An endocrinology blood glucose data monitoring method and system

Abstract

The present invention relates to the technical field of blood glucose data monitoring, and specifically discloses an endocrinology blood glucose data monitoring method and system. The method generates a first type of fault parameter set for the blood glucose monitoring device by evaluating the storage environment parameters of the blood glucose monitoring device, analyzes the performance parameters of the blood glucose monitoring device to generate a second type of fault parameter set for the blood glucose monitoring device, determines the data accuracy coefficient of the blood glucose monitoring device, and generates a third type of fault parameter set for the blood glucose monitoring device, so as to realize the comprehensive monitoring of the blood glucose monitoring device. Thus, the monitoring feedback of the fault data of the blood glucose monitoring device is carried out, which helps to quickly identify and locate the specific problem types existing in the blood glucose monitoring device, provides a scientific basis for the maintenance of the blood glucose monitoring device, and ensures the accuracy and continuity of the blood glucose data monitoring results.

Description

Technical Field

[0001] The present invention relates to the technical field of blood glucose data monitoring, and specifically to a method and system for monitoring blood glucose data in the endocrinology department. Background Art

[0002] Currently, during the process of monitoring blood glucose data, the blood glucose monitoring device, as an important tool for data monitoring, its stability and reliability are directly related to the accuracy of blood glucose data. However, the existing methods for monitoring and analyzing blood glucose data only rely on the direct analysis of blood glucose data, ignoring the monitoring and evaluation of the key parameters of the blood glucose monitoring device, resulting in the inability to formulate effective maintenance strategies, and thus unable to improve the accuracy and efficiency of the blood glucose monitoring device in monitoring blood glucose data.

[0003] For example, the invention patent with the publication number CN112798783B discloses a blood glucose detection system and method. The system includes a blood glucose meter and a cloud server communicatively connected to the blood glucose meter; the blood glucose meter is configured to: send the measured temperature value and humidity value to the cloud server, and perform temperature compensation calculation during the process of measuring blood glucose concentration based on the temperature compensation calculation parameters returned by the cloud server; the cloud server is configured to: obtain multiple groups of data, each group of data including a standard parameter comparison table and the temperature value and humidity value under the same conditions; train a BP neural network model with the temperature value, humidity value, and standard parameter comparison table; receive the temperature value and humidity value sent by the blood glucose meter; input the temperature value and humidity value into the trained BP neural network model to obtain temperature compensation calculation parameters; send the temperature compensation calculation parameters to the blood glucose meter, which can improve the accuracy of the blood glucose meter in detecting blood glucose concentration and the quality control of the testing process.

[0004] For example, the invention patent with the publication number CN105403705B discloses a continuous blood glucose monitoring device including a blood glucose classification function fault detection module. The device detects faults of the continuous blood glucose monitor by establishing a blood glucose PCA monitoring graph to provide accurate blood glucose signals; due to the influence of external inputs (such as diet, patient emotional changes, etc.), the blood glucose fluctuation situation of the patient will change, and the corresponding blood glucose signal SPE value also changes significantly; in addition, there is obvious non-linearity between blood glucose signals, so it is impossible to establish a unified and effective control limit to detect whether the blood glucose meter fails.

[0005] However, during the implementation of the embodiments of the present application, it is found that the above technologies have at least the following technical problems: during the existing blood glucose data monitoring process, the display of the analysis results of blood glucose data is relatively single, which may lead to over-maintenance of blood glucose data, thus unable to formulate an efficient maintenance strategy, resulting in the inability to improve the accuracy of blood glucose data. Summary of the Invention

[0006] In view of the deficiencies of the prior art, the present invention provides a method and system for monitoring blood glucose data in the endocrinology department, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is realized through the following technical solutions: In the first aspect of the present invention, a method for monitoring blood glucose data in the endocrinology department is provided, including: S1. Mark the electronic device for monitoring blood glucose data in the endocrinology department as a blood glucose monitoring device, obtain the storage environment parameters of the blood glucose monitoring device, evaluate the storage environment rationality index of the blood glucose monitoring device, compare it with the storage environment rationality threshold. If the storage environment rationality index of the blood glucose monitoring device is less than the storage environment rationality threshold, then transmit the storage environment parameters of the blood glucose monitoring device to the first type of fault parameter set of the blood glucose monitoring device, and continue to execute S2. Otherwise, if the storage environment rationality index of the blood glucose monitoring device is greater than or equal to the storage environment rationality threshold, then continue to execute S2; S2. Collect the performance parameters of the blood glucose monitoring device, analyze the performance compliance index of the blood glucose monitoring device, compare it with the performance compliance threshold. If the performance compliance index of the blood glucose monitoring device is less than the performance compliance threshold, then transmit the performance parameters of the blood glucose monitoring device to the second type of fault parameter set of the blood glucose monitoring device, and continue to execute S3. Otherwise, if the performance compliance index of the blood glucose monitoring device is greater than or equal to the performance compliance threshold, then continue to execute S3; S3. Test various sample reagents, based on the test results of various sample reagents, obtain the test data curve of the blood glucose monitoring device, determine the data accuracy coefficient of the blood glucose monitoring device, compare it with the data accuracy threshold. If the data accuracy coefficient of the blood glucose monitoring device is less than the data accuracy threshold, then transmit the test data of the blood glucose monitoring device to the third type of fault parameter set of the blood glucose monitoring device, and continue to execute S4. Otherwise, if the data accuracy coefficient of the blood glucose monitoring device is greater than or equal to the data accuracy threshold, then continue to execute S4; S4. Integrate the first type of fault parameter set of the blood glucose monitoring device, the second type of fault parameter set of the blood glucose monitoring device, and the third type of fault parameter set of the blood glucose monitoring device to generate the fault parameter set of the blood glucose monitoring device, thereby monitoring and feedback the fault data of the blood glucose monitoring device.

[0008] As a further method, the process of testing various sample reagents is specifically as follows: Use the blood glucose monitoring device to measure various sample reagents, and the measurement interval duration between adjacent sample reagents is equal, thereby obtaining the test results of various sample reagents and recording them as the respective test data of the blood glucose monitoring device.

[0009] As a further method, obtaining the test data curve of the blood glucose monitoring device specifically means: The blood glucose data management system receives the respective test data of the blood glucose monitoring device and generates the test data curve of the blood glucose monitoring device.

[0010] As a further method, the process of generating the fault parameter set of the blood glucose monitoring device is as follows: The blood glucose data management system integrates and packages the first type of fault parameter set of the blood glucose monitoring device, the second type of fault parameter set of the blood glucose monitoring device, and the third type of fault parameter set of the blood glucose monitoring device, thereby generating the fault parameter set of the blood glucose monitoring device.

[0011] As a further method, the process of monitoring and feedback on the fault data of the blood glucose monitoring device is as follows: The blood glucose data management system feeds back the fault parameter set of the blood glucose monitoring device, thereby completing the monitoring and feedback on the fault data of the blood glucose monitoring device.

[0012] The second aspect of the present invention provides a system applying the method for monitoring blood glucose data in the endocrinology department as described above, including: a storage environment evaluation module, used to mark the electronic device for monitoring blood glucose data in the endocrinology department as a blood glucose monitoring device, obtain the storage environment parameters of the blood glucose monitoring device, evaluate the reasonable index of the storage environment of the blood glucose monitoring device, compare it with the reasonable threshold of the storage environment. If the reasonable index of the storage environment of the blood glucose monitoring device is less than the reasonable threshold of the storage environment, then transmit the storage environment parameters of the blood glucose monitoring device to the first type of fault parameter set of the blood glucose monitoring device, and continue to execute the device performance analysis module. On the contrary, if the reasonable index of the storage environment of the blood glucose monitoring device is greater than or equal to the reasonable threshold of the storage environment, then continue to execute the device performance analysis module; a device performance analysis module, used to collect the performance parameters of the blood glucose monitoring device, analyze the performance compliance index of the blood glucose monitoring device, compare it with the performance compliance threshold. If the performance compliance index of the blood glucose monitoring device is less than the performance compliance threshold, then transmit the performance parameters of the blood glucose monitoring device to the second type of fault parameter set of the blood glucose monitoring device, and continue to execute the data accuracy determination module. On the contrary, if the performance compliance index of the blood glucose monitoring device is greater than or equal to the performance compliance threshold, then continue to execute the data accuracy determination module; a data accuracy determination module, used to test various sample reagents, based on the test results of various sample reagents, obtain the test data curve of the blood glucose monitoring device, determine the data accuracy coefficient of the blood glucose monitoring device, compare it with the data accuracy threshold. If the data accuracy coefficient of the blood glucose monitoring device is less than the data accuracy threshold, then transmit the test data of the blood glucose monitoring device to the third type of fault parameter set of the blood glucose monitoring device, and continue to execute the fault monitoring and feedback module. On the contrary, if the data accuracy coefficient of the blood glucose monitoring device is greater than or equal to the data accuracy threshold, then continue to execute the fault monitoring and feedback module; a fault monitoring and feedback module, used to integrate the first type of fault parameter set of the blood glucose monitoring device, the second type of fault parameter set of the blood glucose monitoring device, and the third type of fault parameter set of the blood glucose monitoring device, generate the fault parameter set of the blood glucose monitoring device, thereby monitoring and feedback on the fault data of the blood glucose monitoring device.

[0013] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0014] (1) The present invention provides a method and system for monitoring blood glucose data in the endocrinology department. By evaluating the storage environment parameters of the blood glucose monitoring device, a first type of fault parameter set of the blood glucose monitoring device is generated. By analyzing the performance parameters of the blood glucose monitoring device, a second type of fault parameter set of the blood glucose monitoring device is generated. By determining the data accuracy coefficient of the blood glucose monitoring device, a third type of fault parameter set of the blood glucose monitoring device is generated, realizing comprehensive monitoring of the blood glucose monitoring device. Thus, monitoring and feedback of the fault data of the blood glucose monitoring device are carried out, which helps to quickly identify and locate the specific problem types existing in the blood glucose monitoring device, provides a scientific basis for the maintenance of the blood glucose monitoring device, and ensures the accuracy and continuity of the blood glucose data monitoring results.

[0015] (2) The present invention analyzes the data of three dimensions, namely the total concentration of target gases, the light uniformity, and the moisture content, in the storage environment of the blood glucose monitoring device, and comprehensively processes them to obtain the reasonable index of the storage environment of the blood glucose monitoring device. Compared with maintaining when a single data is abnormal, it is beneficial to reduce the problem of over-maintenance, making the maintenance more accurate and scientific. At the same time, considering multiple dimensions can accurately locate the cause of the fault of the blood glucose monitoring device, thereby shortening the fault troubleshooting time of the blood glucose monitoring device and improving the maintenance efficiency.

[0016] (3) The present invention comprehensively analyzes the voltage fluctuation ratio coefficient of the blood glucose monitoring device, the color offset value of the test strip to which the blood glucose monitoring device belongs, and the degree of aging of the blood glucose monitoring device to obtain the performance compliance index of the blood glucose monitoring device, which helps to timely discover potential problems that may be ignored when the blood glucose monitoring device monitors blood glucose data, thereby improving the comprehensiveness of the performance evaluation of the blood glucose monitoring device and ensuring the accuracy of the blood glucose monitoring device in monitoring blood glucose. Description of the Drawings

[0017] The present invention is further described with the help of the drawings, but the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the following drawings.

[0018] Figure 1 It is a schematic flow chart of the method steps of the present invention.

[0019] Figure 2 It is a schematic diagram of the connection of the system modules of the present invention.

[0020] Figure 3 It is a schematic diagram of the voltage fluctuation curve involved in the present invention.

[0021] Figure 4 It is a schematic diagram of the test data curve of the blood glucose monitoring device involved in the present invention.

[0022] Reference numerals: 1, data reception time point; 2, start time point of data test; 3, reception interval duration; 4, reception interval duration; 5, minimum voltage deviation value; 6, maximum voltage deviation value. Detailed implementation mode

[0023] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0024] Refer to Figure 1 As shown, the first aspect of the present invention provides a method for monitoring blood glucose data in the endocrinology department, including: S1. Mark the electronic device for monitoring blood glucose data in the endocrinology department as a blood glucose monitoring device, obtain the storage environment parameters of the blood glucose monitoring device, evaluate the storage environment rationality index of the blood glucose monitoring device, compare it with the storage environment rationality threshold. If the storage environment rationality index of the blood glucose monitoring device is less than the storage environment rationality threshold, then transmit the storage environment parameters of the blood glucose monitoring device to the first type of fault parameter set of the blood glucose monitoring device, and continue to execute S2. On the contrary, if the storage environment rationality index of the blood glucose monitoring device is greater than or equal to the storage environment rationality threshold, then continue to execute S2.

[0025] The above storage environment rationality threshold refers to the minimum value of the reasonable range of the storage environment rationality index of the blood glucose monitoring device, which is specified by the equipment maintenance specialist based on historical work experience. If the storage environment rationality index of the blood glucose monitoring device is less than the storage environment rationality threshold, it indicates that the storage environment of the blood glucose monitoring device cannot meet the performance requirements of the blood glucose monitoring device, which may lead to a decline in the performance of the blood glucose monitoring device and damage to the accuracy of blood glucose monitoring data. Therefore, the storage environment parameters of the blood glucose monitoring device are transmitted to the first type of fault parameter set of the blood glucose monitoring device. Among them, the first type of fault parameter set of the blood glucose monitoring device represents a set for storing the storage environment parameters of the blood glucose monitoring device. If there is data in this set, it indicates that the comprehensive negative impact of the data in this set on the performance of the blood glucose monitoring device is relatively large. In an exemplary embodiment, the first type of fault parameter set of the blood glucose monitoring device includes moisture content, light uniformity, and total target gas concentration. If the storage environment rationality index of the blood glucose monitoring device is greater than or equal to the storage environment rationality threshold, it indicates that the storage environment of the blood glucose monitoring device can meet the performance requirements of the blood glucose monitoring device, and there is no need to generate the first type of fault parameter set of the blood glucose monitoring device, and directly continue to execute S2.

[0026] The storage environment parameters of the above blood glucose monitoring device. In this embodiment, the environmental parameters include the concentrations of various target gases (unit: milligrams per cubic meter), illuminance values (unit: lux), average air pressure (unit: pascals), average water vapor partial pressure (unit: millimeters of mercury), etc. In this example, in addition to being applicable to the above parameters, it can also be used for other parameters, but the directions (i.e., positive and negative relationships) that these parameters can reflect are the same.

[0027] In a specific embodiment, the present invention analyzes the data of three dimensions, namely the total concentration of target gases, the light uniformity, and the moisture content, in the storage environment of the blood glucose monitoring device, and comprehensively processes them to obtain the reasonable index of the storage environment of the blood glucose monitoring device. Compared with maintaining the device when a single data is abnormal, it is beneficial to reduce the problem of over-maintenance, making the maintenance more accurate and scientific. At the same time, considering multiple dimensions can accurately locate the cause of the failure of the blood glucose monitoring device, thereby shortening the troubleshooting time of the blood glucose monitoring device and improving the maintenance efficiency.

[0028] Specifically, the reasonable index of the storage environment of the blood glucose monitoring device. In this embodiment, the reasonable index of the storage environment of the above blood glucose monitoring device is obtained through comprehensive analysis of the total concentration of target gases, the light uniformity, and the moisture content in the storage environment of the blood glucose monitoring device, and is a numerical value used to evaluate the rationality of the storage environment of the blood glucose monitoring device. The specific expression is:

[0029] ;

[0030] is the total concentration of target gases in the storage environment of the blood glucose monitoring device. These gases may come from the air in the storage environment or other factors. If the concentration is too high, it will exacerbate the chemical reaction of the test strips of the blood glucose monitoring device, resulting in inaccurate test results.

[0031] is the light uniformity in the storage environment of the blood glucose monitoring device. Uneven illumination will cause uneven reactions of the test strips, resulting in inaccurate test results.

[0032] is the moisture content in the storage environment of the blood glucose monitoring device. If the moisture content deviates too much from the reference value, it may cause corrosion or damage to the internal components of the device, reduce the performance of the blood glucose monitoring device, and at the same time affect the stability and accuracy of the test strips of the blood glucose monitoring device, further resulting in large errors in blood glucose data.

[0033] It is the reference illumination uniformity, representing the reference value for analyzing the illumination uniformity of the storage environment where the blood glucose monitoring device is located. It is numerically specified by the device maintenance specialist. In an exemplary embodiment, the value of the reference illumination uniformity is 1, indicating that the first-ranked illuminance value is equal to the last-ranked illuminance value, thus indicating relatively uniform illumination.

[0034] It is the reference moisture content, representing the reference value for analyzing the moisture content of the storage environment where the blood glucose monitoring device is located. It is numerically specified by the device maintenance specialist based on historical work experience.

[0035] e is the natural constant. It is the influence factor corresponding to the preset target gas total concentration unit value in the information management library, representing the numerical value of the influence degree of the target gas total concentration unit value on the storage environment rationality index. A mapping set of the target gas total concentration and its corresponding influence factor is constructed based on the relationship between the historical target gas total concentration and the storage environment rationality index, and the real-time target gas total concentration is input into the mapping set to obtain the influence factor corresponding to the target gas total concentration unit value. Meanwhile, in this example, its value range is [0, 1].

[0036] It is the correction factor corresponding to the preset illumination uniformity in the information management library, representing the numerical value of the correction degree for the numerical change of the illumination uniformity. A mapping set of the illumination uniformity and its corresponding correction factor is constructed based on the relationship between the historical illumination uniformity and the storage environment rationality index, and the real-time illumination uniformity is input into the mapping set to obtain the correction factor corresponding to the illumination uniformity. Meanwhile, in this example, its value range is [0, 1].

[0037] It is the correction factor corresponding to the preset moisture content in the information management library, representing the numerical value of the correction degree for the numerical change of the moisture content. A mapping set of the moisture content and its corresponding correction factor is constructed based on the relationship between the historical moisture content and the storage environment rationality index, and the real-time moisture content is input into the mapping set to obtain the correction factor corresponding to the moisture content. Meanwhile, in this example, its value range is [0, 1].

[0038] Among them, is the reasonable index of the storage environment of the blood glucose monitoring device. When the moisture content deviates greatly from the reference value, it will cause abnormal reactions between the test strips of the blood glucose monitoring device and some chemical substances in the air. When the concentration of the target gas increases, this abnormal reaction will become more intense. At the same time, if the light uniformity also deviates greatly from the reference value, that is, the light is uneven, the reactions of different parts of the test strips of the blood glucose monitoring device will become uneven, the performance of the test strips will decline, and further affect the accuracy of the test results of the blood glucose monitoring device, indicating that the storage environment of the blood glucose monitoring device is relatively unreasonable. If there are too many target gases in the storage environment, that is, some chemical substances that may react with the test strips of the blood glucose monitoring device, these gases will intensify the reaction of the test strips, thus affecting the accuracy of the blood glucose test results. If the light uniformity deviates greatly from the reference value, the performance differences of different parts of the test strips of the blood glucose monitoring device will be large, resulting in inaccurate test results when measuring blood glucose content. If the moisture content deviates too much from the reference value, it may cause corrosion or damage to the internal components of the blood glucose monitoring device, and at the same time, it will also affect the stability and accuracy of the test strips. Therefore, the total concentration of the target gas, the light uniformity and the moisture content are interrelated and jointly affect the reasonable index of the storage environment of the blood glucose monitoring device. By quantitatively analyzing these three parameters, the negative impact of external environmental factors on blood glucose data can be analyzed, so as to accurately locate the factors affecting the accuracy of blood glucose data.

[0039] Further, the specific evaluation process for evaluating the reasonable index of the storage environment of the blood glucose monitoring device is as follows: extract the concentrations of each target gas at the end time point of the environmental analysis cycle from the storage environment parameters of the blood glucose monitoring device, and accumulate them to obtain the total concentration of the target gas in the storage environment of the blood glucose monitoring device; the above environmental analysis cycle refers to the time period for analyzing the storage environment of the blood glucose monitoring device, and its specific duration is specified by the device maintenance specialist; the above target gases include volatile organic compounds (such as toluene, chloroform, xylene), and the concentrations of each target gas are detected by a portable volatile organic compound detector and accumulated to obtain the total concentration of the target gas.

[0040] Extract the illuminance values of each illuminance detection point in the storage environment of the blood glucose monitoring device at the end time point of the environmental analysis period from the storage environment parameters of the blood glucose monitoring device. Sort the illuminance values in ascending order, extract the first-ranked illuminance value and the last-ranked illuminance value, and perform a ratio process to obtain the light uniformity of the storage environment of the blood glucose monitoring device. The above-mentioned each illuminance detection point refers to the position points randomly arranged by the device maintenance specialist in the storage environment of the blood glucose monitoring device. In an exemplary embodiment, each illuminance detection point refers to the position points randomly arranged by the device maintenance specialist in the endocrine department. The illuminance values of the above-mentioned each illuminance detection point at the end time point of the environmental analysis period are measured by an illuminometer. The above-mentioned light uniformity refers to the first-ranked illuminance value divided by the last-ranked illuminance value. The closer the light uniformity is to the reference light uniformity, the more uniform the light is.

[0041] Extract the average air pressure and average water vapor partial pressure in the storage environment of the blood glucose monitoring device during the environmental analysis period from the storage environment parameters of the blood glucose monitoring device, and perform data analysis to obtain the moisture content in the storage environment of the blood glucose monitoring device. Thus, comprehensively evaluate and obtain the storage environment rationality index of the blood glucose monitoring device. The above-mentioned average air pressure is obtained by measuring the real-time pressure in the storage environment of the blood glucose monitoring device during the environmental analysis period with a barometer and performing mean value processing to obtain the average air pressure. The above-mentioned average water vapor partial pressure is obtained by measuring the real-time water vapor partial pressure in the storage environment of the blood glucose monitoring device during the environmental analysis period with a water vapor partial pressure meter and performing mean value processing to obtain the average water vapor partial pressure. The specific data analysis process of the moisture content in the storage environment of the blood glucose monitoring device is as follows: , where is the average water vapor partial pressure, is the average air pressure.

[0042] S2. Collect the performance parameters of the blood glucose monitoring device, analyze the performance compliance index of the blood glucose monitoring device, and compare it with the performance compliance threshold. If the performance compliance index of the blood glucose monitoring device is less than the performance compliance threshold, then transmit the performance parameters of the blood glucose monitoring device to the second type of fault parameter set of the blood glucose monitoring device, and continue to execute S3. On the contrary, if the performance compliance index of the blood glucose monitoring device is greater than or equal to the performance compliance threshold, then continue to execute S3.

[0043] The above performance compliance threshold refers to the minimum value within the reasonable range of the performance compliance index of the blood glucose monitoring device, which is specified by the device maintenance specialist based on historical work experience. If the performance compliance index of the blood glucose monitoring device is less than the performance compliance threshold, it indicates that the self-performance of the blood glucose monitoring device does not meet the ideal requirements, which will result in impaired accuracy of blood glucose monitoring data. Therefore, the performance parameters of the blood glucose monitoring device are transmitted to the second type of fault parameter set of the blood glucose monitoring device. The second type of fault parameter set of the blood glucose monitoring device represents a set that stores the performance parameters of the blood glucose monitoring device. If there is data in this set, it indicates that the combined negative impact of the data in this set on the performance of the blood glucose monitoring device is relatively large. In an exemplary embodiment, the second type of fault parameter set of the blood glucose monitoring device includes the voltage fluctuation ratio coefficient of the blood glucose monitoring device, the color offset value of the test strip to which the blood glucose monitoring device belongs, and the degree of aging of the blood glucose monitoring device. If the performance compliance index of the blood glucose monitoring device is greater than or equal to the performance compliance threshold, it indicates that the self-performance of the blood glucose monitoring device meets the ideal requirements, and there is no need to generate the second type of fault parameter set of the blood glucose monitoring device, and S3 is directly continued to be executed.

[0044] The performance parameters of the above blood glucose monitoring device. In this embodiment, the performance parameters include a voltage fluctuation curve (the abscissa is the performance detection time point, the unit is second, and the ordinate is the voltage value, the unit is volt), a hexadecimal color value, and the surface image parameters of the blood glucose monitoring device at the end time point of the performance detection cycle. The surface image parameters include the lengths of each crack (the unit is millimeter). In addition to the above parameters, this example can also be applied to other parameters, but the directions (i.e., positive and negative relationships) that these parameters can reflect are the same.

[0045] Specifically, for analyzing the performance compliance index of the blood glucose monitoring device, the specific analysis process is as follows: Extract the voltage fluctuation curve of the power supply to which the blood glucose monitoring device belongs during the performance detection cycle from the performance parameters of the blood glucose monitoring device. Locate each voltage detection point on the voltage fluctuation curve, perform mean value analysis on the ordinates corresponding to each voltage detection point to obtain the average voltage value of the power supply to which the blood glucose monitoring device belongs during the performance detection cycle. Locate the voltage value corresponding to the highest position point and the lowest position point of the voltage fluctuation curve, respectively perform difference processing with the average voltage value, and perform ratio processing on the two results of the difference processing to obtain the voltage fluctuation ratio coefficient of the blood glucose monitoring device. The above performance detection cycle refers to the time period for analyzing the self-performance of the blood glucose monitoring device, and its specific duration is formulated by the device maintenance specialist. The above voltage fluctuation curve is as Figure 3As shown, the horizontal axis is the performance test time point, the unit is second, and the vertical axis is the voltage value, the unit is volt, which is extracted from the data of the power supply of the blood glucose monitoring device recorded by the voltage sensor during the performance test cycle; the above-mentioned voltage test points refer to a number of data points randomly located on the voltage fluctuation curve by the equipment maintenance specialist; the voltage fluctuation proportional coefficient of the above-mentioned blood glucose monitoring device, the specific ratio processing process is: Figure 3 As shown, the numerical value obtained by processing the difference between the voltage value corresponding to the highest position point of the voltage fluctuation curve and the average voltage value is marked as the maximum voltage deviation value 6, and the numerical value obtained by processing the difference between the voltage value corresponding to the lowest position point of the voltage fluctuation curve and the average voltage value is marked as the minimum voltage deviation value 5. The voltage fluctuation proportional coefficient is the result of dividing the maximum voltage deviation value by the minimum voltage deviation value. The numerical value obtained by processing the difference between the voltage value corresponding to the lowest position point of the voltage fluctuation curve and the average voltage value is a negative value. In this embodiment, the absolute value of the numerical value is taken for calculation and analysis.

[0046] The hexadecimal color values ​​of each detection position point of the test strip belonging to the blood glucose monitoring device at the end time of the performance detection cycle are extracted from the performance parameters of the blood glucose monitoring device, and the standard deviation processing is performed to obtain the color offset value of the test strip belonging to the blood glucose monitoring device; the above-mentioned detection position points refer to the position points randomly arranged by the equipment maintenance specialist on the test strip belonging to the blood glucose monitoring device; the hexadecimal color values ​​of the above-mentioned detection position points at the end time of the performance detection cycle are obtained by taking a complete image of the surface of the test strip belonging to the blood glucose monitoring device with a high-definition camera, and using a color picking tool to obtain the red color of each detection position point Green and blue values, the red, green and blue values ​​(intensity values ​​of the three components of red, green and blue, ranging from 0 to 255) are formatted into a hexadecimal string, that is, the value of each component is converted into two hexadecimal numbers (if less than two digits, the leading 0 is added), and then these three hexadecimal numbers are sequentially spliced ​​together to achieve, for example, the red, green and blue values ​​​​(255,165,0) The corresponding hexadecimal color value is #FFA500. In this embodiment, the numerical part of the hexadecimal color value is converted to decimal for calculation, such as #FFA500, and the value substituted into the formula is 17252415; assuming is the result of the hexadecimal color value mean processing of each detection position point at the end time of the performance detection cycle, and the specific standard deviation processing process of the color offset value is: , is the hexadecimal color value of the sth detection position at the end of the performance detection cycle, s is the number of each detection position, , q is the total number of detected position points.

[0047] Extract the surface image parameters of the blood glucose monitoring device at the end time point of the performance detection cycle from the performance parameters of the blood glucose monitoring device, locate and accumulate the lengths of each crack of the blood glucose monitoring device from the surface image parameters to obtain the total crack length of the blood glucose monitoring device, and match it with the aging degree corresponding to each total crack length interval stored in the information management library to obtain the aging degree of the blood glucose monitoring device. The above surface image parameters refer to those obtained by the device maintenance specialist by photographing the surface shell of the blood glucose monitoring device with a high-definition camera. The specific positioning method for the lengths of each crack of the blood glucose monitoring device is as follows: Use the edge detection algorithm based on mathematical morphology to process the surface image parameters, and thus obtain the lengths of each crack. The specific matching process for the aging degree of the blood glucose monitoring device is as follows: Each total crack length interval corresponds to an aging degree. Query the total crack length interval to which the total crack length of the blood glucose monitoring device belongs, and the aging degree corresponding to this total crack length interval is the aging degree of the blood glucose monitoring device. It should be noted that the aging degree corresponding to each total crack length interval is formulated by the device maintenance specialist based on historical work experience in terms of numerical values and corresponding rules.

[0048] Thus, comprehensively analyze to obtain the performance compliance index of the blood glucose monitoring device. In this embodiment, the above performance compliance index of the blood glucose monitoring device is obtained through comprehensive analysis of the voltage fluctuation ratio coefficient of the blood glucose monitoring device, the color offset value of the test strip to which the blood glucose monitoring device belongs, and the aging degree of the blood glucose monitoring device. It is a numerical value used to analyze the performance compliance degree of the blood glucose monitoring device, and the specific expression is:

[0049] ;

[0050] is the voltage fluctuation ratio coefficient of the blood glucose monitoring device, which reflects the degree to which the power supply voltage of the blood glucose monitoring device deviates from its average voltage. An overly large voltage fluctuation ratio coefficient will cause the current signal to be unstable, thereby affecting the accuracy of the blood glucose measurement value.

[0051] is the color offset value of the test strip to which the blood glucose monitoring device belongs. A larger color offset value of the test strip indicates that the performance of the test strip itself is poor, and thus it cannot meet the high-precision blood glucose monitoring process.

[0052] is the aging degree of the blood glucose monitoring device. As the aging degree of the blood glucose monitoring device increases, the measurement accuracy of the blood glucose monitoring device will gradually decrease.

[0053] is the reference value of the voltage fluctuation ratio coefficient, representing the reference value for analyzing the voltage fluctuation ratio coefficient of the blood glucose monitoring device, which is specified by the device maintenance specialist. In an exemplary embodiment, this value is specified as 1. The reference value of the voltage fluctuation ratio coefficient indicates that the difference between the highest position point of the voltage fluctuation curve and the average voltage is equal to the voltage value corresponding to the lowest position point and the average voltage value, indicating that the voltage fluctuation is relatively gentle without drastic fluctuations.

[0054] e is the natural constant, is the correction factor corresponding to the voltage fluctuation ratio coefficient preset in the management information base, representing the value for correcting the numerical change of the voltage fluctuation ratio coefficient. It is to construct a mapping set of the voltage fluctuation ratio coefficient and its corresponding correction factor based on the relationship between the historical voltage fluctuation ratio coefficient and the performance compliance index, and input the real-time voltage fluctuation ratio coefficient into the mapping set to obtain the correction factor corresponding to the voltage fluctuation ratio coefficient. At the same time, in this example, its value range is [0, 1].

[0055] is the influence factor corresponding to the unit value of the color offset preset in the management information base, representing the value of the influence degree of the unit value of the color offset on the performance compliance index. It is to construct a mapping set of the color offset and its corresponding influence factor based on the relationship between the historical color offset and the performance compliance index, and input the real-time color offset into the mapping set to obtain the influence factor corresponding to the unit value of the color offset. At the same time, in this example, its value range is [0, 1].

[0056] is the influence factor corresponding to the unit value of the aging degree preset in the management information base, representing the value of the influence degree of the unit value of the aging degree on the performance compliance index. It is to construct a mapping set of the aging degree and its corresponding influence factor based on the relationship between the historical aging degree and the performance compliance index, and input the real-time aging degree into the mapping set to obtain the influence factor corresponding to the unit value of the aging degree. At the same time, in this example, its value range is [0, 1].

[0057] Among them, The performance compliance index of the blood glucose monitoring device. The aging degree of the blood glucose monitoring device is relatively high, resulting in corresponding aging phenomena in the power supply and test strips of the blood glucose monitoring device. This aging phenomenon not only affects the stability of the power supply of the blood glucose monitoring device, making it unable to provide a stable voltage output, but also causes the color of the test strips to become uneven, having a negative impact on the accuracy of the test results. Therefore, the three parameters jointly represent the performance of the blood glucose monitoring device. The performance of the blood glucose monitoring device requires the device to provide stable measurement results. However, a large deviation of the voltage fluctuation ratio coefficient from the reference value, a large color offset value, and a high aging degree all lead to abnormal blood glucose measurement data. Therefore, by quantitatively analyzing the three parameters, the performance problems of the blood glucose monitoring device can be identified, which helps to quickly locate the root cause of the problems with the blood glucose monitoring device, and thus take targeted maintenance measures to improve the accuracy of the blood glucose monitoring device in monitoring blood glucose data.

[0058] S3. Test each sample reagent. Based on the test results of each sample reagent, obtain the test data curve of the blood glucose monitoring device, determine the data accuracy coefficient of the blood glucose monitoring device, and compare it with the data accuracy threshold. If the data accuracy coefficient of the blood glucose monitoring device is less than the data accuracy threshold, then transmit the test data of the blood glucose monitoring device to the third type of fault parameter set of the blood glucose monitoring device, and continue to execute S4. Otherwise, if the data accuracy coefficient of the blood glucose monitoring device is greater than or equal to the data accuracy threshold, then continue to execute S4.

[0059] The above data accuracy threshold refers to the minimum value within the reasonable range of the data accuracy coefficient of the blood glucose monitoring device, which is specified by the device maintenance specialist based on historical work experience. If the data accuracy coefficient of the blood glucose monitoring device is less than the data accuracy threshold, it indicates that the monitoring data performance of the blood glucose monitoring device does not meet the ideal requirements, and the accuracy of the blood glucose monitoring data is impaired. Therefore, the test data of the blood glucose monitoring device is transmitted to the third type of fault parameter set of the blood glucose monitoring device. The third type of fault parameter set of the blood glucose monitoring device represents a set that stores the test data of the blood glucose monitoring device. If there is data in this set, it indicates that the comprehensive negative impact of the data in this set on the performance of the blood glucose monitoring device is relatively large. In an exemplary embodiment, the third type of fault parameter set of the blood glucose monitoring device includes the receiving interval duration deviation value, the analysis duration deviation value, and the total blood glucose content deviation value. If the data accuracy coefficient of the blood glucose monitoring device is greater than or equal to the data accuracy threshold, it indicates that the monitoring data performance of the blood glucose monitoring device meets the ideal requirements, and there is no need to generate the third type of fault parameter set of the blood glucose monitoring device, and directly continue to execute S4.

[0060] In a specific embodiment, the present invention obtains the performance compliance index of the blood glucose monitoring device by comprehensively analyzing the voltage fluctuation ratio coefficient of the blood glucose monitoring device, the color offset value of the test strip to which the blood glucose monitoring device belongs, and the aging degree of the blood glucose monitoring device, which helps to timely discover potential problems that may be overlooked when the blood glucose monitoring device monitors blood glucose data, thereby improving the comprehensiveness of the performance evaluation of the blood glucose monitoring device and ensuring the accuracy of the blood glucose monitoring device in monitoring blood glucose.

[0061] Specifically, the obtaining of the test data curve of the blood glucose monitoring device specifically refers to: the blood glucose data management system receives each test data of the blood glucose monitoring device and generates a test data curve of the blood glucose monitoring device. Each of the above test data includes the blood glucose content and the data reception time point. It should be noted that the specific generation process is: a computer programmer writes curve generation code, and the matrix laboratory software to which the blood glucose data management system belongs runs the curve generation code and inputs each test data of the blood glucose monitoring device, thereby generating a test data curve of the blood glucose monitoring device.

[0062] It should be noted that the blood glucose data management system is a system used to receive the data monitored by the blood glucose monitoring device and perform data analysis.

[0063] Specifically, the testing of each sample reagent has the following specific testing process: the blood glucose monitoring device is used to measure each sample reagent, and the measurement interval time between adjacent sample reagents is equal, thereby obtaining the test results of each sample reagent, which are recorded as each test data of the blood glucose monitoring device; each of the above sample reagents is a sample that needs to be tested for blood glucose, and is prepared by a pharmaceutical professional according to each preset blood glucose content; the test results of each of the above sample reagents are extracted from the log of receiving information by the blood glucose data management system, and each test result includes the blood glucose content and the data reception time point.

[0064] Further, the determination of the data precision coefficient of the blood glucose monitoring device has the following specific determination process: locate the data reception time point of each test data point on the test data curve of the blood glucose monitoring device, perform a difference process on the data reception time point of each test data point and the historical adjacent data reception time point to obtain the reception interval time of each test data, and perform a standard deviation process to obtain the reception interval time deviation value of the test data; the test data curve of the above blood glucose monitoring device is as Figure 4As shown, the abscissa is the data reception time point in seconds, and the ordinate is the blood glucose content in millimoles per liter. The data reception time point of each of the above test data points refers to the time point when the blood glucose data management system receives the blood glucose content of each sample reagent tested by the blood glucose monitoring device, which is extracted from the analysis log of the blood glucose data management system. The reception interval duration of each of the above test data, in an exemplary embodiment, can be represented as reception interval duration 3 and reception interval duration 4. Since there is no historical adjacent data reception time point for data reception time point 1, its reception interval duration is 0. The specific standard deviation processing process of the above reception interval duration deviation value is the same as that of the color offset value standard deviation processing process. Analyzing the reception interval duration deviation value is to check the stability of the data uploaded by the blood glucose monitoring device.

[0065] Obtain the data test start time point corresponding to each test data point, perform a difference process on the data reception time point of each test data point and the data test start time point corresponding to each test data point to obtain the analysis duration of each test data, and perform standard deviation processing to obtain the analysis duration deviation value of the test data. The data test start time point corresponding to each of the above test data points is set by the equipment maintenance specialist when testing each sample reagent. The above analysis duration, as Figure 4 shown, subtracting the corresponding data test start time point 2 from data reception time point 1, the obtained value is the analysis duration. The specific standard deviation processing process of the above analysis duration deviation value is the same as that of the color offset value standard deviation processing process.

[0066] Obtain the preset blood glucose content corresponding to each test data point, locate the blood glucose content of each test data point on the test data curve of the blood glucose monitoring device, perform a difference process with the preset blood glucose content corresponding to each test data point to obtain the blood glucose content deviation value of each test data, and accumulate to obtain the total blood glucose content deviation value of the test data. The preset blood glucose content corresponding to each of the above test data points is specified by the equipment maintenance specialist. The blood glucose content of each of the above test data points is the ordinate corresponding to each test data point.

[0067] Thus, comprehensively determine the data accuracy coefficient of the blood glucose monitoring device. In this embodiment, the data accuracy coefficient of the above blood glucose monitoring device is obtained through comprehensive analysis of the reception interval duration deviation value, analysis duration deviation value, and total blood glucose content deviation value of the test data, and is a numerical value used to determine the data accuracy degree of the blood glucose monitoring device. The specific expression is:

[0068] ;

[0069] For the deviation value of the receiving interval duration of test data, assume that the blood glucose monitoring device is set to measure blood glucose data every 20 seconds, but in fact, the receiving time interval of blood glucose data fluctuates between 20 seconds and 35 seconds. Then this kind of fluctuation affects the deviation value of the receiving interval duration.

[0070] For the deviation value of the analysis duration of test data, where the analysis duration refers to the interval duration between the time when the blood glucose monitoring device starts to measure blood glucose data and the time point when the blood glucose data management system receives the blood glucose data, which reflects the efficiency of the blood glucose monitoring device in processing and analyzing blood glucose data and the response speed of the blood glucose data management system.

[0071] For the total deviation value of blood glucose content of test data, which reflects the accuracy and reliability of the blood glucose monitoring device in blood glucose measurement. The lower the total deviation value of blood glucose content, the higher the measurement accuracy of the blood glucose monitoring device.

[0072] e is the natural constant, It is the influence factor corresponding to the unit value of the deviation value of the receiving interval duration preset in the information management library, which represents the numerical value of the influence degree of the unit value of the deviation value of the receiving interval duration on the data precision coefficient. It is to construct a mapping set of the deviation value of the receiving interval duration and its corresponding influence factor according to the relationship between the historical deviation value of the receiving interval duration and the data precision coefficient, and input the real-time deviation value of the receiving interval duration into the mapping set to obtain the influence factor corresponding to the unit value of the deviation value of the receiving interval duration. At the same time, in this example, its value range is [0,1].

[0073] It is the influence factor corresponding to the unit value of the deviation value of the analysis duration preset in the information management library, which represents the numerical value of the influence degree of the unit value of the deviation value of the analysis duration on the data precision coefficient. It is to construct a mapping set of the deviation value of the analysis duration and its corresponding influence factor according to the relationship between the historical deviation value of the analysis duration and the data precision coefficient, and input the real-time deviation value of the analysis duration into the mapping set to obtain the influence factor corresponding to the unit value of the deviation value of the analysis duration. At the same time, in this example, its value range is [0,1].

[0074] It is the influence factor corresponding to the unit value of the total deviation value of blood glucose content preset in the information management library, which represents the numerical value of the influence degree of the unit value of the total deviation value of blood glucose content on the data precision coefficient. It is to construct a mapping set of the total deviation value of blood glucose content and its corresponding influence factor according to the relationship between the historical total deviation value of blood glucose content and the data precision coefficient, and input the real-time total deviation value of blood glucose content into the mapping set to obtain the influence factor corresponding to the unit value of the total deviation value of blood glucose content. At the same time, in this example, its value range is [0,1].

[0075] Among them, The data precision coefficient of the blood glucose monitoring device, with a significant increase in the deviation of the data reception interval duration, directly reflects the deficiency of the blood glucose monitoring device in terms of data output stability. This instability weakens the basic measurement ability of the blood glucose monitoring device, making it unable to fully capture the subtle characteristics of blood glucose changes, resulting in the analysis results deviating from the actual blood glucose level, that is, the total deviation value of blood glucose content increases. When the blood glucose monitoring device falls into an unstable state due to a large deviation in the reception interval duration, its data processing and transmission capabilities are also affected, leading to an increase in the fluctuation and uncertainty of the analysis duration, and increasing the deviation value of the analysis duration. These three parameters together constitute a multi-dimensional framework for evaluating the data accuracy of the blood glucose monitoring device. The deviation value of the data reception interval duration, as the primary indicator for evaluating the stability of the blood glucose monitoring device, is directly related to the continuity and integrity of the data stream. The deviation value of the analysis duration reflects the performance of the blood glucose monitoring device in terms of data processing efficiency. The total deviation value of blood glucose content, as the core indicator for measuring the measurement accuracy of the blood glucose monitoring device, directly reflects the difference between the output result of the blood glucose monitoring device and the true blood glucose level. Therefore, by quantitatively analyzing these three parameters, the overall performance of the blood glucose monitoring device can be comprehensively evaluated from multiple dimensions, which helps to discover potential problems in different links of the blood glucose monitoring device and provides a comprehensive basis for subsequent improvement and optimization.

[0076] In this exemplary embodiment, the change table of the data precision coefficient of the above blood glucose monitoring device and its corresponding parameters is shown in Table 1:

[0077] Table 1 Change table of the data precision coefficient of the blood glucose monitoring device and its corresponding parameters

[0078] Receiving interval duration deviation value / Percentage Analysis duration deviation value / Percentage Total blood glucose content deviation value / millimole per liter Data accuracy coefficient / Percentage 50 20 3 40.7 65 23 3.52 39.0 71 30 4 37.8

[0079] In this exemplary embodiment, the value of the influencing factor corresponding to the unit value of the deviation value of the reception interval duration is set to 0.4, the value of the influencing factor corresponding to the unit value of the deviation value of the analysis duration is set to 0.35, and the value of the influencing factor corresponding to the unit value of the total deviation value of blood glucose content is set to 0.25. It can be seen from Table 1 that the data precision coefficient will decrease with the increase of the deviation value of the reception interval duration, the increase of the deviation value of the analysis duration, and the increase of the total deviation value of blood glucose content.

[0080] S4. Integrate the first type of fault parameter set of the blood glucose monitoring device, the second type of fault parameter set of the blood glucose monitoring device, and the third type of fault parameter set of the blood glucose monitoring device to generate a fault parameter set of the blood glucose monitoring device, thereby monitoring and feedback the fault data of the blood glucose monitoring device.

[0081] Specifically, for the monitoring and feedback of the fault data of the blood glucose monitoring device, the specific feedback process is as follows: The blood glucose data management system feeds back the fault parameter set of the blood glucose monitoring device, thereby completing the monitoring and feedback of the fault data of the blood glucose monitoring device. It should be noted that the specific feedback process is: The blood glucose data management system feeds back the fault parameter set of the blood glucose monitoring device to the device maintenance specialist in the form of a system log. The device maintenance specialist maintains the blood glucose monitoring device according to the fault data of the blood glucose monitoring device involved in the fault parameter set of the blood glucose monitoring device, so as to ensure the accuracy of the blood glucose data monitored by the blood glucose monitoring device. In an exemplary embodiment, the fault parameter set of the blood glucose monitoring device involves the first type of fault parameter set of the blood glucose monitoring device. The device maintenance specialist can improve the influence of the parameters involved in the first type of fault parameter set of the blood glucose monitoring device by transferring the storage location point of the blood glucose monitoring device.

[0082] Further, for the generation of the fault parameter set of the blood glucose monitoring device, the specific generation process is as follows: The blood glucose data management system integrates and packages the first type of fault parameter set of the blood glucose monitoring device, the second type of fault parameter set of the blood glucose monitoring device, and the third type of fault parameter set of the blood glucose monitoring device, thereby generating the fault parameter set of the blood glucose monitoring device. It should be noted that if a certain blood glucose monitoring device only has the first type of fault parameter set and the third type of fault parameter set of the blood glucose monitoring device, only the first type of fault parameter set and the third type of fault parameter set of the blood glucose monitoring device need to be packaged. In this embodiment, the packaging refers to integrating various fault parameter sets into a system log.

[0083] In a specific embodiment, the present invention provides an endocrinology blood glucose data monitoring method and system. By evaluating the storage environment parameters of the blood glucose monitoring device, the first type of fault parameter set of the blood glucose monitoring device is generated. By analyzing the performance parameters of the blood glucose monitoring device, the second type of fault parameter set of the blood glucose monitoring device is generated. By determining the data accuracy coefficient of the blood glucose monitoring device, the third type of fault parameter set of the blood glucose monitoring device is generated, realizing the comprehensive monitoring of the blood glucose monitoring device. Thereby, the monitoring and feedback of the fault data of the blood glucose monitoring device are carried out, which helps to quickly identify and locate the specific problem types existing in the blood glucose monitoring device, provides a scientific basis for the maintenance of the blood glucose monitoring device, and ensures the accuracy and continuity of the blood glucose data monitoring results.

[0084] Refer to Figure 2 As shown, in the second aspect of the present invention, a system applying the endocrinology blood glucose data monitoring method as described above is provided, including: a storage environment evaluation module, a device performance analysis module, a data accuracy determination module, and a fault monitoring and feedback module.

[0085] In a second aspect of the present invention, there is provided a system applying the method for monitoring blood glucose data in the endocrinology department as described above. The system further includes an information management library, which is used to store influence factors corresponding to the unit value of the total concentration of the target gas, correction factors corresponding to the light uniformity, correction factors corresponding to the moisture content, aging degrees corresponding to each total crack length interval, correction factors corresponding to the voltage fluctuation proportionality coefficient, influence factors corresponding to the unit value of the color shift value, influence factors corresponding to the unit value of the aging degree, influence factors corresponding to the unit value of the receiving interval duration deviation value, influence factors corresponding to the unit value of the analysis duration deviation value, and influence factors corresponding to the unit value of the total blood glucose content deviation value.

[0086] The storage environment evaluation module is respectively connected to the device performance analysis module and the information management library. The device performance analysis module is respectively connected to the data accuracy determination module and the information management library. The data accuracy determination module is respectively connected to the fault monitoring and feedback module and the information management library.

[0087] The storage environment evaluation module is used to mark the electronic device for monitoring endocrinology blood glucose data as a blood glucose monitoring device, obtain the storage environment parameters of the blood glucose monitoring device, evaluate the reasonable index of the storage environment of the blood glucose monitoring device, compare it with the reasonable threshold of the storage environment. If the reasonable index of the storage environment of the blood glucose monitoring device is less than the reasonable threshold of the storage environment, the storage environment parameters of the blood glucose monitoring device will be transmitted to the first type of fault parameter set of the blood glucose monitoring device, and the device performance analysis module will continue to be executed. On the contrary, if the reasonable index of the storage environment of the blood glucose monitoring device is greater than or equal to the reasonable threshold of the storage environment, the device performance analysis module will continue to be executed.

[0088] The device performance analysis module is used to collect the performance parameters of the blood glucose monitoring device, analyze the performance compliance index of the blood glucose monitoring device, compare it with the performance compliance threshold. If the performance compliance index of the blood glucose monitoring device is less than the performance compliance threshold, the performance parameters of the blood glucose monitoring device will be transmitted to the second type of fault parameter set of the blood glucose monitoring device, and the data accuracy determination module will continue to be executed. On the contrary, if the performance compliance index of the blood glucose monitoring device is greater than or equal to the performance compliance threshold, the data accuracy determination module will continue to be executed.

[0089] The data accuracy determination module is used to test each sample reagent. Based on the test results of each sample reagent, obtain the test data curve of the blood glucose monitoring device, determine the data accuracy coefficient of the blood glucose monitoring device, compare it with the data accuracy threshold. If the data accuracy coefficient of the blood glucose monitoring device is less than the data accuracy threshold, the test data of the blood glucose monitoring device will be transmitted to the third type of fault parameter set of the blood glucose monitoring device, and the fault monitoring and feedback module will continue to be executed. On the contrary, if the data accuracy coefficient of the blood glucose monitoring device is greater than or equal to the data accuracy threshold, the fault monitoring and feedback module will continue to be executed.

[0090] The fault monitoring and feedback module is used to integrate the first type of fault parameter set of the blood glucose monitoring device, the second type of fault parameter set of the blood glucose monitoring device, and the third type of fault parameter set of the blood glucose monitoring device to generate a fault parameter set of the blood glucose monitoring device, thereby monitoring and feeding back the fault data of the blood glucose monitoring device.

[0091] The above content is only an example and explanation of the structure of the present invention. Those skilled in the art of the present technology can make various modifications or supplements to the described specific embodiments or use similar methods for substitution, as long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A method for monitoring blood sugar data in endocrinology department, characterized in that: include: S1. Mark the electronic device that monitors blood glucose data of the endocrinology department as a blood glucose monitoring device, obtain the storage environment parameters of the blood glucose monitoring device, evaluate the storage environment rationality index of the blood glucose monitoring device, and compare it with the storage environment rationality threshold. If the storage environment rationality index of the blood glucose monitoring device is less than the storage environment rationality threshold, the storage environment parameters of the blood glucose monitoring device are transmitted to the first type of fault parameter set of the blood glucose monitoring device, and continue to execute S2. On the contrary, if the storage environment rationality index of the blood glucose monitoring device is greater than or equal to the storage environment rationality threshold, continue to execute S2. S2. Collect the performance parameters of the blood glucose monitoring device, analyze the performance compliance index of the blood glucose monitoring device, and compare it with the performance compliance threshold. If the performance compliance index of the blood glucose monitoring device is less than the performance compliance threshold, the performance parameters of the blood glucose monitoring device are transmitted to the second type of fault parameter set of the blood glucose monitoring device, and S3 is continued to be executed. On the contrary, if the performance compliance index of the blood glucose monitoring device is greater than or equal to the performance compliance threshold, S3 is continued to be executed. S3. Test each sample reagent, obtain the test data curve of the blood glucose monitoring device based on the test results of each sample reagent, determine the data accuracy coefficient of the blood glucose monitoring device, and compare it with the data accuracy threshold. If the data accuracy coefficient of the blood glucose monitoring device is less than the data accuracy threshold, the test data of the blood glucose monitoring device is transmitted to the third type fault parameter set of the blood glucose monitoring device, and continue to execute S4. On the contrary, if the data accuracy coefficient of the blood glucose monitoring device is greater than or equal to the data accuracy threshold, continue to execute S4; S4. Integrate the first type fault parameter set, the second type fault parameter set and the third type fault parameter set of the blood glucose monitoring device to generate a blood glucose monitoring device fault parameter set, thereby monitoring and feeding back the fault data of the blood glucose monitoring device.

2. The method for monitoring blood sugar data in endocrinology department according to claim 1, characterized in that: The specific evaluation process of evaluating the storage environment rationality index of the blood glucose monitoring device is as follows: Extracting the target gas concentrations of the storage environment of the blood glucose monitoring device at the end time of the environmental analysis cycle from the storage environment parameters of the blood glucose monitoring device, and accumulating them to obtain the total target gas concentration of the storage environment of the blood glucose monitoring device; Extracting the illumination value of each illumination detection point of the storage environment to which the blood glucose monitoring device belongs at the end time point of the environmental analysis cycle from the storage environment parameters to which the blood glucose monitoring device belongs, sorting the illumination values ​​in ascending order, extracting the illumination value ranked first and the illumination value ranked last, performing ratio processing, and obtaining the illumination uniformity of the storage environment to which the blood glucose monitoring device belongs; The average air pressure and average water vapor partial pressure of the storage environment of the blood glucose monitoring device during the environmental analysis period are extracted from the storage environment parameters of the blood glucose monitoring device, and the moisture content of the storage environment of the blood glucose monitoring device is obtained through data analysis. Based on this, a comprehensive evaluation is conducted to obtain the reasonableness index of the storage environment of the blood glucose monitoring device.

3. The method for monitoring blood sugar data in endocrinology department according to claim 2, characterized in that: The storage environment rationality index of the blood glucose monitoring device is specifically expressed as: Among them, ES is the reasonable index of the storage environment of the blood glucose monitoring device, TCC is the total concentration of the target gas in the storage environment of the blood glucose monitoring device, IU is the uniformity of light in the storage environment of the blood glucose monitoring device, MC is the humidity content of the storage environment of the blood glucose monitoring device, and IU c is the reference illumination uniformity, MC c is the reference moisture content, cs1 is the influencing factor corresponding to the unit value of the target gas total concentration preset in the information management library, cs2 is the correction factor corresponding to the illumination uniformity preset in the information management library, and cs3 is the correction factor corresponding to the moisture content preset in the information management library.

4. The method for monitoring blood sugar data in endocrinology department according to claim 1, characterized in that: The specific analysis process of analyzing the performance compliance index of the blood glucose monitoring device is as follows: Extract the voltage fluctuation curve of the power supply to which the blood glucose monitoring device belongs within the performance detection period from the performance parameters of the blood glucose monitoring device, locate each voltage detection point on the voltage fluctuation curve, perform mean analysis on the ordinate corresponding to each voltage detection point, and obtain the average voltage value of the power supply to which the blood glucose monitoring device belongs within the performance detection period, locate the voltage value corresponding to the highest position point and the voltage value corresponding to the lowest position point of the voltage fluctuation curve, perform difference processing on them respectively with the average voltage value, and perform ratio processing on the two results of the difference processing to obtain the voltage fluctuation proportional coefficient of the blood glucose monitoring device; Extracting the hexadecimal color value of each detection position point of the test strip belonging to the blood glucose monitoring device at the end time of the performance detection cycle from the performance parameters of the blood glucose monitoring device, and performing standard deviation processing to obtain the color offset value of the test strip belonging to the blood glucose monitoring device; The surface image parameters of the blood glucose monitoring device at the end time of the performance test cycle are extracted from the performance parameters of the blood glucose monitoring device, and the lengths of each crack of the blood glucose monitoring device are located and accumulated from the surface image parameters to obtain the total crack length of the blood glucose monitoring device. The total crack length is matched with the aging degree corresponding to each total crack length interval stored in the information management library to obtain the aging degree of the blood glucose monitoring device. The performance compliance index of the blood glucose monitoring device is thus obtained through comprehensive analysis.

5. The method for monitoring blood sugar data in endocrinology department according to claim 1, characterized in that: The specific testing process of testing each sample reagent is as follows: using a blood glucose monitoring device to measure each sample reagent, and the measurement intervals of adjacent sample reagents are equal, thereby obtaining the test results of each sample reagent and recording them as test data of the blood glucose monitoring device.

6. The method for monitoring blood sugar data in endocrinology department according to claim 5, characterized in that: The obtaining of the test data curve of the blood glucose monitoring device specifically refers to: the blood glucose data management system receives various test data of the blood glucose monitoring device and generates the test data curve of the blood glucose monitoring device.

7. The method for monitoring blood sugar data in endocrinology department according to claim 6, characterized in that: The specific determination process of determining the data accuracy coefficient of the blood glucose monitoring device is as follows: Locate the data receiving time point of each test data point on the test data curve of the blood glucose monitoring device, perform difference processing on the data receiving time point of each test data point and the historical adjacent data receiving time point to obtain the receiving interval duration of each test data, and perform standard deviation processing to obtain the receiving interval duration deviation value of the test data; Obtain the data test start time point corresponding to each test data point, perform difference processing on the data receiving time point of each test data point and the data test start time point corresponding to each test data point to obtain the analysis time length of each test data, and perform standard deviation processing to obtain the analysis time length deviation value of the test data; Obtain the preset blood glucose content corresponding to each test data point, locate the blood glucose content of each test data point from the test data curve of the blood glucose monitoring device, perform difference processing with the preset blood glucose content corresponding to each test data point, obtain the blood glucose content deviation value of each test data, accumulate to obtain the total blood glucose content deviation value of the test data, and thus comprehensively determine the data accuracy coefficient of the blood glucose monitoring device.

8. The method for monitoring blood sugar data in endocrinology department according to claim 1, characterized in that: The specific process of generating the blood glucose monitoring device fault parameter set is as follows: The blood glucose data management system integrates and packages the first type fault parameter set of the blood glucose monitoring equipment, the second type fault parameter set of the blood glucose monitoring equipment and the third type fault parameter set of the blood glucose monitoring equipment, thereby generating a blood glucose monitoring equipment fault parameter set.

9. The method for monitoring blood sugar data in endocrinology department according to claim 1, characterized in that: The monitoring and feedback of the fault data of the blood glucose monitoring device is specifically carried out as follows: The blood glucose data management system feeds back the fault parameter set of the blood glucose monitoring device, thereby completing the monitoring and feedback of the fault data of the blood glucose monitoring device.

10. A system using the endocrinology blood glucose data monitoring method according to any one of claims 1 to 9, characterized in that: include: A storage environment evaluation module is used to mark an electronic device that monitors blood glucose data of the endocrinology department as a blood glucose monitoring device, obtain storage environment parameters belonging to the blood glucose monitoring device, evaluate the storage environment rationality index of the blood glucose monitoring device, and compare it with the storage environment rationality threshold. If the storage environment rationality index of the blood glucose monitoring device is less than the storage environment rationality threshold, the storage environment parameters belonging to the blood glucose monitoring device are transmitted to the first type of fault parameter set of the blood glucose monitoring device, and the device performance analysis module is continued to be executed. On the contrary, if the storage environment rationality index of the blood glucose monitoring device is greater than or equal to the storage environment rationality threshold, the device performance analysis module is continued to be executed; The device performance analysis module is used to collect the performance parameters of the blood glucose monitoring device, analyze the performance compliance index of the blood glucose monitoring device, and compare it with the performance compliance threshold. If the performance compliance index of the blood glucose monitoring device is less than the performance compliance threshold, the performance parameters of the blood glucose monitoring device are transmitted to the second type of fault parameter set of the blood glucose monitoring device, and the data precision determination module is continued to be executed. On the contrary, if the performance compliance index of the blood glucose monitoring device is greater than or equal to the performance compliance threshold, the data precision determination module is continued to be executed; A data accuracy determination module is used to test each sample reagent, obtain a test data curve of the blood glucose monitoring device based on the test results of each sample reagent, determine the data accuracy coefficient of the blood glucose monitoring device, and compare it with the data accuracy threshold. If the data accuracy coefficient of the blood glucose monitoring device is less than the data accuracy threshold, the test data of the blood glucose monitoring device is transmitted to the third type fault parameter set of the blood glucose monitoring device, and the fault monitoring feedback module is continued to be executed. On the contrary, if the data accuracy coefficient of the blood glucose monitoring device is greater than or equal to the data accuracy threshold, the fault monitoring feedback module is continued to be executed; The fault monitoring and feedback module is used to integrate the first type fault parameter set of the blood glucose monitoring equipment, the second type fault parameter set of the blood glucose monitoring equipment and the third type fault parameter set of the blood glucose monitoring equipment to generate a blood glucose monitoring equipment fault parameter set, thereby monitoring and feedbacking the fault data of the blood glucose monitoring equipment.

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