A non-invasive continuous blood glucose detection method

Abstract

This invention discloses a non-invasive continuous blood glucose monitoring method, belonging to the field of non-invasive detection technology. The method includes attaching a temperature sensing module to the user's neck, with the temperature detection component covering the high-temperature area of ​​the carotid artery surface; the temperature sensing module collects real-time temperature data of the skin surface of the carotid artery; a data processing module analyzes the distribution characteristics of the temperature data, identifies the highest temperature point, and confirms the carotid artery surface temperature detection location based on a preset temperature difference threshold; based on the temperature data from the confirmed carotid artery surface temperature detection location, combined with a preset blood glucose correlation model, the blood glucose concentration is calculated and output. This invention greatly improves the user experience while ensuring detection accuracy. Ultimately, the entire system, from signal acquisition, intelligent positioning, model calculation to interactive prompts, forms a complete, adaptive, and user-friendly detection closed loop, theoretically achieving the goal of non-invasive, continuous, accurate, and comfortable blood glucose monitoring.

Description

Technical Field

[0001] This invention belongs to the field of non-invasive detection technology, and in particular relates to a non-invasive continuous blood glucose detection method. Background Technology

[0002] Blood glucose testing is a crucial step in the prevention, diagnosis, treatment, and daily management of diabetes. An ideal blood glucose testing technology should balance accuracy, convenience, comfort, and affordability. Currently, blood glucose testing technologies on the market are mainly divided into three categories: 1. Invasive blood glucose testing: Represented by traditional finger prick blood glucose meters, this method involves collecting blood samples by pricking the fingertip for analysis. While highly accurate, this method causes patients continuous pain, infection risks, and psychological burden. Furthermore, it cannot achieve continuous monitoring and struggles to capture instantaneous fluctuations in blood glucose levels.

[0003] 2. Minimally Invasive Continuous Glucose Monitoring: This method continuously monitors glucose concentration in interstitial fluid using a probe implanted under the skin. However, this method has inherent drawbacks. From a biomedical perspective, the implantation process causes local tissue trauma and inflammatory responses, leading to significant discrepancies between the monitored data and actual blood glucose levels in the initial and later stages of implantation, resulting in decreased accuracy. Furthermore, the implantable sensors are expensive, and the invasive nature of the procedure reduces user acceptance for long-term use.

[0004] 3. Non-invasive blood glucose detection: As a research hotspot, it aims to completely solve the pain points of invasive methods. Its main technical approaches include optical methods and body temperature detection methods based on the principle of metabolic heat integration. (1) Optical methods: such as infrared spectroscopy and Raman spectroscopy, are easily affected by factors such as skin condition, ambient light, and sweat. The equipment is usually large and expensive, and the accuracy of detection is difficult to guarantee in dynamic environments.

[0005] (2) Metabolic thermometry: This method relies on the mechanism by which changes in blood glucose levels affect the body's metabolic rate, thereby altering blood flow and skin temperature in specific areas. Existing products mostly collect temperature data from the fingers or under the tongue. However, finger temperature is easily affected by ambient temperature and peripheral circulation, resulting in poor stability. Sublingual temperature measurement is uncomfortable and difficult to achieve continuous monitoring. Currently, regardless of the technical approach used, there is no non-invasive continuous blood glucose monitoring method that can achieve user-friendly and long-term continuous monitoring while ensuring the accuracy required for clinical use.

[0006] Therefore, there is an urgent need to design a non-invasive continuous blood glucose monitoring method to solve the problems mentioned above. Summary of the Invention

[0007] The purpose of this invention is to provide a non-invasive continuous blood glucose monitoring method, which has the advantages of being non-invasive, accurate, continuous and user-friendly, and solves the problems mentioned in the background art.

[0008] To achieve the above objectives, the specific technical solution of the non-invasive continuous blood glucose monitoring method of the present invention is as follows: A non-invasive continuous glucose monitoring method includes the following steps: S1. The temperature sensing module is attached to the user's neck, and the temperature detection component covers the high temperature area on the surface of the carotid artery. S2. The temperature sensing module collects real-time temperature data of the skin surface of the carotid artery. S3. The data processing module analyzes the distribution characteristics of temperature data, identifies the highest temperature point, and confirms the carotid artery surface temperature detection location based on the preset temperature difference threshold. S4. Based on the temperature data of the confirmed carotid artery surface temperature detection location, and combined with the preset blood glucose correlation model, calculate and output the blood glucose concentration.

[0009] Furthermore, in S1, the temperature sensing module includes at least two temperature sensors distributed in the transverse direction along the carotid artery.

[0010] Furthermore, the temperature sensing module is set around the user's neck via a flexible carrier to adapt to different neck shapes.

[0011] Furthermore, in S3, the distribution characteristics of temperature data from each temperature sensor are analyzed through the data processing module to determine the highest temperature point.

[0012] Furthermore, if the temperature difference between the temperature sensor at the highest temperature point and other temperature sensors is greater than or equal to a preset temperature difference threshold, then the location of the highest temperature point is determined as the carotid artery surface temperature detection location.

[0013] Furthermore, if the temperature difference between the temperature sensors is less than a preset temperature difference threshold, a position adjustment prompt message is generated to guide the user to move the temperature sensing module until the temperature difference between the temperature sensor at the highest temperature point and other temperature sensors is greater than or equal to the preset temperature difference threshold.

[0014] Furthermore, in S4, a blood glucose correlation model based on the principle of metabolic heat integration is obtained. The model comprehensively considers the dynamic relationship between carotid artery surface temperature and human metabolic rate and blood flow velocity. The temperature data of the carotid artery surface temperature detection location is input into the blood glucose correlation model, and combined with the user's physiological parameters, the current blood glucose concentration value is calculated.

[0015] Furthermore, the mathematical expression for the blood glucose-related model is: ; in, Blood glucose concentration, This refers to the temperature of the carotid artery surface. For age, For gender, Body Mass Index (BMI) , , , , These are the model parameters obtained through training.

[0016] This invention has the following advantages: Through modular and closed-loop hardware and software co-design, it systematically solves the two core problems of inaccurate sensor positioning and individual difference correction in non-invasive blood glucose testing. While ensuring the accuracy of detection, it greatly improves the user experience. Ultimately, the entire system, from signal acquisition, intelligent positioning, model calculation to interactive prompts, forms a complete, adaptive and user-friendly detection closed loop, theoretically achieving the goal of non-invasive, continuous, accurate and comfortable blood glucose monitoring. Attached Figure Description

[0017] Figure 1 This is a schematic flowchart of the detection method of the present invention; Figure 2 This is a schematic diagram of the detection system of the present invention; Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Those skilled in the art will understand that although some embodiments herein include certain features included in other embodiments but not others, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments can be used in any combination.

[0020] The following is a reference to the appendix. Figure 1 and attached Figure 2 This invention describes a non-invasive continuous blood glucose monitoring method.

[0021] This non-invasive blood glucose testing system mainly involves the following modules: Temperature sensing module: This module is the hardware front end of the system, responsible for contacting the user's body and collecting raw physiological signals. The temperature sensing module consists of a flexible carrier and temperature detection components integrated on it.

[0022] The flexible carrier is designed to comfortably and securely wrap around the user's neck, ensuring that the temperature sensing components conform to the neck's curve and cover the target area. The flexible carrier can be made of medical nonwoven fabric with an adhesive backing layer for adhesion to the user's skin.

[0023] The temperature detection component consists of at least two temperature sensors arranged laterally along the carotid artery to collect temperature data of the skin on the carotid artery surface in real time and at multiple points, providing basic signals for subsequent analysis.

[0024] Specifically, the temperature sensor is a thermistor sensor or an infrared temperature sensor, with a detection distance of 2-5mm and a resolution of 0.02℃, to ensure the accuracy and real-time performance of temperature acquisition.

[0025] Data Processing Module: This module is the logical core of the system, responsible for processing raw temperature data and solving the problem of accurate sensor positioning. The data processing module receives real-time data from the temperature detection component and analyzes the distribution characteristics of these temperature values ​​to identify the highest temperature point. Subsequently, the data processing module makes logical judgments based on preset temperature difference thresholds to confirm the optimal temperature detection point representing the carotid artery location. If the current data does not meet the threshold conditions, this module will trigger the prompt module to generate an adjustment prompt.

[0026] Blood glucose calculation module: This module is the core of the system model and is responsible for converting accurate temperature information into blood glucose values. It is a preset blood glucose correlation model, which is built based on the principle of metabolic heat integration and is corrected by individual physiological parameters such as age, gender, and body mass index (BMI). This module receives temperature data from the optimal location confirmed by the data processing module, inputs it into the model along with the user's physiological parameters, performs calculations through the calculation unit, and finally outputs the estimated blood glucose concentration value.

[0027] Interaction and Prompt Module: This module serves as the interface between the system and the user, guiding operation and presenting results. Based on instructions from the data processing module, it provides position adjustment prompts to the user when the sensor position is unsatisfactory, guiding the user to slightly move the device until accurate positioning is achieved. After the test is complete, this module outputs the final blood glucose concentration result, typically displayed to the user via a screen or connected smart device.

[0028] This non-invasive continuous glucose monitoring method includes the following steps: S1. The temperature sensing module is attached to the user's neck, and the temperature detection component covers the high temperature area on the surface of the carotid artery. Specifically, the temperature sensing module includes at least two temperature sensors, which are distributed in the transverse direction along the carotid artery.

[0029] The temperature sensing module is set around the user's neck via a flexible carrier to adapt to different neck shapes.

[0030] S2. The temperature sensing module collects real-time temperature data of the skin surface of the carotid artery. S3. The data processing module analyzes the distribution characteristics of temperature data, identifies the highest temperature point, and confirms the carotid artery surface temperature detection location based on the preset temperature difference threshold. Specifically, the data processing module analyzes the distribution characteristics of temperature data from each temperature sensor to determine the highest temperature point.

[0031] If the temperature difference between the temperature sensor at the highest temperature point and other temperature sensors is greater than or equal to a preset temperature difference threshold, then the location of the highest temperature point is determined as the carotid artery surface temperature detection location.

[0032] If the temperature difference between the temperature sensors is less than the preset temperature difference threshold, a position adjustment prompt message is generated to guide the user to move the temperature sensing module until the temperature difference between the temperature sensor at the highest temperature point and other temperature sensors is greater than or equal to the preset temperature difference threshold.

[0033] When there are two temperature sensors, the distribution range of the two temperature sensors needs to cover the high temperature area on the surface of the carotid artery. The lateral width of the high temperature area in the common carotid artery segment is about 8-10mm. Therefore, the interval between the two temperature sensors is set to 3-5mm, and the total coverage width is 9-10mm.

[0034] If the temperature T1 of one temperature sensor is significantly higher than the temperature T2 of another temperature sensor, and the temperature difference is greater than or equal to a preset temperature difference threshold, then the higher temperature point T1 is the carotid artery surface temperature detection location. If the temperatures of the two temperature sensors are close, and the temperature difference is less than the preset temperature difference threshold, the instrument will prompt the user to slightly move the temperature detection component left or right through the display unit until the temperature difference is greater than or equal to the preset temperature difference threshold. Then the temperature T1 of the temperature sensor is the detection location.

[0035] When there are three temperature sensors, the distribution range of the three temperature sensors should cover the high temperature area on the surface of the carotid artery. The lateral width of the high temperature area in the common carotid artery segment should be about 8-10mm, and the interval between the three temperature sensors should be set to 3-5mm, with a total coverage width of 12-15mm, to ensure complete coverage of the high temperature area on the surface of the carotid artery.

[0036] If the temperature T1 of one of the temperature sensors is significantly higher than the temperatures T2 and T3 of the other two temperature sensors, and the temperature difference is greater than or equal to the preset temperature difference threshold, then the position of temperature sensor T1 is the carotid artery surface temperature detection position. If the temperatures of the three temperature sensors are close, and the temperature difference is less than the preset temperature difference threshold, the instrument will prompt the user to slightly move the temperature detection component left or right through the display unit until the temperature difference is greater than or equal to the preset temperature difference threshold, and the position of temperature sensor T1 will be the detection position.

[0037] According to medical data, there are natural temperature gradients in different parts of the human body. Because the neck is close to large blood vessels and has a rich blood flow, its surface temperature is usually slightly higher than that of exposed areas such as the forehead. The normal temperature difference is about 0.3-0.5℃.

[0038] The preset temperature difference threshold is between 0.3℃ and 0.5℃. Preferably, the preset temperature difference threshold is 0.3℃. In other embodiments of the present invention, it may be other values ​​within the above range.

[0039] S4. Based on the temperature data of the confirmed carotid artery surface temperature detection location, and combined with the preset blood glucose correlation model, calculate and output the blood glucose concentration.

[0040] Specifically, a blood glucose correlation model based on the principle of metabolic heat integration is obtained. The model comprehensively considers the dynamic relationship between carotid artery surface temperature and human metabolic rate and blood flow velocity. The temperature data of the carotid artery surface temperature detection location is input into the blood glucose correlation model, and combined with the user's physiological parameters, the current blood glucose concentration value is calculated.

[0041] The mathematical expression for the blood glucose correlation model is: ; in, Blood glucose concentration, This refers to the temperature of the carotid artery surface. For age, For gender, Body Mass Index (BMI) , , , , These are the model parameters obtained through training.

[0042] Indicates the surface temperature of the carotid artery ( ) on blood glucose concentration ( The direct impact of weights on the weights. With a coefficient of 0.3, in this embodiment, the estimated blood glucose concentration will increase by 0.3 mmol / L for every 1°C increase in temperature.

[0043] Indicates age ( The correction weights of ) The coefficient is 0.02. In this embodiment, the estimated blood glucose concentration increases by 0.02 mmol / L for every year of age increase.

[0044] Indicates gender ( The correction weights of ) The coefficient is 0.5.

[0045] With males assigned a value of 1 and females a value of 0, in this embodiment, the estimated blood glucose concentration for males is 0.5 mmol / L higher than that for females.

[0046] This indicates the adjusted weight of body mass index (BMI). The coefficient is 0.05. In this embodiment, for every 1 kg / m² increase in BMI... 2 The estimated increase in blood glucose concentration was 0.05 mmol / L.

[0047] It is the intercept term of the model. The coefficient is 4.5, when all other variables ( , , , When both are 0, the blood glucose concentration ( The base value of ).

[0048] The advantages of this non-invasive blood glucose monitoring system and method lie in its modular, closed-loop hardware and software collaborative design, which systematically solves the two core challenges of inaccurate sensor positioning and individual difference correction in non-invasive blood glucose monitoring. While ensuring detection accuracy, it greatly improves the user experience. Ultimately, the entire system, from signal acquisition, intelligent positioning, model calculation to interactive prompts, forms a complete, adaptive, and user-friendly detection closed loop, theoretically achieving the goal of non-invasive, continuous, accurate, and comfortable blood glucose monitoring.

[0049] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art can make other variations or modifications based on the above description. It is neither necessary nor possible to exhaustively describe all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method of non-invasive continuous blood glucose detection, characterized in that, Includes the following steps: S1. The temperature sensing module is attached to the user's neck, and the temperature detection component covers the high-temperature area on the surface of the carotid artery. S2. The temperature sensing module collects real-time temperature data of the skin surface of the carotid artery. S3. The data processing module analyzes the distribution characteristics of temperature data, identifies the highest temperature point, and confirms the carotid artery surface temperature detection location based on the preset temperature difference threshold. S4. Based on the temperature data of the confirmed carotid artery surface temperature detection location, and combined with the preset blood glucose correlation model, calculate and output the blood glucose concentration.

2. The non-invasive continuous blood glucose monitoring method according to claim 1, wherein, In S1, the temperature sensing module includes at least two temperature sensors distributed in the transverse direction along the carotid artery.

3. The non-invasive continuous blood glucose monitoring method of claim 1, wherein, The temperature sensing module is set around the user's neck via a flexible carrier to adapt to different neck shapes.

4. The non-invasive continuous blood glucose monitoring method according to claim 2, wherein, In S3, the data processing module analyzes the distribution characteristics of temperature data from each temperature sensor to determine the highest temperature point.

5. The non-invasive continuous blood glucose monitoring method according to claim 4, wherein, If the temperature difference between the temperature sensor at the highest temperature point and other temperature sensors is greater than or equal to a preset temperature difference threshold, then the location of the highest temperature point is determined as the carotid artery surface temperature detection location.

6. The non-invasive continuous blood glucose monitoring method according to claim 5, wherein, If the temperature difference between the temperature sensors is less than the preset temperature difference threshold, a position adjustment prompt message is generated to guide the user to move the temperature sensing module until the temperature difference between the temperature sensor at the highest temperature point and other temperature sensors is greater than or equal to the preset temperature difference threshold.

7. The non-invasive continuous glucose monitoring method according to claim 1, characterized in that, In S4, a blood glucose correlation model based on the principle of metabolic heat integration is obtained. The model comprehensively considers the dynamic relationship between carotid artery surface temperature and human metabolic rate and blood flow velocity. The temperature data of the carotid artery surface temperature detection location is input into the blood glucose correlation model, and combined with the user's physiological parameters, the current blood glucose concentration value is calculated.

8. The non-invasive continuous glucose monitoring method according to claim 7, characterized in that, The mathematical expression for the blood glucose correlation model is: ; in, Blood glucose concentration, This refers to the temperature of the carotid artery surface. For age, For gender, Body Mass Index (BMI) , , , , These are the model parameters obtained through training.

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