art, the present invention provides a health monitoring method, device, terminal and storage medium for smart elderly care, the method comprising: using a health monitoring device to collect the health data of a target user, and reporting the health data to a side controller; using the side controller to clean the health data to obtain the first health data of the target user; sending the first health data of the target user to a trained health analysis model, processing the health analysis model, and outputting the health analysis result of the target user. The present invention collects the health data of the target user through a health monitoring device and automatically reports it to the side controller, and the side controller generates the first health data after processing and sends it to the health analysis model, and uses the health analysis model to process the first health data to generate the health analysis result, which effectively improves the efficiency of health monitoring of the elderly in nursing homes.

[0043] See also Figure 1 The health monitoring method for smart elderly care described in the embodiment of the present invention comprises the following steps:

[0044] Step S100: Use a health monitoring device to collect health data of a target user, and report the health data to a side controller.

[0045] Specifically, health data refers to data that characterizes the health status of the user, such as blood pressure, blood sugar, body temperature, blood oxygen saturation, pulse rate, etc. The target users are elderly people in nursing homes. The present invention distributes health monitoring equipment in nursing homes, so that target users can use health monitoring equipment to collect health data independently, or they can ask corresponding medical staff to help collect data. Since the collected health data can be reported independently, it effectively avoids omissions or mistakes caused by negligence of medical staff. In addition, this method can also avoid the problems of difficulty in saving, querying and sharing caused by using paper to record health data.

[0046] In one implementation, the side controller may be a control device supporting the OpenHarmony operating system, which is an operating system developed based on the OpenHarmony system and has strong computing capabilities.

[0047] In one implementation, the health monitoring device includes an intelligent blood pressure meter, an intelligent blood glucose meter, an intelligent thermometer, and an intelligent blood oximeter; the health monitoring device is used to collect health data of the target user, and the health data is reported to the side controller, including:

[0048] The smart blood pressure meter is used to collect the systolic and diastolic blood pressure of the target user, and the systolic and diastolic blood pressure are reported as health data to the side controller;

[0049] The smart blood glucose meter is used to collect the fasting blood glucose value of the target user, and the fasting blood glucose value is reported to the side controller as health data;

[0050] The intelligent thermometer is used to collect the body temperature of the target user, and the body temperature is reported to the side controller;

[0051] The smart oximeter is used to collect the blood oxygen saturation and pulse rate of the target user, and the blood oxygen saturation and pulse rate are reported to the side controller as health data.

[0052] Specifically, the smart blood pressure meter, smart blood glucose meter, smart thermometer and smart oximeter in the present invention are public equipment and are distributed in nursing homes. The smart blood pressure meter, smart blood glucose meter, smart thermometer and smart oximeter all contain communication devices, which can transmit data between the side controller and the internal system of the nursing home. After the target user passes the identity authentication, he can use the health monitoring equipment to collect health data by himself, or the medical staff can collect it. It supports a variety of identity authentication methods, such as face recognition, card swiping, etc., which are not limited here.

[0053] In one implementation, the health monitoring device further includes a smart pillow; the smart pillow includes a sensor that supports collecting the user's sleep state to obtain the user's sleep duration; the method of collecting the health data of the target user using the health monitoring device and reporting the health data to the side controller further includes:

[0054] The sensor in the smart pillow is used to collect the sleep state of the target user, and the sleep duration is determined based on the sleep state, and the sleep duration is reported to the side controller as health data.

[0055] Specifically, the smart pillow is a personal device. When the smart pillow senses that the elderly person has entered a sleeping state, it starts to collect data to generate the elderly person's sleep duration for reporting. The present invention sets up different health monitoring devices in the nursing home, including both public equipment and personal equipment. Since the health data will be automatically uploaded to the side controller after collection, and then synchronized to the internal management system of the nursing home after processing by the side controller, it also overcomes the shortcomings of paper records that are easy to lose and difficult to save. It can be understood that the present invention can obtain more comprehensive data reflecting the health status of the elderly by combining a variety of health monitoring devices, thereby providing strong data support for subsequent health analysis results.

[0056] See also Figure 1 The health monitoring method for smart elderly care described in the embodiment of the present invention also includes the following steps:

[0057] Step S200: Utilize the edge controller to clean the health data to obtain the first health data of the target user.

[0058] Specifically, the number of side controllers of the present invention can be set according to the needs of the nursing home. For example, multiple side controllers can be set on floors with higher population density, and fewer side controllers can be set on floors with lower population density. After the side controller receives the health data of the target user, it first cleans the health data, which can effectively improve the quality of the data, reduce the bandwidth and time required to transmit the data to the health analysis model, and is conducive to improving the real-time and efficiency of data processing.

[0059] In one implementation, the method further includes:

[0060] After obtaining the first health data, if a data item in the first health data exceeds a corresponding first preset threshold or is lower than a corresponding second preset threshold, generating an alarm message;

[0061] The alarm information is sent to the medical staff corresponding to the target user in the nursing home.

[0062] Specifically, after obtaining the first health data, each data item in the first health data is compared with the corresponding preset threshold value. The first health data includes diastolic blood pressure, systolic blood pressure, fasting blood sugar value, body temperature, blood oxygen saturation, and pulse rate. Among them, the range of the first preset threshold value corresponding to the diastolic pressure is 95mmHg-100mmHg, and the range of the second preset threshold value corresponding to the diastolic pressure is 60mmHg-70mmHg; the range of the first preset threshold value corresponding to the systolic pressure is 160mmHg-180mmHg, and the range of the second preset threshold value corresponding to the systolic pressure is 60mmHg-70mmHg; the range of the first preset threshold value corresponding to the fasting blood glucose value is 7.0mmol / L-9.0mmol / L, and the range of the second preset threshold value corresponding to the fasting blood glucose value is 3.5mmol / L-4.0mmol / L; the range of the first preset threshold value corresponding to the body temperature is 38.0℃-39.0℃, and the range of the second preset threshold value corresponding to the body temperature is 33.0℃-34.0℃; the range of the second preset threshold value corresponding to the blood oxygen saturation is 92%-94%; the first preset threshold value corresponding to the pulse rate is 110 times / min, and the range of the second preset threshold value corresponding to the pulse rate is 45 times / min-55 times / min. It is understandable that the blood oxygen saturation only needs to give an alarm when it is lower than the second preset threshold.

[0063] In one implementation, the first health data also includes sleep duration.

[0064] Specifically, the first preset threshold range corresponding to the sleep duration is 12-15 hours, and the second preset threshold range is 3-4 hours.

[0065] The present invention sets a corresponding first preset threshold and a second preset threshold for each data item in the first health data, and compares the first health data with the corresponding preset threshold in a timely manner after receiving the first health data, so as to quickly identify any abnormal indicators that exceed or fall below the normal range or may indicate health risks, thereby realizing refined monitoring of the health status of the elderly. Such a design greatly shortens the time interval from health data monitoring to abnormality discovery and then to intervention response, providing faster and more effective health protection for the elderly.

[0066] In one implementation, when an alarm message is generated, a call will be made to the target user's corresponding medical staff, and the alarm message will be played in the form of voice.

[0067] Specifically, by making a phone call, medical staff can be notified quickly to intervene in the elderly in a timely manner, avoiding delays in treatment time and effectively ensuring the health and safety of the elderly in nursing homes. For example, when the elderly's fasting blood sugar value is found to be 3.3, an alarm message is immediately sent, and the elderly's corresponding medical staff is called and notified by voice, so that the medical staff can deal with the elderly's hypoglycemia in a timely manner, providing timely and effective health protection for the elderly.

[0068] See also Figure 1 The health monitoring method for smart elderly care described in the embodiment of the present invention also includes the following steps:

[0069] Step S300: Send the first health data of the target user to a trained health analysis model, and output a health analysis result of the target user after being processed by the health analysis model.

[0070] Specifically, the health analysis model is used to analyze and process the first health data, and the health analysis results of the target user can be directly obtained. In this way, the problem of low efficiency caused by doctors using paper records for analysis can be avoided. The health analysis model can be used to obtain health analysis results faster, which helps to take necessary health management measures in a timely manner. In addition, this method avoids the subjective limitations of manual analysis and ensures the consistency and accuracy of the analysis process.

[0071] In one implementation, the health analysis model is a multi-layer perceptron model; sending the first health data of the target user to a trained health analysis model, processing the health analysis model, and outputting a health analysis result of the target user includes:

[0072] Sending the first health data to an input layer of a trained multi-layer perceptron model, and transmitting the first health data to a hidden layer of the multi-layer perceptron model via the input layer;

[0073] Processing the first health data using the hidden layer to obtain a first health feature;

[0074] The first health feature is input into the output layer of the multi-layer perceptron model, and is processed by the output layer to obtain a health analysis result of the target user.

[0075] Specifically, the multilayer perceptron model includes an input layer, a hidden layer, and an output layer. The hidden layer in the multilayer perceptron model can capture the complex relationships in the health data, such as the interaction between different health data, changes in time trends, etc., through multiple layers of nonlinear transformations. These features (i.e., the first health features) are the basis for subsequent health analysis, and they play a key role in distinguishing different health states. By processing the first health data with a trained multilayer perceptron model (MLP, MultilayerPerceptron), a more accurate health analysis result can be obtained.

[0076] In one implementation, the health analysis results include: sub-health status, basic health status, good health status, excellent health status and outstanding health status.

[0077] In one implementation, the method further includes:

[0078] Synchronize the first health data of the target user to the internal system of the nursing home.

[0079] Specifically, while sending the first health data to the trained health analysis model, the first health data is synchronized to the internal system of the nursing home. The internal system of the nursing home is a comprehensive management platform, which stores the information of the nursing home, the basic information of the elderly in the nursing home, the living habits of the elderly, health characteristics, etc. It is used for medical staff to manage the elderly in the nursing home. After synchronizing the health data to the internal system of the nursing home, medical staff can check the health data of the elderly in a timely manner, which is convenient for formulating rehabilitation plans, daily life care and service arrangements, etc.

[0080] In one implementation, the internal system of the nursing home of the present invention uses a redis database to store data and is equipped with a timed synchronization mechanism. The first health data is backed up every other week, which can effectively resist the risk of data loss caused by hardware failure, human error or malicious attack, and effectively ensure the safe storage of the first health data.

[0081] In one implementation, the training step of the health analysis model includes:

[0082] Constructing an initial health analysis model, wherein the initial health analysis model is a multi-layer perceptron model;

[0083] Acquire a training data set, wherein the training data set includes systolic blood pressure, diastolic blood pressure, fasting blood glucose value, body temperature, blood oxygen saturation and pulse rate of multiple users;

[0084] The initial health analysis model is trained using the training data set until the loss function converges to a preset value, thereby obtaining a trained health analysis model.

[0085] Specifically, before obtaining the training data set, the training data set is first constructed. When constructing the training data set of the present invention, multi-dimensional health information from multiple elderly people is gathered, and the differences in the health status of different elderly people, the wide range of age distribution and the diversity of living habits are fully considered. This training data set not only comprehensively covers key health indicators such as blood pressure (including systolic and diastolic blood pressure), fasting blood glucose value, body temperature, blood oxygen saturation, pulse rate, etc., but also strives to reflect the complexity and diversity of the health status of the elderly. Therefore, the training data set of the present invention lays a solid and rich foundation for subsequent model training and health analysis, ensuring that it can deeply understand and accurately capture the various factors that affect the health of the elderly. During the training process, the back propagation algorithm is used to update the weights and biases of the initial health analysis model by comparing the error between the output of the initial health analysis model and the true label.

[0086] In one implementation, the training data set also includes sleep duration.

[0087] In one implementation, the method further includes:

[0088] Generate a health report by combining the health analysis result and the health data of the target user;

[0089] The health report is sent to the target user's contacts via email, text message or app notification.

[0090] Specifically, a health report is generated and sent to the contact of the target user in combination with the health data and health analysis results. In the health report, if there are abnormal indicators, the indicators will be displayed in bold. The contact of the target user is the contact registered in the nursing home. In this way, it is convenient for the contact to understand the health status of the elderly in a timely manner. In the present invention, the nursing home has corresponding management application software, which supports the contact of the target user to receive the health report after registration.

[0091] In one implementation, the method further includes:

[0092] Generate health recommendations for target users based on historical health analysis results and historical health data of target users;

[0093] The health advice is sent to the target user's corresponding medical staff via email, text message or application notification.

[0094] Specifically, after the health advice is generated, the health advice can be sent to the medical staff corresponding to the target user, so that the medical staff can supervise and adjust the target user's living habits, physical exercise, etc. according to the health advice. Historical health analysis results and historical health data support custom time intervals, such as one month, three months or half a year, etc., which are not restricted here. For example, if the sleep duration in the historical health data of the target user is less than 4 hours many times, a health advice will be generated. The health advice includes appropriately increasing exercise, such as slow walking, etc., and improving the diet structure, using more tryptophan-rich foods, such as milk, bananas, walnuts, etc. Medical staff will adjust the diet structure of the target user and formulate an appropriate exercise plan to improve the elderly's lack of sleep.

[0095] In one implementation, the method further includes:

[0096] Synchronize health analysis results, health reports and health recommendations to the nursing home’s internal system.

[0097] Specifically, when any of the health analysis results, health reports and health recommendations are generated, they will be synchronized to the internal system of the nursing home, so that doctors can follow up on the health of the target users in a timely manner. In this way, the problems of paper reports being difficult to save, difficult to retrieve and difficult to share in a timely manner can be effectively overcome. Even different doctors can monitor the health of the target users, which effectively improves the intelligence level of the nursing home and provides effective protection for the health of the elderly in the nursing home.

[0098] In one implementation, the health monitoring device and the side controller are connected via a distributed soft bus.

[0099] Specifically, health data reporting can be done through WIFI protocol, Bluetooth (BLE) protocol, etc. The built-in communication device of the health device can effectively interact with the side controller. In the side controller, the first health data can be input into the health analysis model through the MQTT protocol. The MQTT protocol is widely used in the field of the Internet of Things due to its lightweight, low bandwidth occupancy, and easy implementation. The present invention can effectively reduce the load of the network through the MQTT protocol, which is convenient for large-scale data transmission.

[0100] In summary, the present invention collects the health data of the target user by using a health monitoring device, and reports the health data to a side controller; uses the side controller to clean the health data to obtain the first health data of the target user; sends the first health data of the target user to a trained health analysis model, and outputs the health analysis result of the target user after being processed by the health analysis model. The present invention collects the health data of the target user by a health monitoring device and automatically reports it to the side controller, and the side controller generates the first health data after processing and sends it to the health analysis model, and uses the health analysis model to process the first health data to generate the health analysis result, which effectively improves the efficiency of nursing homes in monitoring the health of the elderly.

[0101] In one embodiment, if Figure 2 As shown, based on the above health monitoring method for smart elderly care, the present invention also provides a health monitoring system for smart elderly care, including:

[0102] The information collection and reporting module 100 is used to collect health data of the target user using the health monitoring device and report the health data to the side controller;

[0103] The data processing module 200 is used to clean the health data using the edge controller to obtain the first health data of the target user;

[0104] The result generation module 300 is used to send the first health data of the target user to a trained health analysis model, and output the health analysis result of the target user after being processed by the health analysis model.

[0105] In one embodiment, the health monitoring device includes an intelligent blood pressure meter, an intelligent blood glucose meter, an intelligent thermometer, and an intelligent blood oximeter; the information collection and reporting module includes:

[0106] A first collection and reporting unit is used to collect the systolic and diastolic blood pressure of the target user using the smart blood pressure meter, and report the systolic and diastolic blood pressure as health data to the side controller;

[0107] A second collection and reporting unit is used to collect the fasting blood glucose value of the target user using the smart blood glucose meter, and report the fasting blood glucose value as health data to the side controller;

[0108] A third collection and reporting unit, configured to collect the body temperature of the target user using the smart thermometer and report the body temperature to the side controller;

[0109] The fourth collection and reporting unit is used to use the intelligent blood oximeter to collect the blood oxygen saturation and pulse rate of the target user, and report the blood oxygen saturation and pulse rate as health data to the side controller.

[0110] In one embodiment, the health analysis model is a multi-layer perceptron model; the data processing module includes:

[0111] A data input unit, used to send the first health data to an input layer of a trained multi-layer perceptron model, and transmit the first health data to a hidden layer of the multi-layer perceptron model via the input layer;

[0112] a feature generating unit, configured to process the first health data using the hidden layer to obtain a first health feature;

[0113] The data analysis unit is used to input the first health feature into the output layer of the multi-layer perceptron model, and obtain the health analysis result of the target user through processing by the output layer.

[0114] In one embodiment, the system further comprises:

[0115] A first construction unit is used to construct an initial health analysis model, wherein the initial health analysis model is a multi-layer perceptron model;

[0116] A training set acquisition unit, used to acquire a training data set, wherein the training data set includes systolic blood pressure, diastolic blood pressure, fasting blood glucose value, body temperature, blood oxygen saturation and pulse rate of multiple users;

[0117] A model training unit is used to train the initial health analysis model using the training data set until the loss function converges to a preset value to obtain a trained health analysis model.

[0118] In one embodiment, the device further comprises:

[0119] a report generating unit, configured to generate a health report in combination with the health analysis result and the health data of the target user;

[0120] The report sending unit is used to send the health report to the contact of the target user by email, SMS or application notification.

[0121] In one embodiment, the device further comprises:

[0122] A suggestion generating unit, used for generating health suggestions for a target user based on the historical health analysis results and historical health data of the target user;

[0123] The advice sending unit is used to send the health advice to the medical staff corresponding to the target user in the form of email, text message or application notification.

[0124] Based on the above embodiment, the present invention further provides a terminal, whose principle block diagram can be shown as follows: Figure 3 As shown. The terminal includes a processor, a memory, a network interface and a display screen connected via a device bus. Among them, the processor of the terminal is used to provide computing and control capabilities. The memory of the terminal includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating device and a health monitoring program for smart elderly care. The internal memory provides an environment for the operation of the operating device and the health monitoring program for smart elderly care in the non-volatile storage medium. The network interface of the terminal is used to communicate with an external terminal through a network connection. When the health monitoring program for smart elderly care is executed by the processor, the steps of any one of the above-mentioned health monitoring methods for smart elderly care are implemented. The display screen of the terminal can be a liquid crystal display screen or an electronic ink display screen.

[0125] Those skilled in the art will understand that Figure 3 The principle block diagram shown in the figure is only a block diagram of a partial structure related to the scheme of the present invention, and does not constitute a limitation on the terminal to which the scheme of the present invention is applied. The specific terminal may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0126] In one embodiment, a terminal is provided, which includes a memory, a processor, and a health monitoring program for smart elderly care stored in the memory and executable on the processor. When the health monitoring program for smart elderly care is executed by the processor, the steps of any one of the health monitoring methods for smart elderly care provided in the embodiments of the present invention are implemented.

[0127] An embodiment of the present invention also provides a computer-readable storage medium, on which a health monitoring program for smart elderly care is stored. When the health monitoring program for smart elderly care is executed by a processor, the steps of any one of the health monitoring methods for smart elderly care provided in the embodiment of the present invention are implemented.

[0128] It should be understood that the serial numbers of the steps in the above embodiments do not imply a sequence of execution, and the execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0129] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the above-mentioned device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention. The specific working process of the units and modules in the above-mentioned device can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0130] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0131] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0132] In the embodiments provided by the present invention, it should be understood that the disclosed apparatus / terminal equipment and method can be implemented in other ways. For example, the apparatus / terminal equipment embodiments described above are only illustrative, for example, the division of the above modules or units is only a logical function division, and in actual implementation, other division methods can be used, for example, multiple units or components can be combined or integrated into another apparatus, or some features can be ignored or not executed.

[0133] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features therein may be replaced by equivalents. However, these modifications or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A health monitoring method for smart elderly care, characterized in that: The method comprises: Using health monitoring equipment to obtain health data of the target user, and reporting the health data to the side controller; Using the edge controller to clean the health data to obtain first health data of the target user; The first health data of the target user is sent to a trained health analysis model, and the health analysis result of the target user is output after being processed by the health analysis model.

2. The health monitoring method for smart elderly care according to claim 1, characterized in that: The health monitoring equipment includes an intelligent blood pressure meter, an intelligent blood glucose meter, an intelligent thermometer and an intelligent blood oximeter; The method of collecting health data of a target user by using a health monitoring device and reporting the health data to a side controller includes: The smart blood pressure meter is used to collect the systolic and diastolic blood pressure of the target user, and the systolic and diastolic blood pressure are reported as health data to the side controller; The smart blood glucose meter is used to collect the fasting blood glucose value of the target user, and the fasting blood glucose value is reported to the side controller as health data; The intelligent thermometer is used to collect the body temperature of the target user, and the body temperature is reported to the side controller; The smart oximeter is used to collect the blood oxygen saturation and pulse rate of the target user, and the blood oxygen saturation and pulse rate are reported to the side controller as health data.

3. The health monitoring method for smart elderly care according to claim 1, characterized in that: The health analysis model is a multi-layer perceptron model; sending the first health data of the target user to the trained health analysis model, processing the health analysis model, and outputting the health analysis result of the target user includes: Sending the first health data to an input layer of a trained multi-layer perceptron model, and transmitting the first health data to a hidden layer of the multi-layer perceptron model via the input layer; Processing the first health data using the hidden layer to obtain a first health feature; The first health feature is input into the output layer of the multi-layer perceptron model, and is processed by the output layer to obtain a health analysis result of the target user.

4. The health monitoring method for smart elderly care according to claim 1, characterized in that: The training steps of the health analysis model include: Constructing an initial health analysis model, wherein the initial health analysis model is a multi-layer perceptron model; Acquire a training data set, wherein the training data set includes systolic blood pressure, diastolic blood pressure, fasting blood glucose value, body temperature, blood oxygen saturation and pulse rate of multiple users; The initial health analysis model is trained using the training data set until the loss function converges to a preset value, thereby obtaining a trained health analysis model.

5. The health monitoring method for smart elderly care according to claim 1, characterized in that: The method further comprises: generating a health report by combining the health analysis result and the first health data of the target user; The health report is sent to the target user's contacts via email, text message or app notification.

6. The health monitoring method for smart elderly care according to claim 1, characterized in that: The method further comprises: Generate health recommendations for target users based on historical health analysis results and historical health data of target users; The health advice is sent to the target user's corresponding medical staff via email, text message or application notification.

7. The health monitoring method for smart elderly care according to claim 1, characterized in that: The health monitoring device and the side controller are connected via a distributed soft bus.

8. A health monitoring system for smart elderly care, characterized in that: include: An information collection and reporting module is used to collect health data of target users using health monitoring equipment and report the health data to the side controller; A data processing module, used for performing data cleaning on the health data using the edge controller to obtain first health data of a target user; The result generation module is used to send the first health data of the target user to a trained health analysis model, and output the health analysis result of the target user after being processed by the health analysis model.

9. A terminal, characterized in that: The terminal includes a memory, a processor, and a health monitoring program for smart elderly care stored in the memory and executable on the processor. When the health monitoring program for smart elderly care is executed by the processor, the steps of the health monitoring method for smart elderly care as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a health monitoring program for smart elderly care. When the health monitoring program for smart elderly care is executed by the processor, the steps of the health monitoring method for smart elderly care as described in any one of claims 1 to 7 are implemented.

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