Method for automatically recording service life of electronic sphygmomanometer

Abstract

The invention relates to the technical field of electronic sphygmomanometer service life recording, in particular to an electronic sphygmomanometer service life automatic recording method which is achieved by executing stored software instructions through a built-in processor of equipment and comprises the steps that a current count value is initialized and read; defining and capturing a complete measurement action as a counting trigger condition; executing safe counting increasing and verification operation; synchronously correlating and recording temperature, humidity and voltage environment data; based on the number of times of use and the environment trend, the health degree is calculated through a life model, and early warning is generated; encrypting the synchronous data to the cloud; providing an administrator query and reset interface; and system self-inspection is executed regularly. According to the invention, each time of use is accurately recorded and analysis is carried out in combination with multi-dimensional environmental factors, so that the inaccuracy of traditional single time estimation is overcome, intelligent life prediction and maintenance reminding are realized, the reliability, safety and user experience of equipment are effectively improved, and meanwhile, the method has the advantages of low cost and easiness in popularization.

Description

Technical Field

[0001] This invention relates to the field of electronic blood pressure monitor lifespan recording technology, and in particular to an automatic method for recording the lifespan of an electronic blood pressure monitor. Background Technology

[0002] As a commonly used home medical device, the accuracy and reliability of electronic blood pressure monitors directly affect users' health assessments. However, the performance of core components (such as the air pump, pressure sensor, and solenoid valve) gradually deteriorates with increased use and environmental factors, eventually leading to measurement errors exceeding permissible limits and posing potential health risks. Currently, most electronic blood pressure monitors on the market lack effective lifespan management and early warning mechanisms. Some products use simple power-on time as a basis for lifespan assessment, which seriously ignores the differences in actual usage frequency and the accelerating effect of environmental stresses such as temperature and humidity on device aging, resulting in inaccurate and unreliable warnings. Users are unaware of the device's true health status and often continue to use it even after it has become severely inaccurate. Furthermore, for home sharing or multi-user clinical scenarios, there is a lack of differentiated recording of individual user contributions; the key lifespan data generated by the device is also not effectively utilized to support remote maintenance and systematic management.

[0003] Therefore, there is an urgent need in this field for a solution that can accurately and automatically record usage intensity and intelligently predict and warn about lifespan by taking into account environmental factors, so as to improve the safety and reliability of electronic blood pressure monitors. Summary of the Invention

[0004] To address the aforementioned issues, this invention overcomes the bias in lifespan assessment caused by differences in usage frequency and environment, transforming lifespan management from a rough time estimate to a precise assessment of usage intensity and environmental adaptability, thereby improving the accuracy and reliability of lifespan prediction through an automatic lifespan recording method for electronic blood pressure monitors.

[0005] The technical solution adopted in this invention is: an automatic recording method for the lifespan of an electronic blood pressure monitor, which is implemented by the processor built into the electronic blood pressure monitor executing software instructions stored in non-volatile memory, including the following steps: Step S1: In response to the power-on startup of the electronic blood pressure monitor, the software initializes the counting module and the environmental monitoring module, and reads the current usage count value and environmental correction parameters from the specified address of the non-volatile memory; Step S2: Define a complete usage action through software logic as a complete process from pressing the measurement key to the end of the final state output. The final state includes successfully outputting blood pressure and heart rate values ​​and displaying operation error information. Step S3: Capture the measurement process end event at the software level, and generate a count trigger signal regardless of whether the measurement is successful or not. Step S4, in response to the counting trigger signal, performs a safe counting increment operation, including: first reading the current count value from the memory into the processor register, performing an increment operation, then writing the new value back to the memory, and performing a read verification after writing to ensure data integrity; Step S5: At each count update, call the environmental sensor driver to read the current temperature, humidity and power supply voltage data, timestamp the environmental data and associate it with the current count record to store it in the extended log area; Step S6: Periodically or when the count reaches a node of 100 or 1000, trigger the life calculation subroutine to calculate the equipment health and remaining life based on the current total number of uses, recent environmental data trends and preset component life model. When the health is lower than the threshold or the remaining life is insufficient, generate an early warning message. Step S7: Through the device management backend service, the locally stored usage records and environment logs are encrypted and synchronized to the cloud server according to the set policy; Step S8: Provide administrator interface services, and after verifying specific input combinations or connection credentials, allow authorized users to query detailed usage statistics, export data, or perform counter resets; Step S9: During idle periods, the device automatically runs a self-test routine to verify the memory read / write function, counter checksum, sensor reading accuracy, and communication module status, and records the self-test log.

[0006] A further improvement to the above scheme is that, in step S4, the counting update process is not interrupted by disabling interrupts or using a hardware write protection mechanism, and the CRC32 checksum of the written data is calculated and verified after each write operation.

[0007] A further improvement to the above scheme is that, in step S5, the temperature data is taken from the built-in thermistor, with a sampling range of 0~50℃ and an accuracy of ±0.5℃; the humidity data is taken from the capacitive humidity sensor, with a sampling range of 10%~90%RH and an accuracy of ±3%RH; and the power supply voltage is taken from the ADC channel of the power management IC, with an accuracy of ±0.05V.

[0008] A further improvement to the above scheme is that, in step S6, the component life model used in the life calculation and early warning step is a regression model trained based on historical failure data. The input features include the number of uses, average temperature, humidity extreme values ​​and voltage fluctuation variance, and the output is the remaining life percentage of the air pump, pressure sensor and valve.

[0009] A further improvement to the above scheme is that, in step S7, both wired and wireless methods are supported. Wireless synchronization prioritizes Wi-Fi, and switches to Bluetooth Low Energy when Wi-Fi is unavailable. Synchronization data is encrypted using AES-128, and the cloud server returns a confirmation message of successful reception for the received data.

[0010] A further improvement to the above solution is that the warning information is simultaneously provided to the user through three methods: flashing icons on the device display screen, playing a prompt sound, and changing the color of the indicator light. At the same time, the warning message content is uploaded to the cloud through a data synchronization step.

[0011] A further improvement to the above scheme is that, in step S8, the authorization verification methods include: long-pressing a specific button combination while the device is powered off, authenticating by touching an NFC tag, or verifying by scanning a QR code through a paired mobile application.

[0012] A further improvement to the above solution is the inclusion of a software version check sub-step. When the device is connected to the Internet, it will query the server for the latest firmware version. If a new version exists, the user will be prompted to upgrade. After upgrading, the user can choose to reset or migrate the lifetime calculation model parameters.

[0013] A further improvement to the above scheme is to support a multi-user mode, allowing users to select or automatically identify the current user before starting the measurement, and associate usage records and environmental data with the corresponding user configuration file to independently calculate the usage contribution and device health impact of each user.

[0014] A further improvement to the above solution is that it also includes a data export step. In response to administrator instructions or user requests, the usage records, environmental data, early warning logs, and self-test results for the selected time period are generated into a standard JSON format file. This file can be transferred via USB, sent via email, or directly uploaded to a designated health management platform. The exported file contains a digital signature for verification.

[0015] The beneficial effects of this invention are: Compared to existing electronic blood pressure monitors, this invention accurately records every complete use and performs correlation analysis using multi-dimensional environmental data such as temperature, humidity, and voltage to construct a lifespan prediction model based on actual usage intensity and conditions. This effectively overcomes lifespan assessment biases caused by differences in usage frequency and environment, transforming lifespan management from coarse time estimation to precise assessment of usage intensity and environmental adaptability, thus improving the accuracy and reliability of lifespan prediction. The "atomic" counting update operation and CRC check mechanism implemented at the software level ensure that critical usage data is not lost or corrupted even in the event of unexpected power outages or interference. The periodic automatic self-check function can detect potential faults in storage, sensors, or communication modules in advance and record detailed logs, significantly improving the robustness and maintainability of the entire recording system and providing a solid guarantee for the long-term stable operation of the device. In addition to local data recording and early warning, a secure encrypted data synchronization mechanism connects device status information to a cloud platform, enabling manufacturers, medical institutions, or users to perform remote device monitoring, batch asset management, and predictive maintenance. Meanwhile, the multi-user support and detailed data export function meet the needs of different scenarios such as home sharing and institutional management, realizing a leap from single-point device to systemic health management, and enhancing the added value of the product and user experience. Through multimodal methods such as screen icons, sounds, and lights, it proactively conveys the device's health status and warning information to users, changing the previous situation where users were unaware of the device's internal wear and tear. The intuitive and timely feedback mechanism greatly enhances users' safety awareness, guiding them to maintain or replace the device before its performance deteriorates, effectively avoiding the potential health risks of inaccurate measurements due to using devices beyond their lifespan. Implemented through software algorithms, it mainly relies on the device's existing processor, memory, and sensors, without adding expensive hardware costs, thus endowing existing electronic blood pressure monitors with advanced lifespan management functions, demonstrating good economic efficiency and promotional value. Its modular design also facilitates adaptation to different models and levels of devices, making it widely applicable. This invention not only solves the pain points in the lifespan management of electronic blood pressure monitors, but also constructs a precise, reliable, intelligent, and interconnected lifespan management system through software innovation, achieving significant progress in improving device safety, reliability, and user experience. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the automatic recording method for the lifespan of the electronic blood pressure monitor according to the present invention. Detailed Implementation

[0017] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Preferred embodiments of the invention are shown in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of the invention.

[0018] It should be noted that when a component is said to be "fixed to" another component, it can be directly attached to the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0020] like Figure 1 As shown, in one embodiment of the present invention, a method for automatically recording the lifespan of an electronic blood pressure monitor is provided. This method is implemented by the processor built into the electronic blood pressure monitor executing software instructions stored in non-volatile memory, and includes the following steps: Step S1: In response to the power-on startup of the electronic blood pressure monitor, the software initializes the counting module and environmental monitoring module, reading the current usage count value and environmental calibration parameters from a designated address in non-volatile memory. Step S2: The software logic defines a complete usage action as a full process from pressing the measurement button to the final state output, where the final state includes successfully outputting blood pressure and heart rate values ​​and displaying operation error information. Step S3: At the software level, the measurement process end event is captured, generating a counting trigger signal regardless of whether the measurement is successful or not. Step S4: In response to the counting trigger signal, a safe count increment operation is performed, including: first, reading the current count value from memory into the processor register, incrementing it by one, then writing the new value back to memory, and performing a read verification after writing to ensure data integrity. Step S5: Simultaneously with each count update, the environmental sensor driver is invoked to read the current temperature. The system collects environmental data, including humidity and power supply voltage, timestamps the data, and associates it with the current count record, storing it in the extended log area. Step S6: Periodically or when the count reaches multiples of 100 or 1000, a lifespan calculation subroutine is triggered. Based on the current total usage count, recent environmental data trends, and a preset component lifespan model, the system calculates the device's health and remaining lifespan. When the health falls below a threshold or the remaining lifespan is insufficient, a warning message is generated. Step S7: Through the device management backend service, the locally stored usage records and environmental logs are encrypted and synchronized to the cloud server according to a set strategy. Step S8: An administrator interface service is provided, allowing authorized users to query detailed usage statistics, export data, or execute counter resets after verifying specific input combinations or connection credentials. Step S9: During idle periods, the device automatically runs a self-test routine to verify memory read / write functions, counter checksums, sensor reading accuracy, and communication module status, recording the self-test log.

[0021] This embodiment accurately records every complete usage session and performs correlation analysis using multi-dimensional environmental data such as temperature, humidity, and voltage to construct a lifespan prediction model based on actual usage intensity and conditions. This effectively overcomes lifespan assessment biases caused by differences in usage frequency and environment, transforming lifespan management from coarse time estimation to precise assessment of usage intensity and environmental adaptability, thus improving the accuracy and reliability of lifespan prediction. The "atomic" counting update operation and CRC check mechanism implemented at the software level ensure that critical usage data is not lost or corrupted even in the event of unexpected power outages or interference. The periodic automatic self-check function can detect potential faults in storage, sensors, or communication modules in advance and record detailed logs, significantly improving the robustness and maintainability of the entire recording system and providing a solid guarantee for the long-term stable operation of the equipment. It not only completes local data recording and early warning but also connects equipment status information to the cloud platform through a secure encrypted data synchronization mechanism. This enables manufacturers, medical institutions, or users to perform remote equipment monitoring, batch asset management, and predictive maintenance. Meanwhile, the multi-user support and detailed data export function meet the needs of different scenarios such as home sharing and institutional management, realizing a leap from single-point device to systemic health management, and enhancing the added value of the product and user experience. Through multimodal methods such as screen icons, sounds, and lights, the device proactively conveys its health status and warning information to users, changing the previous situation where users were unaware of the device's internal wear and tear. The intuitive and timely feedback mechanism greatly enhances users' safety awareness, guiding them to maintain or replace the device before its performance deteriorates, effectively avoiding the potential health risks of inaccurate measurements due to using devices beyond their lifespan. Implemented through software algorithms, it mainly relies on the device's existing processor, memory, and sensors, without adding expensive hardware costs, thus endowing existing electronic blood pressure monitors with advanced lifespan management functions, demonstrating good economic efficiency and promotional value. Its modular design also facilitates adaptation to different models and levels of devices, making it widely applicable. This embodiment not only solves the pain points in the lifespan management of electronic blood pressure monitors, but also constructs a precise, reliable, intelligent, and interconnected lifespan management system through software innovation, achieving significant progress in improving device safety, reliability, and user experience.

[0022] In step S4, interrupts are disabled or a hardware write protection mechanism is used to ensure that the counting update process is not interrupted, and a CRC32 checksum of the written data is calculated and verified after each write operation. This embodiment constructs a highly reliable data write guarantee system at the software level by disabling interrupts or using a hardware write protection mechanism combined with "CRC32 checksum verification." In actual operation, it can effectively cope with sudden power fluctuations or system interference that the electronic blood pressure monitor may encounter during the counting update process, ensuring that critical usage count data will not be written incorrectly or lost due to unexpected interruptions in the process. The CRC32 checksum mechanism further verifies the integrity of the data after writing, improving the accuracy and reliability of the stored data.

[0023] In step S5, temperature data is obtained from a built-in thermistor, with a range of 0~50℃ and an accuracy of ±0.5℃; humidity data is obtained from a capacitive humidity sensor, with a range of 10%~90%RH and an accuracy of ±3%RH; and the power supply voltage is obtained from the ADC channel of the power management IC, with an accuracy of ±0.05V. This embodiment specifically defines the source and technical specifications of environmental monitoring data, expanding lifespan assessment from a single dimension of usage frequency to multi-dimensional environmental influencing factors. By employing a thermistor with an accuracy of ±0.5℃, a capacitive humidity sensor with ±3%RH, and high-precision ADC voltage detection, high-quality and highly reliable environmental parameters can be collected. The accurate data (0~50℃ temperature, 10%~90%RH humidity) truly reflects the actual environmental stress of the equipment operation, providing accurate input features for subsequent lifespan prediction models.

[0024] In step S6, the component lifespan calculation and early warning step uses a regression model trained on historical failure data. Input features include usage frequency, average temperature, extreme humidity, and voltage fluctuation variance. The output is the remaining lifespan percentage of the air pump, pressure sensor, and valve. This embodiment upgrades lifespan prediction from traditional fixed threshold alarms to intelligent prediction based on artificial intelligence. By employing a regression model trained on historical failure data and selecting features strongly correlated with the wear of mechanical and electronic components, such as usage frequency, average temperature, extreme humidity, and voltage fluctuation variance, as inputs, the model can dynamically calculate the remaining lifespan percentage of core components such as air pumps, pressure sensors, and valves.

[0025] In step S7, both wired and wireless methods are supported. Wireless synchronization prioritizes Wi-Fi, switching to Bluetooth Low Energy when Wi-Fi is unavailable. Synchronized data is encrypted using AES-128, and the cloud server returns a confirmation message indicating successful reception of the received data. This embodiment sets up a data synchronization strategy. First, wired and wireless dual-mode backup (prioritizing Wi-Fi, seamlessly switching to BLE) ensures that data can always find a usable transmission path in different application scenarios (such as home, clinic), improving the success rate and flexibility of data synchronization. Second, the AES-128 encryption algorithm is used to encrypt the synchronized data, effectively preventing user privacy and device data from being stolen or tampered with during transmission, meeting the stringent data security requirements of medical devices.

[0026] The warning information is simultaneously communicated to the user through three methods: flashing icons on the device display screen, playing a prompt sound, and changing the color of the indicator light. Simultaneously, the warning message content is uploaded to the cloud via data synchronization. This embodiment improves the efficiency and reliability of human-computer interaction by constructing a warning information notification system. The technical effects are: Multi-channel coverage: Combining visual (flashing screen icons, gradual color change of indicator lights) and auditory (prompt sounds) notifications simultaneously ensures that users in different environments (such as those with poor eyesight or hearing) can receive warning information promptly and accurately, avoiding the risk of being overlooked by a single notification method. Intuitive and clear: The indicator lights use the internationally recognized color coding logic of "green-yellow-red," allowing users to intuitively understand the evolution of the device's health status from good to warning to critical without reading complex text. Third, information closed loop: While providing local notifications, the warning message is uploaded to the cloud, enabling device manufacturers or maintenance personnel to remotely monitor the device status.

[0027] In step S8, the authorization verification methods include: long-pressing a specific button combination while the device is powered off, NFC tag touch authentication, or scanning a QR code via a paired mobile application. This embodiment provides an administrator permission verification scheme that cleverly balances convenience and security. Its technical advantages are reflected in: operational versatility: It provides three methods—"hardware button combination," "NFC touch authentication," and "mobile application scanning"—adapting to different authentication habits and device support capabilities from traditional to modern approaches, ensuring authorized personnel can find a suitable management entry point in any scenario. The requirement for physical contact or pre-pairing effectively prevents accidental operation and malicious access by remote or unauthorized personnel, ensuring the security of critical functions such as counter reset and data export.

[0028] It also includes a software version check sub-step. When the device connects to the internet, it queries the server for the latest firmware version. If a new version exists, the user is prompted to upgrade. After upgrading, the user can choose to reset or migrate the lifespan calculation model parameters. This embodiment sets up online upgrade and model maintenance functions, enabling the electronic blood pressure monitor's lifespan management system to have the ability to continuously evolve and self-optimize. First, functional sustainability: By connecting to the internet to query and upgrade firmware, known software defects can be fixed, system performance can be improved, and new functions can be continuously added, extending the product's technical lifespan. Second, model optimizability: The most forward-looking effect is that it allows the core "lifespan calculation model parameters" to be reset or migrated after the upgrade.

[0029] Supporting a multi-user mode, the system allows users to select or automatically identify the current user before measurement begins. Usage records and environmental data are then linked to the corresponding user profiles, independently calculating each user's contribution to device health and its impact. This multi-user mode, tailored to shared devices in homes or small clinics, enables refined and personalized lifespan management. First, clear responsibility: The system distinguishes between different users' usage records and links the data to their respective profiles, clearly recording each member's total "wear and tear contribution" to the device, resolving the issue of unclear responsibility allocation when sharing equipment. Second, personalized health assessment: By independently calculating each user's "usage contribution and device health impact," the system can provide more personalized device status feedback for each user. For example, it can remind a family member who frequently uses the device of the impact of their usage on the device's lifespan, or inform all users of the overall health status of the device under the current combined usage intensity.

[0030] The system also includes a data export step. Responding to administrator commands or user requests, it generates a standard JSON format file from usage records, environmental data, warning logs, and self-test results for a selected time period. This file can be transferred via USB, sent via email, or directly uploaded to a designated health management platform. The exported file contains a digital signature for verification. The data export function provided in this embodiment greatly enhances the usability and reliability of system data. Its technical effects are reflected in: First, standardized format and interoperability: Exporting to a standard JSON format file allows users, medical personnel, or third-party health management platforms (such as hospital information systems and health apps) to directly read and further analyze the data, breaking down the closed nature of device data. Second, flexible and diverse methods: Supporting multiple export channels such as USB, email, and direct upload meets the needs of different user preferences and technical environments. Third, data authenticity and tamper-proofing: Attaching a digital signature to the exported file is like stamping the data with an "electronic seal," and any tampering with the file will cause signature verification to fail.

[0031] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this patent should be determined by the appended claims.

Claims

1. A method for automatically recording the lifespan of an electronic blood pressure monitor, characterized in that: The method is implemented by executing software instructions stored in non-volatile memory through the processor built into the electronic blood pressure monitor, and includes the following steps: Step S1: In response to the power-on startup of the electronic blood pressure monitor, the software initializes the counting module and the environmental monitoring module, and reads the current usage count value and environmental correction parameters from the specified address of the non-volatile memory; Step S2: Define a complete usage action through software logic as a complete process from pressing the measurement key to the end of the final state output. The final state includes successfully outputting blood pressure and heart rate values ​​and displaying operation error information. Step S3: Capture the measurement process end event at the software level, and generate a count trigger signal regardless of whether the measurement is successful or not. Step S4, in response to the counting trigger signal, performs a safe counting increment operation, including: first reading the current count value from the memory into the processor register, performing an increment operation, then writing the new value back to the memory, and performing a read verification after writing to ensure data integrity; Step S5: At each count update, call the environmental sensor driver to read the current temperature, humidity and power supply voltage data, timestamp the environmental data and associate it with the current count record to store it in the extended log area; Step S6: Periodically or when the count reaches a node of 100 or 1000, trigger the life calculation subroutine to calculate the equipment health and remaining life based on the current total number of uses, recent environmental data trends and preset component life model. When the health is lower than the threshold or the remaining life is insufficient, generate an early warning message. Step S7: Through the device management backend service, the locally stored usage records and environment logs are encrypted and synchronized to the cloud server according to the set policy; Step S8: Provide administrator interface services, and after verifying specific input combinations or connection credentials, allow authorized users to query detailed usage statistics, export data, or perform counter resets; Step S9: During idle periods, the device automatically runs a self-test routine to verify the memory read / write function, counter checksum, sensor reading accuracy, and communication module status, and records the self-test log.

2. The method for automatically recording the service life of an electronic blood pressure monitor according to claim 1, characterized in that: In step S4, the counting update process is ensured to be uninterrupted by disabling interrupts or using a hardware write protection mechanism, and the CRC32 checksum of the written data is calculated and verified after each write operation.

3. The method for automatically recording the service life of an electronic blood pressure monitor according to claim 1, characterized in that: In step S5, the temperature data is taken from the built-in thermistor, with a sampling range of 0~50℃ and an accuracy of ±0.5℃; the humidity data is taken from the capacitive humidity sensor, with a sampling range of 10%~90%RH and an accuracy of ±3%RH; and the power supply voltage is taken from the ADC channel of the power management IC, with an accuracy of ±0.05V.

4. The method for automatically recording the service life of an electronic blood pressure monitor according to claim 1, characterized in that: In step S6, the component life model used in the life calculation and early warning step is a regression model trained based on historical failure data. The input features include usage frequency, average temperature, humidity extreme values ​​and voltage fluctuation variance, and the output is the remaining life percentage of the air pump, pressure sensor and valve.

5. The method for automatically recording the service life of an electronic blood pressure monitor according to claim 1, characterized in that: In step S7, both wired and wireless methods are supported. Wireless synchronization prioritizes Wi-Fi, and switches to Bluetooth Low Energy when Wi-Fi is unavailable. Synchronization data is encrypted using AES-128, and the cloud server returns a confirmation message of successful reception for the received data.

6. The method for automatically recording the service life of an electronic blood pressure monitor according to claim 1, characterized in that: The warning information is simultaneously communicated to the user through three methods: flashing icons on the device display screen, playing a prompt sound, and changing the color of the indicator light. At the same time, the warning message content is uploaded to the cloud through a data synchronization process.

7. The method for automatically recording the service life of an electronic blood pressure monitor according to claim 1, characterized in that: In step S8, the authorization verification methods include: pressing and holding a specific button combination while the device is powered off, authenticating by touching an NFC tag, or verifying by scanning a QR code through a paired mobile application.

8. The method for automatically recording the service life of an electronic blood pressure monitor according to claim 1, characterized in that: It also includes a software version check sub-step. When the device is connected to the Internet, it will query the server for the latest firmware version. If a new version exists, the user will be prompted to upgrade. After upgrading, the user can choose to reset or migrate the lifetime calculation model parameters.

9. The method for automatically recording the service life of an electronic blood pressure monitor according to claim 1, characterized in that: It supports multi-user mode. Before starting the measurement, users can select or automatically identify the current user through the interface, associate usage records and environmental data with the corresponding user configuration file, and independently calculate the usage contribution and device health impact of each user.

10. The method for automatically recording the service life of an electronic blood pressure monitor according to claim 1, characterized in that: It also includes a data export step, which, in response to administrator instructions or user requests, generates a standard JSON format file from usage records, environmental data, warning logs, and self-inspection results for a selected time period. The file can be transferred via USB, sent via email, or directly uploaded to a designated health management platform. The exported file contains a digital signature for verification.

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