Intelligent multifunctional glucometer supporting data cloud storage and remote analysis

Abstract

The invention relates to the technical field of glucometers, and discloses an intelligent multifunctional glucometer supporting data cloud storage and remote analysis, which comprises hardware, detection, data processing, wireless communication, a cloud server platform and an interactive terminal module to form a complete data closed loop. The hardware module is composed of an upper shell and a lower shell which are clamped, and the upper shell is provided with a detection port, an operation button and anti-skid lines. The detection module is integrated with an electrochemical sensor array and can synchronously detect blood glucose, uric acid, ketone body and blood fat. The data processing unit processes data in real time to generate a health report, and the wireless communication module supports multi-mode communication and encrypted transmission. The cloud platform stores data and outputs suggestions through machine learning, and the interactive terminal supports biological recognition and voice broadcast. The modules cooperate to realize multi-index detection, cloud analysis and intelligent interaction. The system has the advantages of multi-index synchronous detection, data security intelligent analysis and convenient interaction, and supports data cloud storage and remote analysis.

Description

Technical Field

[0001] This invention relates to the field of blood glucose meter technology, specifically to an intelligent multifunctional blood glucose meter that supports cloud data storage and remote analysis. Background Art

[0002] Blood glucose meters are a key tool for daily blood glucose monitoring for diabetic patients. They enable rapid detection of blood glucose concentration by collecting a small amount of blood sample, providing data support for disease management.

[0003] In existing technologies, traditional blood glucose meters can only detect a single blood glucose level, requiring multiple blood samples to measure other metabolic indicators. Furthermore, their detection errors are relatively large, typically exceeding ±10%. Regarding data processing, most products lack real-time analysis capabilities, only displaying raw test values ​​and failing to generate multi-dimensional health reports. In terms of data transmission and storage, existing devices largely rely on one-way Bluetooth transmission, lacking multi-mode communication capabilities such as 5G / Wi-Fi, and their data encryption levels are low, posing a risk of leakage. Simultaneously, existing devices generally lack deep integration with cloud platforms, hindering long-term trend analysis and personalized health recommendations. In addition, issues such as chaotic multi-user management, data fragmentation from other health devices, and the absence of outlier handling mechanisms also limit their effectiveness in chronic disease management. Summary of the Invention

[0004] To address the aforementioned problems, this invention proposes an intelligent multi-functional blood glucose meter that features simultaneous detection of multiple indicators, secure and intelligent data analysis, and convenient interactive capabilities, supporting cloud storage and remote analysis.

[0005] To address the aforementioned technical problems, the present invention proposes the following technical solution: an intelligent multifunctional blood glucose meter supporting cloud data storage and remote analysis, comprising mutually cooperating hardware modules, a detection module, a data processing unit, a wireless communication module, a cloud server platform, and an interactive terminal, with each module forming a complete closed loop of data acquisition-processing-transmission-analysis-interaction.

[0006] The hardware module includes an upper housing and a lower housing that are interlocked with each other. The upper housing has a detection port on its side wall, an operation button integrated on its top surface, and anti-slip texture on its side.

[0007] The detection module integrates an electrochemical sensor array, which is precisely connected to the detection port, and can simultaneously detect blood glucose, uric acid, ketone bodies and blood lipid indicators.

[0008] The data processing unit is electrically connected to the detection module and has a built-in edge computing chip to receive and process detection data in real time and generate a health report.

[0009] The wireless communication module connects the data processing unit and the cloud server platform, supports 5G / Wi-Fi / BLE multi-mode communication, and uses AES-256 encryption.

[0010] The cloud server platform stores historical detection data and performs trend analysis through machine learning models to output personalized health recommendations.

[0011] The interactive terminal includes a touch screen and a biometric module integrated into the upper housing, which interact bidirectionally with the data processing unit and supports fingerprint / face recognition and voice broadcast functions.

[0012] Furthermore, the detection module adopts microfluidic chip technology, and blood is collected through the detection port (3). A single blood collection is linked to the data processing unit to complete the detection of multiple indicators. The detection error is ≤ ±5%. The detection module adopts a replaceable sensor chip, and the detection items can be quickly switched by matching with the data processing unit.

[0013] Furthermore, the data processing unit has a built-in outlier identification algorithm. When the detection result exceeds a preset threshold, it automatically triggers a secondary detection procedure with the detection module and synchronizes the data to the interactive terminal.

[0014] Furthermore, the cloud server platform forms a data closed loop with the data processing unit through a wireless communication module, including: a user database that stores detection data transmitted via the wireless communication module and medication records entered by the interactive terminal in a time-series manner; a risk assessment engine that performs trend analysis on historical data based on an LSTM neural network model to predict the risk of diabetic complications; and a doctor collaboration module that supports medical terminals in accessing user database information through an encrypted link, generating electronic medical orders, and pushing them to the interactive terminal via the wireless communication module.

[0015] Furthermore, the interactive terminal establishes data synchronization with peripherals such as smartwatches and body fat scales through a wireless communication module, forms a health record, and uploads it to the cloud server platform. The interactive terminal has a built-in offline storage unit that works in conjunction with the data processing unit to cache the most recent 100 test data entries. After the network is restored, it is automatically synchronized to the cloud through the wireless communication module.

[0016] Furthermore, the wireless communication module adopts a dynamic key exchange mechanism, which generates a unique session key when establishing a connection with the data processing unit and the cloud server platform. The encryption protocol is paired with the decryption mechanism of the cloud server platform to ensure that the data cannot be tampered with.

[0017] Furthermore, the biometric module is bound to the user account on the cloud platform through the interactive terminal, and the data processing unit is triggered by fingerprint / face recognition to call the corresponding historical data, so as to realize independent data management for multiple users.

[0018] Furthermore, the cloud server platform provides API interfaces to support access for third-party health management applications through an encrypted channel of the wireless communication module, enabling collaborative data analysis.

[0019] Compared with existing technologies, the advantages of this invention are as follows: The blood glucose meter adopts microfluidic chip technology, enabling multiple indicator tests to be completed with a single blood sample, reducing the number of blood draws, and providing accurate results. The interchangeable sensor chip allows for flexible switching of test items. Dynamic key exchange ensures secure data transmission and storage. The cloud platform and data processing unit form a closed loop, analyzing historical data through machine learning models to generate trend analysis and personalized suggestions, predicting complication risks, and supporting physician collaboration. Equipped with a touchscreen and biometric recognition, it supports multiple recognition methods and voice broadcasting, can synchronize data with external devices, caches data offline, and automatically synchronizes after network recovery, making user operation and data management more convenient. Attached Figure Description

[0020] Figure 1 This is a perspective view of the present invention.

[0021] As shown in the figure: 1. Upper housing; 2. Lower housing; 3. Detection port; 4. Operation button; 5. Touch screen. Detailed Implementation

[0022] The present invention will now be described in further detail with reference to the accompanying drawings.

[0023] Combined with appendix Figure 1 This intelligent multifunctional blood glucose meter supports cloud data storage and remote analysis. It includes interconnected hardware modules, a detection module, a data processing unit, a wireless communication module, a cloud server platform, and an interactive terminal. These modules form a complete closed loop of data acquisition, processing, transmission, analysis, and interaction. The hardware module consists of an upper housing 1 and a lower housing 2 that interlock. The upper housing 1 has a detection port 3 on its side wall, an integrated operation button 4 on its top surface, and anti-slip textures on its sides. The detection module integrates an electrochemical sensor array, precisely docked with the detection port 3, and can simultaneously detect blood glucose, uric acid, ketone bodies, and blood lipids. The detection module uses microfluidic chip technology. Blood is collected through the detection port 3, and a single blood collection triggers the data processing unit to complete multiple indicator detections with a detection error ≤ ±5%. The detection module uses a replaceable sensor chip, which, by matching with the data processing unit, enables rapid switching of detection items, reducing the pain of blood collection while ensuring detection accuracy and allowing for flexible switching of detection items.

[0024] The data processing unit is electrically connected to the detection module and has a built-in edge computing chip. It receives and processes detection data in real time and generates a health report. The data processing unit has a built-in outlier identification algorithm. When the detection result exceeds a preset threshold, it automatically triggers a secondary detection program with the detection module and synchronizes the data to the interactive terminal, which improves the reliability of the detection data and avoids misjudgment from affecting the user's health assessment.

[0025] The wireless communication module connects the data processing unit and the cloud server platform, supports 5G / Wi-Fi / BLE multi-mode communication, and uses AES-256 encryption. The wireless communication module adopts a dynamic key exchange mechanism, generating a unique session key when establishing a connection with the data processing unit and the cloud server platform. The encryption protocol is paired with the decryption mechanism of the cloud server platform to ensure that the data is immutable, protect the security of the data during transmission and storage, and prevent leakage and tampering.

[0026] The cloud server platform stores historical test data and performs trend analysis through machine learning models to output personalized health recommendations. The cloud server platform forms a data closed loop with the data processing unit via a wireless communication module, including: a user database that stores test data transmitted via the wireless communication module and medication records entered by the interactive terminal in a time-series manner; a risk assessment engine that performs trend analysis on historical data based on an LSTM neural network model to predict the risk of diabetic complications; and a doctor collaboration module that allows medical personnel to access user database information via an encrypted link, generate electronic medical orders, and push them to the interactive terminal via the wireless communication module, making user data management more systematic, accurately predicting risks, and facilitating doctor-patient collaboration.

[0027] The interactive terminal includes a touchscreen display 5 integrated into the upper housing 1 and a biometric module, which interacts bidirectionally with the data processing unit, supporting fingerprint / face recognition and voice broadcast functions. The interactive terminal establishes data synchronization with peripherals such as smartwatches and body fat scales via a wireless communication module, forming health records and uploading them to a cloud server platform. The interactive terminal has a built-in offline storage unit that works in conjunction with the data processing unit to cache the 100 most recent test data entries. Upon network recovery, it automatically synchronizes to the cloud via the wireless communication module, enriching the health record content and ensuring no data loss. The biometric module is bound to the user account on the cloud platform through the interactive terminal. Fingerprint / face recognition triggers the data processing unit to retrieve corresponding historical data, enabling independent data management for multiple users, protecting user privacy while facilitating multiple users using the same device. The cloud server platform provides API interfaces, supporting third-party health management applications through an encrypted channel of the wireless communication module, enabling collaborative data analysis, expanding the device's functionality and application scenarios, and enhancing the comprehensiveness of health management.

[0028] Specific implementation of the invention: When using the device, the user first completes fingerprint or facial recognition via the biometric module, and the touchscreen display 5 lights up. The blood sample is then inserted through the detection port 3. The electrochemical sensor array of the detection module precisely connects to the detection port 3, and detection is initiated using microfluidic chip technology. Multiple indicators can be detected simultaneously with a single blood sample. The data processing unit receives data in real time. If the result is abnormal, the detection module will automatically trigger a second detection, simultaneously generating a health report. The wireless communication module encrypts and transmits the data to the cloud server platform, where the platform stores the data and analyzes it using a machine learning model. The user can view the health report, historical data, and personalized suggestions pushed by the cloud platform on the touchscreen display via operation buttons, and can also hear voice broadcasts. If the network is interrupted, the offline storage unit will cache the data, and it will automatically synchronize to the cloud after the network is restored.

[0029] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the term "connection" should be interpreted broadly, for example, it can be a fixed connection, a detachable connection, or an integral connection; those skilled in the art can understand the specific meaning of the above term in this invention according to the specific circumstances.

[0030] The present invention and its embodiments are described above. This description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if a person skilled in the art is inspired by this and, without departing from the purpose of the present invention, designs structures and embodiments similar to this technical solution without inventiveness, they shall fall within the scope of protection of the present invention.

Claims

1. A smart multi-functional blood glucose meter that supports cloud data storage and remote analysis, characterized in that: It includes interconnected hardware modules, detection modules, data processing units, wireless communication modules, cloud server platforms, and interactive terminals. These modules form a complete closed loop of data acquisition, processing, transmission, analysis, and interaction. The hardware module includes an upper housing (1) and a lower housing (2) that are interlocked with each other. The upper housing (1) has a detection port (3) on its side wall, an operation button (4) integrated on its top surface, and anti-slip texture on its side. The detection module integrates an electrochemical sensor array, which is precisely connected to the detection port (3) and can simultaneously detect blood glucose, uric acid, ketone bodies and blood lipid indicators. The data processing unit is electrically connected to the detection module and has a built-in edge computing chip to receive and process detection data in real time and generate a health report. The wireless communication module connects the data processing unit and the cloud server platform, supports 5G / Wi-Fi / BLE multi-mode communication, and uses AES-256 encryption. The cloud server platform stores historical detection data and performs trend analysis through machine learning models to output personalized health recommendations. The interactive terminal includes a touch screen (5) integrated into the upper housing (1) and a biometric module, which interacts bidirectionally with the data processing unit and supports fingerprint / face recognition and voice broadcast functions.

2. The intelligent multifunctional blood glucose meter supporting cloud data storage and remote analysis according to claim 1, characterized in that: The detection module uses microfluidic chip technology. Blood is collected through the detection port (3). A single blood collection is linked to the data processing unit to complete the detection of multiple indicators. The detection error is ≤ ±5%. The detection module uses a replaceable sensor chip, which can quickly switch detection items by matching with the data processing unit.

3. The intelligent multifunctional blood glucose meter supporting cloud data storage and remote analysis according to claim 1, characterized in that: The data processing unit has a built-in outlier identification algorithm. When the detection result exceeds the preset threshold, it automatically triggers a secondary detection program with the detection module and synchronizes the data to the interactive terminal.

4. The intelligent multifunctional blood glucose meter supporting cloud data storage and remote analysis according to claim 1, characterized in that: The cloud server platform forms a data closed loop with the data processing unit through a wireless communication module, including: a user database that stores detection data transmitted via the wireless communication module and medication records entered by the interactive terminal in a time-series manner; a risk assessment engine that performs trend analysis on historical data based on an LSTM neural network model to predict the risk of diabetic complications; and a doctor collaboration module that allows medical devices to access user database information through an encrypted link, generate electronic medical orders, and push them to the interactive terminal via the wireless communication module.

5. The intelligent multifunctional blood glucose meter supporting cloud data storage and remote analysis according to claim 1, characterized in that: The interactive terminal establishes data synchronization with peripherals such as smartwatches and body fat scales through a wireless communication module, forms a health record, and uploads it to the cloud server platform. The interactive terminal has a built-in offline storage unit that works in conjunction with the data processing unit to cache the 100 most recent test data. After the network is restored, it is automatically synchronized to the cloud through the wireless communication module.

6. The intelligent multifunctional blood glucose meter supporting cloud data storage and remote analysis according to claim 1, characterized in that: The wireless communication module adopts a dynamic key exchange mechanism, which generates a unique session key when establishing a connection with the data processing unit and the cloud server platform. The encryption protocol is paired with the decryption mechanism of the cloud server platform to ensure that the data cannot be tampered with.

7. The intelligent multifunctional blood glucose meter supporting cloud data storage and remote analysis according to claim 1, characterized in that: The biometric module is bound to the user account on the cloud platform through the interactive terminal. It triggers the data processing unit to call the corresponding historical data by fingerprint / face recognition, so as to realize independent data management for multiple users.

8. The intelligent multifunctional blood glucose meter supporting cloud data storage and remote analysis according to claim 1, characterized in that: The cloud server platform provides API interfaces and supports access for third-party health management applications through an encrypted channel of the wireless communication module, enabling collaborative data analysis.

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