Intelligent paper diaper cloud health data management method and system

Abstract

The invention relates to the technical field of medical health monitoring, in particular to an intelligent paper diaper cloud health data management method and system, biomarker data in urine of a wearer is collected through a flexible electrochemical sensor integrated in a paper diaper, and the biomarker data is sent to a mobile terminal through wireless communication after being processed by a micro-processing unit. And the mobile terminal encrypts and uploads the data to the cloud health data management platform. And the cloud platform performs cleaning, feature extraction and health assessment on the data, generates a health state analysis result and abnormal early warning information, and stores related data in a personal health file of the user to realize trend analysis and historical tracing. The invention further provides a corresponding system structure which supports multi-index collaborative detection, hierarchical authority access and model self-learning optimization, is suitable for scenes such as home care, old-age care institutions and medical health management, and has the advantages of high detection sensitivity, high intelligent degree and high data security.

Description

Technical Field

[0001] This invention relates to the field of medical and health monitoring technology, and in particular to a cloud-based health data management method and system for smart diapers. Background Technology

[0002] The elderly with disabilities, those with diabetes, gout, and chronic kidney disease, among others, have placed greater demands on intelligent nursing care methods. Traditional diapers only have a passive absorption function and cannot provide real-time health feedback and disease warning information, which is not conducive to early intervention and individualized care.

[0003] In recent years, the development of flexible electronics, nanomaterials, and the Internet of Things (IoT) has provided new pathways for the intelligent upgrading of health monitoring equipment. In particular, urine analysis systems based on electrochemical sensors, due to their non-invasive and continuous characteristics, have gradually become one of the key technologies for chronic disease monitoring. However, current market products still suffer from problems such as insufficient sensitivity, data silos, weak communication capabilities, and difficulty in personalized interpretation, making it difficult to meet the dual needs of clinical applications and home care.

[0004] Therefore, there is an urgent need to develop an intelligent diaper system with flexible sensing, high-sensitivity data acquisition, cloud-based intelligent analysis, and personalized health management capabilities to achieve continuous monitoring of urine biochemical indicators, remote data analysis, and real-time early warning of health status. Summary of the Invention

[0005] This invention aims to provide a cloud-based health data management method and system for smart diapers, which can collect and wirelessly transmit biomarkers in users' urine in real time, and complete data analysis, health assessment, abnormality warning and personalized file storage through a cloud platform, thereby improving the quality of life and health management level of the elderly and people with chronic diseases.

[0006] The technical solution is as follows: A cloud-based health data management method for smart diapers, comprising the following steps: S1: By using a flexible electrochemical sensor module integrated into the smart diaper, information on at least one biomarker parameter in the wearer's urine is collected in real time. The biomarker includes one or more of urinary glucose, uric acid, electrolyte ions, and dopamine. S2: The microprocessor unit installed in the smart diaper performs signal calibration, noise filtering, and digital-to-analog conversion on the raw signals collected by the sensor to generate standardized test data, and adds time stamps and user identification marks to the data; S3: The standardized detection data is sent to the mobile terminal device bound to the smart diaper via a low-power wireless communication module; S4: The health data management application running on the mobile terminal encrypts and encapsulates the received detection data and uploads it to the cloud-based health data management platform; S5: The cloud-based health data management platform performs data cleaning, feature extraction, and multi-dimensional analysis on the uploaded data, and generates an assessment result of the user's current health status based on a pre-trained health assessment model; S6: Determine whether there is a risk of health abnormality based on the analysis results. When the test results exceed the preset threshold, trigger the health early warning mechanism and generate risk warning information; S7: The health status assessment results and early warning information are simultaneously pushed to the user terminal or the authorized caregiver terminal, and the complete data is stored in the user's personal health record for subsequent trend analysis and historical tracing.

[0007] As a further aspect of the present invention, in step S1, the flexible electrochemical sensor adopts a three-electrode structure based on a composite conductive material of nano-silver paste and graphene, and guides urine to directionally contact the sensing area through a superhydrophobic microstructure to improve detection sensitivity and repeatability.

[0008] As a further aspect of the present invention, in step S5, the health assessment model is a chronic disease risk prediction model that integrates time series analysis and machine learning algorithms, used to identify the changing trends of urine biomarkers and assess the potential risk level of diabetes, kidney disease or gout.

[0009] As a further aspect of the present invention, in step S6, the health warning mechanism determines the confidence interval based on multiple consecutive detection results to exclude occasional abnormal data and reduce the false alarm rate.

[0010] As a further aspect of the present invention, in step S7, the health status assessment results are displayed on the mobile terminal in a graphical manner, and a health report containing the trend of changes in detection indicators and the level of health recommendations is generated.

[0011] As a further aspect of the present invention, the cloud-based health data management platform is equipped with a hierarchical access control mechanism, allowing users to grant corresponding levels of health data access permissions to doctors, nurses, or family members based on authorization policies.

[0012] A cloud-based health data management system for smart diapers, the system comprising: The intelligent diaper terminal integrates a flexible electrochemical sensor module, a microprocessor module, a power management module, and a wireless communication module. Mobile terminal devices are used to receive data from smart diapers and communicate with the cloud platform; A cloud-based health data management platform is used to perform data analysis, health assessment, risk warning, and health record management. The user interaction module is used for health data display, abnormal alerts, and authorization management. The data security module is used to implement encrypted data transmission and access control.

[0013] As a further aspect of the present invention, the cloud-based health data management platform further includes a model self-learning module, which is used to continuously optimize the health assessment model based on historical health data in order to improve the accuracy of personalized health prediction.

[0014] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: 1. By organically combining flexible electrochemical sensors, wireless communication technology, mobile applications, and a cloud-based health data platform, an integrated system with real-time multi-indicator data acquisition, remote intelligent analysis, health risk warning, and personalized data management functions has been constructed, significantly improving the intelligence level of traditional diapers; 2. It achieves biomarker detection with micromolar-level sensitivity, possesses excellent signal stability and wearability, and introduces a deep learning health assessment model to dynamically model and predict the early risks of chronic diseases. Simultaneously, the system supports cross-platform data synchronization, multi-role access permissions, graphical visual interaction, and report export, meeting the needs of various scenarios such as medical institutions and home care. 3. In terms of data security, end-to-end encryption, RBAC access control, and federated learning mechanisms are adopted to ensure user privacy and information integrity. Attached Figure Description

[0015] Figure 1 Flowchart of cloud-based health data management method for smart diapers; Figure 2 Structure diagram of the cloud-based health data management system for smart diapers; Figure 3 Diagram of the health risk warning trigger mechanism. Detailed Implementation

[0016] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0017] In embodiments of the present invention, the words "exemplarily," "for example," etc., are used to indicate that they are examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0018] In the embodiments of this invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the distinction is not emphasized, their intended meanings are consistent. Similarly, "of", "corresponding (relevant)" and "corresponding" can sometimes be used interchangeably. It should be noted that when the distinction is not emphasized, their intended meanings are consistent.

[0019] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0020] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0021] Example 1 This embodiment provides a smart diaper health monitoring system suitable for home use by the elderly or patients with chronic diseases. The diaper has a flexible electrochemical sensor pre-embedded in the urine contact area. This sensor is based on a flexible polyimide (PI) substrate, and its surface is constructed with a three-electrode structure: a working electrode, a reference electrode, and a counter electrode. The electrodes are printed with a graphene-silver nanoparticle composite conductive material using screen printing, and further modified with a nano-enzyme catalytic layer specific to urinary glucose and uric acid to enhance the specific recognition and current response of the target substances.

[0022] The sensor is connected to a miniature embedded processor (MCU) embedded in the waistband of the diaper. The MCU uses a low-power chip (such as Nordic nRF52840) to integrate the signal acquisition module and the BLE communication module. After processing the raw signal, the MCU performs pre-amplification, baseline calibration, artifact removal, and digital filtering to generate standardized data frames, and adds a detection timestamp and user identification code (UID) to each frame of data.

[0023] The standardized data is transmitted via BLE to a bound smartphone or tablet. The user device runs a custom-developed health management app, which features data reception, AES encryption, cache management, and background upload capabilities. The app uploads the data to a health data processing platform deployed on an Alibaba Cloud server via HTTPS. The cloud system analyzes whether changes in urine glucose and uric acid exceed individual health thresholds based on preset logical rules, and generates a preliminary health warning when abnormalities are detected more than three times. The warning information will be pushed to the user via the app and automatically written to the user's personal health record module for future trend tracking.

[0024] Example 2 Based on Example 1, this example further expands the capabilities of the sensor system and data model to meet the needs of home users for multi-indicator collaborative monitoring and member-shared management.

[0025] The flexible sensor has been upgraded to a multi-channel structure design, with multiple microelectrode arrays distributed on the surface of the sensing substrate, each responsible for detecting glucose, uric acid, sodium ions, potassium ions, and dopamine in urine. To improve urine collection efficiency and electrode stability, a superhydrophilic-hydrophobic hybrid microstructure array is constructed on the sensor surface. This array uses capillary guidance channels to rapidly direct urine to different electrode detection areas, thereby avoiding cross-interference.

[0026] The sensor connects to the MCU module via an integrated FPC (Flexible Printed Circuit). The MCU supports a multi-channel AD sampling mechanism, with each channel having independent zeroing and gain adjustment circuits to ensure dynamic range matching of the signal. The acquired data is transmitted at high speed to a smartphone via the BLE 5.0 protocol. The mobile app supports a multi-indicator display interface and highlights abnormal indicator icons, enhancing the user's intuitive understanding.

[0027] After the data is uploaded to the cloud platform, it is analyzed in time series using an LSTM-RNN hybrid neural network model. The model training process uses anonymized historical sample data to distinguish between pathological and non-pathological fluctuation trends, forming an early identification algorithm for chronic diseases, which is particularly suitable for risk assessment of people with chronic diseases such as diabetes, kidney disease, and mood disorders (through dopamine).

[0028] In addition, the system supports users setting tiered access permissions, including roles such as nursing staff accounts, family member viewing accounts, and remote doctor accounts, and implements granular permission division through a role-based access control (RBAC) policy. Authorized personnel can view users' historical monitoring records, risk trends, report exports, and remarks within their authorized scope. All operations are logged to ensure data security and traceability.

[0029] Example 3 Based on Example 2, this example is designed for centralized nursing scenarios such as elderly care institutions and community health stations, further enhancing the system's concurrency capabilities, model adaptability, and doctor interaction functions.

[0030] At the hardware level, the smart diaper terminal retains multi-indicator detection capabilities and adds a breakpoint resume mechanism and local caching strategy to the MCU. It can cache up to 100 data packets during brief communication interruptions to prevent data loss. The system integrates a dual-mode communication module (BLE+Wi-Fi), prioritizing access to a stable Wi-Fi network in institutional settings to achieve high-speed synchronization and remote operation and maintenance functions.

[0031] The cloud-based health data platform introduces a federated learning module to support cross-device model collaborative training. Under this mechanism, user data from various institutions is not directly uploaded; instead, gradients or weight parameters are uploaded to a central server for aggregation and optimization after local model training. This continuously improves the model's adaptability to different population structures and regional health characteristics, enhances personalized prediction capabilities, and protects user privacy.

[0032] Doctors log in to the platform via a dedicated workstation account and can access multi-dimensional views such as the health status distribution map, abnormal alarm list, and indicator trend chart of the users they manage. They can also issue nursing suggestions, appointment reminders, or mark observation records for specific users through the system backend; this content will be simultaneously pushed to the user's or caregiver's app. The system supports one-click export of health records (PDF and CSV formats) and is compatible with common HIS system interfaces, facilitating medical record archiving and medical insurance claims.

[0033] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A cloud-based health data management method for smart diapers, characterized in that... This includes the following steps: S1: By using a flexible electrochemical sensor module integrated into the smart diaper, information on at least one biomarker parameter in the wearer's urine is collected in real time. The biomarker includes one or more of urinary glucose, uric acid, electrolyte ions, and dopamine. S2: The microprocessor unit installed in the smart diaper performs signal calibration, noise filtering, and digital-to-analog conversion on the raw signals collected by the sensor to generate standardized test data, and adds time stamps and user identification marks to the data; S3: The standardized detection data is sent to the mobile terminal device bound to the smart diaper via a low-power wireless communication module; S4: The health data management application running on the mobile terminal encrypts and encapsulates the received detection data and uploads it to the cloud-based health data management platform; S5: The cloud-based health data management platform performs data cleaning, feature extraction, and multi-dimensional analysis on the uploaded data, and generates an assessment result of the user's current health status based on a pre-trained health assessment model; S6: Determine whether there is a risk of health abnormality based on the analysis results. When the test results exceed the preset threshold, trigger the health early warning mechanism and generate risk warning information; S7: The health status assessment results and early warning information are simultaneously pushed to the user terminal or the authorized caregiver terminal, and the complete data is stored in the user's personal health record for subsequent trend analysis and historical tracing.

2. The cloud-based health data management method for smart diapers according to claim 1, characterized in that... In step S1, the flexible electrochemical sensor adopts a three-electrode structure based on a composite conductive material of nano-silver paste and graphene, and guides urine to contact the sensing area through a superhydrophobic microstructure to improve detection sensitivity and repeatability.

3. The cloud-based health data management method for smart diapers according to claim 1, characterized in that... In step S5, the health assessment model is a chronic disease risk prediction model that integrates time series analysis and machine learning algorithms, used to identify the changing trends of urine biomarkers and assess the potential risk level of diabetes, kidney disease or gout.

4. The cloud-based health data management method for smart diapers according to claim 1, characterized in that... In step S6, the health warning mechanism determines the confidence interval based on multiple consecutive detection results to exclude occasional abnormal data and reduce the false alarm rate.

5. The cloud-based health data management method for smart diapers according to claim 1, characterized in that... In step S7, the health status assessment results are displayed graphically on the mobile terminal, and a health report containing the trend of changes in the detection indicators and the level of health recommendations is generated.

6. The cloud-based health data management method for smart diapers according to claim 1, characterized in that... The cloud-based health data management platform has a tiered access control mechanism, allowing users to grant corresponding levels of health data access permissions to doctors, nurses, or family members based on authorization policies.

7. A cloud-based health data management system for intelligent diapers, characterized in that... The system is used in the cloud-based health data management method for smart diapers according to any one of claims 1-6, the system comprising: The intelligent diaper terminal integrates a flexible electrochemical sensor module, a microprocessor module, a power management module, and a wireless communication module. Mobile terminal devices are used to receive data from smart diapers and communicate with the cloud platform; A cloud-based health data management platform is used to perform data analysis, health assessment, risk warning, and health record management. The user interaction module is used for health data display, abnormal alerts, and authorization management. The data security module is used to implement encrypted data transmission and access control.

8. The intelligent diaper cloud-based health data management system according to claim 7, characterized in that... The cloud-based health data management platform further includes a model self-learning module, which is used to continuously optimize the health assessment model based on historical health data in order to improve the accuracy of personalized health prediction.

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