CN-122004852-A - Dynamic feedback correction blood glucose real-time monitoring method, system and storage medium

CN122004852ACN 122004852 ACN122004852 ACN 122004852ACN-122004852-A

Abstract

The application relates to the technical field of blood glucose monitoring and discloses a dynamic feedback correction blood glucose real-time monitoring method, a dynamic feedback correction blood glucose real-time monitoring system and a storage medium, wherein the dynamic feedback correction blood glucose real-time monitoring method comprises the steps of obtaining interstitial fluid data and venous blood reference values, and determining sensor drift deviation based on real-time differences; correcting interstitial fluid data based on drift deviation, calculating blood sugar fluctuation rate, adjusting feedback interval to a high-frequency mode if the fluctuation rate exceeds a preset threshold value, executing calibration correction in the high-frequency mode, correcting interstitial fluid data by fusing venous blood reference values, generating corrected blood sugar monitoring results, evaluating resource consumption level based on the correction results, adjusting the feedback interval to a target interval value in a stable mode if optimization requirements exist, determining the feedback interval as a final feedback rhythm, updating monitoring parameters based on the final feedback rhythm, and enabling the system to adapt to individual differences and dynamic changes. The application improves the accuracy of blood glucose monitoring, the running efficiency of the system and the individuation self-adaptive capacity.

Inventors

ZHANG QI
WANG YANFEN

Assignees

深圳市昕力医疗设备开发有限公司

Dates

Publication Date: 20260512
Application Date: 20260326

Claims (10)

1. A method for dynamically feedback-corrected blood glucose real-time monitoring, the method comprising: Step S1, obtaining interstitial fluid data and venous blood reference values, and determining drift deviation of a current sensor based on real-time difference of the interstitial fluid data and the venous blood reference values; s2, correcting the interstitial fluid data based on drift deviation of the sensor, and calculating the blood sugar fluctuation rate based on the corrected interstitial fluid data; step S3, comparing the blood glucose fluctuation rate with a preset fluctuation threshold, and if the blood glucose fluctuation rate exceeds the preset fluctuation threshold, adjusting a feedback interval of blood glucose monitoring to a high-frequency mode; Step S4, in the high-frequency mode, executing calibration correction based on the adjusted feedback interval, correcting the interstitial fluid data by fusing the venous blood reference value, and generating a corrected blood glucose monitoring result; Step S5, evaluating the resource consumption level of the blood glucose monitoring system based on the corrected blood glucose monitoring result, if the resource consumption optimization requirement exists, adjusting the feedback interval of blood glucose monitoring to a target interval value in a stable mode, and determining the feedback interval as the final feedback rhythm of the current monitoring period; And step S6, updating monitoring parameters of the blood glucose monitoring system based on the final feedback rhythm, so that the blood glucose monitoring system adapts to individual physiological differences and blood glucose dynamic changes.
2. The method for dynamically feedback-corrected blood glucose real-time monitoring according to claim 1, wherein determining the drift deviation of the current sensor in step S1 comprises: Acquiring interstitial fluid data through real-time acquisition equipment, simultaneously acquiring venous blood reference values at the same time point as blood glucose monitoring reference data, comparing the interstitial fluid data at the same time point with the venous blood reference values point by point, calculating a difference value between the interstitial fluid data and the venous blood reference values, determining the drift degree of a current sensor according to a difference value sequence, and generating a quantized drift deviation value of the sensor; And carrying out time sequence analysis on the drift deviation of the sensor, verifying the stability characteristics of the drift deviation of the sensor, and if the stability index of the drift deviation of the sensor meets the preset condition, taking the drift deviation of the sensor as a basic parameter for correcting and calculating the follow-up blood sugar fluctuation rate, recording the change trend of the drift deviation of the sensor along with time, and providing a reference basis for the follow-up blood sugar monitoring and calibrating operation.
3. The method for monitoring blood glucose in real time with dynamic feedback correction according to claim 1, wherein calculating the blood glucose fluctuation rate in step S2 comprises: obtaining interstitial fluid data at continuous time points, constructing an interstitial fluid time sequence data set, applying a differential method to the interstitial fluid time sequence data set, and calculating an original change value of the interstitial fluid data between adjacent time points; correcting the original change value by utilizing drift deviation of the sensor to obtain a corrected change value, determining a quantized value of the blood sugar fluctuation rate based on the corrected change value, performing smooth filtering processing on the quantized value of the blood sugar fluctuation rate, marking the current blood sugar fluctuation state as an abnormal fluctuation state if the fluctuation amplitude of the blood sugar fluctuation rate exceeds a preset range, recording a historical data sequence of the blood sugar fluctuation rate, and providing data support for the dynamic adjustment of a subsequent blood sugar fluctuation rate threshold.
4. The method for dynamically feedback-corrected blood glucose real-time monitoring according to claim 1, wherein the step S3 of adjusting the feedback interval of blood glucose monitoring to the high frequency mode comprises: Acquiring a blood sugar fluctuation rate value at the current moment in real time, comparing the value with the preset fluctuation threshold value, and triggering the blood sugar monitoring system to switch to a high-frequency feedback monitoring mode if the blood sugar fluctuation rate exceeds the preset fluctuation threshold value; Calculating feedback interval duration adapting to the current blood sugar fluctuation state through a self-adaptive adjustment algorithm, shortening the acquisition period of interstitial fluid data and the processing period of blood sugar data according to the calculated feedback interval duration, continuously monitoring the change trend of the blood sugar fluctuation rate, dynamically adjusting the feedback interval in real time, and recording the current feedback interval adjustment parameter and taking the current feedback interval adjustment parameter as a reference basis for the subsequent mode switching when the blood sugar fluctuation rate is restored below the preset fluctuation threshold.
5. The method for dynamically feedback-corrected blood glucose real-time monitoring according to claim 1, wherein generating corrected real-time blood glucose monitoring results in step S4 comprises: According to the adjusted high-frequency mode feedback interval, the latest interstitial fluid data is acquired at regular time, and the latest interstitial fluid data and venous blood reference values are subjected to data fusion processing through a Kalman filter; and generating a blood glucose monitoring result after drift correction according to the data fusion processing result, comparing the corrected blood glucose monitoring result with historical blood glucose monitoring data, verifying the calibration effect, if the calibration effect meets the preset standard, updating the calibration parameters of the blood glucose monitoring sensor, recording the corrected blood glucose monitoring result, and providing data support for subsequent resource consumption evaluation.
6. The method for dynamically feedback-corrected blood glucose real-time monitoring according to claim 1, wherein the step S5 of evaluating the resource consumption level of the blood glucose monitoring system comprises: Acquiring calculation load data generated by a blood glucose monitoring system in the process of generating the corrected blood glucose monitoring result, comparing the calculation load data with a historical load record of the blood glucose monitoring system, determining the current resource consumption level of the blood glucose monitoring system, and judging that the blood glucose monitoring system has resource consumption optimization requirements if the current resource consumption level of the blood glucose monitoring system exceeds a preset load threshold; trend analysis is carried out on the time series data of the resource consumption level, the optimization priority is determined, a resource allocation adjustment scheme of the blood glucose monitoring system is generated according to the optimization priority, the change process of the resource consumption level of the blood glucose monitoring system is recorded, and a reference basis is provided for the optimization decision of the follow-up blood glucose monitoring system.
7. The method according to claim 1, wherein the step S5 of adjusting the feedback interval of blood glucose monitoring to the target interval value in the steady mode and determining the final feedback rhythm of the current monitoring period comprises: If the blood glucose monitoring system is judged to have the resource consumption optimization requirement, triggering the blood glucose monitoring system to switch to a stable monitoring mode, calculating a target feedback interval value in the stable monitoring mode through a self-adaptive adjustment algorithm, prolonging the acquisition period of interstitial fluid data and the processing period of blood glucose data according to the target feedback interval value, and optimizing the adjustment range of the feedback interval through balancing the monitoring precision requirement and the resource utilization efficiency; If the resource consumption level of the blood glucose monitoring system is restored to the preset normal range after the feedback interval is adjusted, determining the current feedback interval as a final feedback rhythm, recording relevant parameters of the final feedback rhythm, and providing a data basis for the dynamic adjustment of the subsequent feedback interval.
8. The method for dynamically feedback-corrected blood glucose real-time monitoring according to claim 1, wherein updating the monitoring parameters of the blood glucose monitoring system in step S6 to adapt the blood glucose monitoring system to the individual physiological differences and the blood glucose dynamic changes comprises: according to the final feedback rhythm, adjusting the operation parameters of the blood glucose monitoring system to enable the blood glucose monitoring system to match the current blood glucose monitoring requirement, collecting and analyzing individual physiological difference data of a user, carrying out customized updating on the operation parameters of the blood glucose monitoring system, and dynamically adjusting the configuration strategy of the operation parameters of the blood glucose monitoring system according to the real-time trend of the dynamic change of blood glucose; And verifying the monitoring stability of the blood glucose monitoring system after the operation parameters are adjusted, determining the optimized effect of the operation parameters after the operation parameters are adjusted according to the verification result, and if the optimized effect meets the preset requirement, storing the current operation parameters of the blood glucose monitoring system as the default configuration of the blood glucose monitoring system, recording the adjustment history of the operation parameters of the blood glucose monitoring system, and providing reference data for the follow-up personalized optimization.
9. A dynamic feedback corrected blood glucose real-time monitoring system for implementing a dynamic feedback corrected blood glucose real-time monitoring method as set forth in any one of claims 1 to 8, the system comprising: The deviation determining unit is used for acquiring interstitial fluid data and venous blood reference values and determining drift deviation of the current sensor based on real-time difference of the interstitial fluid data and the venous blood reference values; A rate calculation unit for correcting the interstitial fluid data based on the drift deviation of the sensor and calculating a blood glucose fluctuation rate based on the corrected interstitial fluid data; The mode triggering unit is used for comparing the blood sugar fluctuation rate with a preset fluctuation threshold value, and if the blood sugar fluctuation rate exceeds the preset fluctuation threshold value, adjusting the feedback interval of blood sugar monitoring to a high-frequency mode; the result generation unit is used for executing calibration and correction based on the adjusted feedback interval in the high-frequency mode, correcting the interstitial fluid data by fusing the venous blood reference value, and generating a corrected blood glucose monitoring result; The resource adjusting unit is used for evaluating the resource consumption level of the blood glucose monitoring system based on the corrected blood glucose monitoring result, adjusting the feedback interval of blood glucose monitoring to a target interval value in a stable mode if resource consumption optimization requirements exist, and determining the feedback interval as the final feedback rhythm of the current monitoring period; And the parameter adapting unit is used for updating the monitoring parameters of the blood glucose monitoring system based on the final feedback rhythm so that the blood glucose monitoring system adapts to individual physiological differences and blood glucose dynamic changes.
10. A computer readable storage medium having instructions stored thereon, wherein the instructions when executed by a processor implement a method for dynamically feedback corrected glucose real-time monitoring according to any of claims 1-8.

Description

Dynamic feedback correction blood glucose real-time monitoring method, system and storage medium Technical Field The application relates to the technical field of blood glucose monitoring, in particular to a dynamic feedback correction blood glucose real-time monitoring method, a dynamic feedback correction blood glucose real-time monitoring system and a storage medium. Background The continuous blood glucose monitoring technology is used as an important means for diabetes management, and the glucose concentration in interstitial fluid is monitored in real time through the implanted sensor, so that continuous blood glucose change trend information can be provided for patients, hyperglycemia and hypoglycemia events can be found in time, and insulin dosage adjustment and lifestyle intervention can be guided. In the prior art, in order to improve monitoring accuracy, a sensor is usually calibrated by periodically collecting venous blood or fingertip blood reference values, and the output of blood glucose values is realized through fixed-frequency data collection and processing, so that the basic requirement of clinical monitoring is met to a certain extent. However, the existing methods still face many challenges in practical applications. First, during long-term implantation of the sensor, drift deviation accumulated with time is generated due to factors such as enzyme activity attenuation and local microenvironment change, so that measured values deviate from real blood glucose concentration gradually, and the traditional periodic calibration method is difficult to capture and correct the drift of dynamic change in real time. Secondly, there are obvious individual physiological differences among different patients, for example, delay time between interstitial fluid glucose and blood glucose is different, and blood glucose fluctuation characteristics of the same patient in different physiological states are different, so that the monitoring mode of the fixed parameters is difficult to adapt to the complex and changeable individuation requirements. In addition, although the high-frequency data acquisition and processing can improve the monitoring precision, the system power consumption can be obviously increased, the service life of the sensor is shortened, and the dynamic balance between the monitoring precision and the resource consumption cannot be realized by a simple threshold triggering or fixed frequency mode. Therefore, how to accurately extract the blood glucose fluctuation characteristics on the basis of identifying and correcting the sensor drift deviation in real time, adaptively adjust the monitoring frequency according to the fluctuation risk and the resource consumption state, and realize the personalized optimization of parameters by continuously learning the individual physiological characteristics at the same time becomes a technical problem to be solved in the continuous blood glucose monitoring field. Disclosure of Invention In order to solve the technical problems, the application provides a dynamic feedback corrected blood glucose real-time monitoring method, a dynamic feedback corrected blood glucose real-time monitoring system and a dynamic feedback corrected blood glucose storage medium, which are used for solving the problems that sensor drift correction is inaccurate, blood glucose fluctuation rate capture lag and monitoring accuracy and resource consumption cannot be dynamically balanced in the existing continuous blood glucose monitoring technology, and realizing self-adaptive monitoring frequency adjustment and individual optimization of system parameters based on double feedback of physiological states and resource consumption. In a first aspect, the present application provides a method for monitoring blood glucose in real time with dynamic feedback correction, the method comprising: Step S1, obtaining interstitial fluid data and venous blood reference values, and determining drift deviation of a current sensor based on real-time difference of the interstitial fluid data and the venous blood reference values; s2, correcting the interstitial fluid data based on drift deviation of the sensor, and calculating the blood sugar fluctuation rate based on the corrected interstitial fluid data; step S3, comparing the blood glucose fluctuation rate with a preset fluctuation threshold, and if the blood glucose fluctuation rate exceeds the preset fluctuation threshold, adjusting a feedback interval of blood glucose monitoring to a high-frequency mode; Step S4, in the high-frequency mode, executing calibration correction based on the adjusted feedback interval, correcting the interstitial fluid data by fusing the venous blood reference value, and generating a corrected blood glucose monitoring result; Step S5, evaluating the resource consumption level of the blood glucose monitoring system based on the corrected blood glucose monitoring result, if the resource consumption optimization requir