Intelligent wearable monitoring system

Abstract

The invention relates to the technical field of wearing monitoring, and discloses an intelligent wearing monitoring system, which comprises a hardware module, a software module and a user interaction module, and is characterized in that the hardware module comprises an embedded system board which comprises an STM32 microcontroller, a Bluetooth 5.0 module, a sensor and a lithium battery; the bioelectrical impedance analysis module comprises a 32-bit processor and is used for monitoring the bladder state of the patient in real time; and the electrode part adopts a low-polarization wet Ag / AgCl electrode, is bonded by using conductive adhesive and is connected with the embedded system board through a conductive wire. Based on a bioelectrical impedance technology principle, a wearable and low-power-consumption intelligent sensing device is independently designed and researched and developed by utilizing an embedded technology and a single-chip microcomputer PCB technology, real-time monitoring and diagnosis of volume change of human bladder tissue are realized, and products for monitoring bladder capacity in the market at present mainly depend on an ultrasonic technology and an optical technology, so that the volume change of the human bladder tissue can be monitored and diagnosed in real time. Produced products are large in power consumption and high in professional requirement degree, and real-time monitoring cannot be achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of wearable monitoring, and in particular to an intelligent wearable monitoring system. Background Art

[0002] Wearable medical devices are intelligent devices that integrate sensors, electronic devices and data transmission functions, and can monitor, record and transmit users' physiological parameters or health data in real time.

[0003] With the aging population and the increase in the number of patients with chronic diseases, the incidence of bladder-related diseases has gradually increased. Traditional monitoring methods are limited by time and space and cannot provide real-time and continuous data. Therefore, the development of wireless wearable sensors for real-time monitoring of human bladder impedance has become an urgent task.

[0004] Therefore, it is necessary to design an intelligent wearable monitoring system to solve the above problems. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent wearable monitoring system.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] An intelligent wearable monitoring system includes a hardware module, a software module and a user interaction module, wherein:

[0008] The hardware module includes:

[0009] Embedded system board: including STM32 microcontroller, Bluetooth 5.0 module, sensor and lithium battery;

[0010] Bioelectrical impedance analysis module: includes a 32-bit processor for real-time monitoring of the patient's bladder status;

[0011] Electrode part: Use low-polarization wet Ag / AgCl electrodes, bond with conductive glue, and connect to the embedded system board through conductive wires;

[0012] The software modules include:

[0013] Data Processing and Algorithm Module: Using big data analysis and machine learning, we design algorithms to mitigate artifacts caused by human motion and establish a linear regression relationship model between human bladder tissue and impedance changes;

[0014] Data transmission and user interface module: uses Bluetooth technology to transmit monitoring data to the user's mobile phone in real time and display the monitoring data on the user's app. The user can view real-time monitoring data, set personalized reminders or vibration alarms;

[0015] The user interaction module includes:

[0016] App interface: Design a user interface that displays real-time monitoring data and allows users to set personalized reminders or alarms. Users can monitor their bladder status anytime, anywhere through the app.

[0017] Personalized settings: Allow users to set impedance thresholds that match different human body characteristics and set corresponding reminder or alarm parameters.

[0018] As a preferred technical solution of the present invention, it also includes a disinfection and maintenance module, which provides guidance to users on how to clean and maintain the bioelectrode to ensure the stability and accuracy of the measurement.

[0019] As a preferred technical solution of the present invention, the data processing and algorithm module includes the following units:

[0020] Motion artifact correction algorithm: Develop a correction algorithm for artifacts caused by human motion. By analyzing and processing sensor data, the impact of motion artifacts on monitoring results can be reduced or eliminated.

[0021] Linear regression relationship modeling: Based on big data analysis and machine learning technology, a linear regression relationship model between human bladder tissue and impedance changes is established to accurately predict bladder status and calibrate monitoring data;

[0022] Impedance threshold setting algorithm: Design an algorithm to set the appropriate impedance threshold according to different human characteristics and needs. Adjust the impedance threshold according to the patient's individual situation to achieve personalized monitoring and reminder functions;

[0023] Reminder and alarm triggering algorithm: Based on the set impedance threshold, an algorithm is designed to trigger personalized reminders or alarms. Based on real-time monitoring data, it is determined whether the preset impedance threshold is reached and the corresponding reminders or alarms are triggered.

[0024] As a preferred technical solution of the present invention, the data transmission and user interface module includes the following units:

[0025] Bluetooth data transmission unit: responsible for communicating with the Bluetooth 5.0 module on the embedded system board to achieve real-time transmission of monitoring data. This unit needs to handle data packaging, unpacking, transmission and reception to ensure stable and reliable data transmission;

[0026] Mobile App Interface Design Unit: Design the user interface of the mobile app, including the main page, monitoring data display page and settings page;

[0027] Real-time monitoring data display unit: displays real-time monitoring data on the mobile app, including bladder status, impedance change curve and monitoring time information. This unit receives and displays monitoring data from the embedded system board in real time;

[0028] Personalized reminder setting unit: allows users to set personalized reminder or alarm parameters on the mobile app, including impedance threshold, reminder method and reminder time. Users can set different reminder parameters according to their needs;

[0029] Data storage and analysis unit: stores the received monitoring data on the mobile phone and provides data analysis functions, including historical data query and trend analysis. Users can view past monitoring records at any time and understand the changing trends of bladder status.

[0030] The present invention has the following beneficial effects:

[0031] (1) Embedded single-chip microcomputer technology design innovation: Based on the principle of bioelectrical impedance technology, we independently designed and developed a wearable, low-power intelligent sensing device using embedded technology and single-chip microcomputer PCB technology to achieve real-time monitoring and diagnosis of changes in human bladder tissue volume. Currently, products used to monitor bladder capacity on the market mainly rely on ultrasonic technology and optical technology. The products they create have high power consumption, high professional requirements, and cannot achieve real-time monitoring;

[0032] (2) Data analysis and model building: Using big data analysis and machine learning technology, a linear regression relationship model between human bladder volume and impedance changes is established. The measurement data is benchmarked against a professional system electrochemical workstation to improve the accuracy and predictability of monitoring, thereby enhancing product measurement performance;

[0033] (3) Low-polarization wet Ag / AgCl electrodes are used, which have low polarization voltage. Therefore, the contact impedance with the skin can be reduced to zero. Conductive glue is used for the electrode bonding part, and conductive wires with good conductivity and stability are used to connect the electrodes to the development board.

[0034] (4) Using wireless Bluetooth technology, the monitoring data is transmitted to the user's mobile phone in real time, creating a digital intelligent monitoring platform called "Patient-App" to facilitate daily monitoring by patients or their guardians, and to make intelligent judgments when the bladder volume changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a schematic diagram of the system structure of an intelligent wearable monitoring system proposed by the present invention;

[0036] Figure 2 This is a working principle diagram of an intelligent wearable monitoring system proposed by the present invention. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0038] Reference Figure 1-2 An intelligent wearable monitoring system includes a hardware module, a software module, and a user interaction module, and also includes a disinfection and maintenance module. The disinfection and maintenance module provides guidance to the user on how to clean and maintain the bioelectrodes to ensure measurement stability and accuracy, wherein:

[0039] The hardware module includes:

[0040] Embedded system board: including STM32 microcontroller, Bluetooth 5.0 module, sensor and lithium battery;

[0041] Bioelectrical impedance analysis module: includes a 32-bit processor for real-time monitoring of the patient's bladder status;

[0042] Electrode part: Use low-polarization wet Ag / AgCl electrodes, bond with conductive glue, and connect to the embedded system board through conductive wires;

[0043] The software modules include:

[0044] Data processing and algorithm module: Using big data analysis and machine learning, an algorithm is designed to reduce artifacts caused by human motion and establish a linear regression relationship model between human bladder tissue and impedance changes. The data processing and algorithm module includes the following units:

[0045] Motion artifact correction algorithm: Develop a correction algorithm for artifacts caused by human motion. By analyzing and processing sensor data, the impact of motion artifacts on monitoring results can be reduced or eliminated.

[0046] Linear regression relationship modeling: Based on big data analysis and machine learning technology, a linear regression relationship model between human bladder tissue and impedance changes is established to accurately predict bladder status and calibrate monitoring data;

[0047] Impedance threshold setting algorithm: Design an algorithm to set the appropriate impedance threshold according to different human characteristics and needs. Adjust the impedance threshold according to the patient's individual situation to achieve personalized monitoring and reminder functions;

[0048] Reminder and alarm triggering algorithm: Based on the set impedance threshold, an algorithm is designed to trigger personalized reminders or alarms. Based on real-time monitoring data, it is determined whether the preset impedance threshold has been reached and the corresponding reminder or alarm is triggered;

[0049] Data transmission and user interface module: This module uses Bluetooth technology to transmit monitoring data to the user's mobile phone in real time and displays the monitoring data on the user's app. The user can view the real-time monitoring data and set personalized reminders or vibration alarms. The data transmission and user interface module includes the following units:

[0050] Bluetooth data transmission unit: responsible for communicating with the Bluetooth 5.0 module on the embedded system board to achieve real-time transmission of monitoring data. This unit needs to handle data packaging, unpacking, transmission and reception to ensure stable and reliable data transmission;

[0051] Mobile App Interface Design Unit: Design the user interface of the mobile app, including the main page, monitoring data display page and settings page;

[0052] Real-time monitoring data display unit: displays real-time monitoring data on the mobile app, including bladder status, impedance change curve and monitoring time information. This unit receives and displays monitoring data from the embedded system board in real time;

[0053] Personalized reminder setting unit: allows users to set personalized reminder or alarm parameters on the mobile app, including impedance threshold, reminder method and reminder time. Users can set different reminder parameters according to their needs;

[0054] Data storage and analysis unit: stores the received monitoring data on the mobile phone and provides data analysis functions, including historical data query and trend analysis. Users can view past monitoring records at any time and understand the changing trends of bladder status;

[0055] The user interaction module includes:

[0056] App interface: Design a user interface that displays real-time monitoring data and allows users to set personalized reminders or alarms. Users can monitor their bladder status anytime, anywhere through the app.

[0057] Personalized settings: Allow users to set impedance thresholds that match different human body characteristics and set corresponding reminder or alarm parameters.

[0058] The specific working principle of the present invention is as follows:

[0059] The hardware module consists of an embedded system board, a bioelectrical impedance analysis module, and electrodes. The embedded system board contains an STM32 microcontroller, a Bluetooth 5.0 module, sensors, and a lithium battery, enabling the collection, processing, and transmission of monitoring data. The bioelectrical impedance analysis module uses a 32-bit processor to monitor the patient's bladder status in real time. The electrodes utilize low-polarization wet-type Ag / AgCl electrodes, which are bonded to the patient using conductive adhesive and connected to the embedded system board via conductive wires to collect bladder impedance data.

[0060] The software module includes data processing and algorithm modules. The motion artifact correction algorithm corrects artifacts caused by human motion. The linear regression relationship modeling uses machine learning technology to establish a relationship model between bladder tissue and impedance changes. The impedance threshold setting algorithm sets the corresponding impedance threshold according to user characteristics. The reminder and alarm triggering algorithm triggers personalized reminders or alarms based on real-time monitoring data.

[0061] The data transmission and user interface module transmits monitoring data to the user's mobile phone in real time via Bluetooth technology and displays the monitoring data on the mobile app. This module includes a Bluetooth data transmission unit, a mobile app interface design unit, a real-time monitoring data display unit, a personalized reminder setting unit, and a data storage and analysis unit.

[0062] The user interaction module includes an app interface and personalized settings. Users can view real-time monitoring data through the app interface and set corresponding impedance thresholds and reminder parameters based on their personal characteristics to achieve personalized monitoring and reminder functions. The disinfection and maintenance module provides cleaning and maintenance guidance to ensure the cleanliness and stability of the bioelectrode, thereby ensuring the accuracy of monitoring results.

[0063] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field can replace or change the technical solution and inventive concept of the present invention within the technical scope disclosed by the present invention, and the replacement or change should be covered by the scope of protection of the present invention.

Claims

1. An intelligent wearable monitoring system, characterized in that: It includes hardware module, software module and user interaction module, among which: The hardware module includes: Embedded system board: including STM32 microcontroller, Bluetooth 5.0 module, sensor and lithium battery; Bioelectrical impedance analysis module: includes a 32-bit processor for real-time monitoring of the patient's bladder status; Electrode part: Use low-polarization wet Ag / AgCl electrodes, bond with conductive glue, and connect to the embedded system board through conductive wires; The software modules include: Data Processing and Algorithm Module: Using big data analysis and machine learning, we design algorithms to mitigate artifacts caused by human motion and establish a linear regression relationship model between human bladder tissue and impedance changes; Data transmission and user interface module: uses Bluetooth technology to transmit monitoring data to the user's mobile phone in real time and display the monitoring data on the user's app. The user can view real-time monitoring data, set personalized reminders or vibration alarms; The user interaction module includes: App interface: Design a user interface that displays real-time monitoring data and allows users to set personalized reminders or alarms. Users can monitor their bladder status anytime, anywhere through the app. Personalized settings: Allow users to set impedance thresholds that match different human body characteristics and set corresponding reminder or alarm parameters.

2. The intelligent wearable monitoring system according to claim 1, characterized in that: It also includes a disinfection and maintenance module, which provides guidance to users on how to clean and maintain the bioelectrode to ensure measurement stability and accuracy.

3. The intelligent wearable monitoring system according to claim 1, characterized in that: The data processing and algorithm module includes the following units: Motion artifact correction algorithm: Develop a correction algorithm for artifacts caused by human motion. By analyzing and processing sensor data, the impact of motion artifacts on monitoring results can be reduced or eliminated. Linear regression relationship modeling: Based on big data analysis and machine learning technology, a linear regression relationship model between human bladder tissue and impedance changes is established to accurately predict bladder status and calibrate monitoring data; Impedance threshold setting algorithm: Design an algorithm to set the appropriate impedance threshold according to different human characteristics and needs. Adjust the impedance threshold according to the patient's individual situation to achieve personalized monitoring and reminder functions; Reminder and alarm triggering algorithm: Based on the set impedance threshold, an algorithm is designed to trigger personalized reminders or alarms. Based on real-time monitoring data, it is determined whether the preset impedance threshold is reached and the corresponding reminders or alarms are triggered.

4. The intelligent wearable monitoring system according to claim 1, characterized in that: The data transmission and user interface module includes the following units: Bluetooth data transmission unit: responsible for communicating with the Bluetooth 5.0 module on the embedded system board to achieve real-time transmission of monitoring data. This unit needs to handle data packaging, unpacking, transmission and reception to ensure stable and reliable data transmission; Mobile App Interface Design Unit: Design the user interface of the mobile app, including the main page, monitoring data display page and settings page; Real-time monitoring data display unit: displays real-time monitoring data on the mobile app, including bladder status, impedance change curve and monitoring time information. This unit receives and displays monitoring data from the embedded system board in real time; Personalized reminder setting unit: allows users to set personalized reminder or alarm parameters on the mobile app, including impedance threshold, reminder method and reminder time. Users can set different reminder parameters according to their needs; Data storage and analysis unit: stores the received monitoring data on the mobile phone and provides data analysis functions, including historical data query and trend analysis. Users can view past monitoring records at any time and understand the changing trends of bladder status.

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