Non-invasive blood glucose measurement method, device, equipment and storage medium

Abstract

Embodiments of the present application disclose a non-invasive blood glucose measurement method, device, equipment and storage medium. The method acquires skin contact data of a user to be detected by a fingerprint sensor, determines a skin contact area according to the skin contact data, acquires skin texture information of the user to be detected from the skin contact data when a contact state meets a preset condition, acquires a spectral measurement value of the user to be detected by an optical detector, then calls corresponding target blood glucose calibration data from a blood glucose calibration database of the user to be detected according to the skin texture information, and determines a blood glucose result of the user to be detected according to the spectral measurement value and the target blood glucose calibration data. By this method, on the one hand, the situation that the detection result is affected due to light leakage caused by poor contact between the user to be detected and the optical detector can be avoided, and on the other hand, errors caused by different contact positions of the user to be detected during each measurement can be avoided.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of intelligent detection technology, and in particular to a non-invasive blood glucose measurement method, apparatus, device, and storage medium. Background Art

[0002] According to statistics from 2015, there are approximately 130 million people with diabetes in my country, making diabetes a major health issue affecting Chinese citizens. Currently, there is no effective cure for diabetes, and controlling blood sugar levels is the only treatment option. Timely blood sugar testing is crucial for controlling diabetes, preventing complications, and improving the quality of life for diabetic patients. Currently, the vast majority of blood sugar tests are performed using invasive blood glucose meters. These tests require blood sampling, which can be traumatic and painful, and poses a risk of infection. Therefore, non-invasive blood glucose measurement has long been a hot topic in cutting-edge research, with optical methods offering the greatest potential for accurate non-invasive blood glucose measurement.

[0003] However, optical methods for noninvasive blood glucose measurement often face significant measurement errors. For one thing, the optical detector's contact with the skin varies with each measurement, leading to significant errors in the results. Furthermore, improper operation, such as insufficient contact between the skin and the optical detector, can cause external ambient light to leak into the detector, resulting in significant errors in the measurement results. Summary of the Invention

[0004] The embodiments of the present application provide a non-invasive blood glucose measurement method, apparatus, device, and storage medium to reduce the error of non-invasive blood glucose measurement.

[0005] In a first aspect, an embodiment of the present application provides a non-invasive blood glucose measurement method, which is applied to a non-invasive blood glucose measurement device, the non-invasive blood glucose measurement device comprising: a fingerprint sensor and an optical detector, the fingerprint sensor being arranged around the optical detector;

[0006] The non-invasive blood glucose measurement method comprises:

[0007] Acquiring skin contact data of the user to be detected through the fingerprint sensor;

[0008] determining a skin contact area based on the skin contact data, and when the skin contact area is greater than a first preset threshold, determining skin texture information of the user to be detected based on the skin contact data, and obtaining a spectral measurement value of the user to be detected through the optical detector;

[0009] Retrieving corresponding target blood glucose calibration data from a blood glucose calibration database of the user to be tested based on the skin texture information, the blood glucose calibration database being constructed based on a blood glucose measurement dataset and blood glucose standard data of the user to be tested, each piece of blood glucose measurement data in the blood glucose measurement dataset including corresponding pre-test texture information and pre-test spectral measurement values, and each piece of blood glucose measurement data generating corresponding blood glucose calibration data;

[0010] The blood glucose result of the user to be tested is determined according to the spectral measurement value and the target blood glucose calibration data.

[0011] Wherein, the fingerprint sensor includes several sensor units.

[0012] Wherein, determining the skin contact area according to the skin contact data includes:

[0013] Acquiring skin contact data of the user to be detected through the sensor unit;

[0014] Counting the number of sensor units that detect that the skin contact data is higher than a second preset threshold;

[0015] The skin contact area is determined according to the number of sensor units that detect that the skin contact data is higher than a second preset threshold.

[0016] The blood glucose calibration database is constructed as follows:

[0017] Acquire a blood glucose measurement data set and blood glucose standard data of the user to be detected, wherein each piece of blood glucose measurement data in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectrum measurement value;

[0018] determining the blood glucose calibration data according to the pre-test spectrum measurement value and the blood glucose standard data, wherein the blood glucose calibration data is used to characterize a mapping relationship between the pre-test spectrum measurement value and the blood glucose standard data;

[0019] The blood glucose calibration data is associated with the corresponding pre-check texture information and saved in the blood glucose calibration database.

[0020] The step of calling corresponding blood glucose calibration data from a blood glucose calibration database of the user to be detected according to the skin texture information includes:

[0021] Comparing the skin texture information with the pre-detection texture information to determine that the user to be detected is a target detection user;

[0022] When the user to be detected is the target detection user, corresponding blood glucose calibration data is retrieved from the blood glucose calibration database of the target detection user according to the skin texture information.

[0023] Wherein, the non-invasive blood glucose measurement method further includes:

[0024] When the skin contact area is lower than a first preset threshold, a reminder message is generated and output, where the reminder message is used to remind the user to be detected to adjust the contact state with the fingerprint sensor.

[0025] The fingerprint sensor is a capacitive fingerprint sensor, an optical fingerprint sensor or an ultrasonic fingerprint sensor.

[0026] In a second aspect, an embodiment of the present application provides a non-invasive blood glucose measurement device, which is applied to a non-invasive blood glucose measurement device. The non-invasive blood glucose measurement device includes a fingerprint sensor and an optical detector, wherein the fingerprint sensor is arranged around the optical detector.

[0027] The non-invasive blood glucose measuring device comprises:

[0028] An information acquisition module, configured to acquire skin contact data of a user to be detected through the fingerprint sensor;

[0029] a spectral measurement module, configured to determine a skin contact area based on the skin contact data, determine skin texture information of the user to be detected based on the skin contact data when the skin contact area is greater than a first preset threshold, and obtain a spectral measurement value of the user to be detected through the optical detector;

[0030] a blood glucose calibration module, configured to retrieve corresponding target blood glucose calibration data from a blood glucose calibration database of the user to be tested based on the skin texture information, wherein the blood glucose calibration database is constructed based on a blood glucose measurement data set and blood glucose standard data of the user to be tested, wherein each blood glucose measurement data item in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectral measurement values, and each blood glucose measurement data item generates corresponding blood glucose calibration data;

[0031] The blood glucose detection module is used to determine the blood glucose result of the user to be detected based on the spectral measurement value and the blood glucose calibration data.

[0032] Wherein, the fingerprint sensor includes several sensor units.

[0033] Wherein, the spectrum measurement module includes:

[0034] a data acquisition unit, configured to acquire skin contact data of a user to be detected through the sensor unit;

[0035] a statistical data unit, configured to count the number of sensor units detecting that the skin contact data is higher than a second preset threshold;

[0036] The area determination unit is configured to determine the skin contact area according to the number of sensor units that detect that the skin contact data is higher than a second preset threshold.

[0037] The blood glucose calibration database is constructed as follows:

[0038] Acquire a blood glucose measurement data set and blood glucose standard data of the user to be detected, wherein each piece of blood glucose measurement data in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectrum measurement value;

[0039] determining the blood glucose calibration data according to the pre-test spectrum measurement value and the blood glucose standard data, wherein the blood glucose calibration data is used to characterize a mapping relationship between the pre-test spectrum measurement value and the blood glucose standard data;

[0040] The blood glucose calibration data is associated with the corresponding pre-check texture information and saved in the blood glucose calibration database.

[0041] Wherein, the blood glucose calibration module includes:

[0042] an information comparison unit, configured to compare the skin texture information with the pre-detection texture information to determine that the user to be detected is a target detection user;

[0043] A data calling unit is configured to call corresponding blood glucose calibration data from a blood glucose calibration database of the target detection user according to the skin texture information when the user to be detected is the target detection user.

[0044] Wherein, the non-invasive blood glucose measurement device further comprises:

[0045] The reminder output module is used to generate and output a reminder message when the skin contact area is lower than a first preset threshold, wherein the reminder message is used to remind the user to be detected to adjust the contact state with the fingerprint sensor.

[0046] The fingerprint sensor is a capacitive fingerprint sensor, an optical fingerprint sensor or an ultrasonic fingerprint sensor.

[0047] In a third aspect, an embodiment of the present application provides an electronic device, including a memory and one or more processors;

[0048] The memory is used to store one or more programs;

[0049] When the one or more programs are executed by the one or more processors, the one or more processors implement the non-invasive blood glucose measurement method as described in the first aspect.

[0050] In a fourth aspect, an embodiment of the present application provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the non-invasive blood glucose measurement method as described in the first aspect.

[0051] In an embodiment of the present application, a fingerprint sensor is used to obtain skin contact data of a user to be detected, and then the skin contact area is determined based on the skin contact data. The contact state between the user to be detected and the fingerprint sensor is then determined based on the skin contact area. When the contact state satisfies a preset condition, the skin texture information of the user to be detected is obtained from the skin contact data, and a spectral measurement value of the user to be detected is obtained through an optical detector. Subsequently, the corresponding target blood glucose calibration data is retrieved from a blood glucose calibration database for the user to be detected based on the skin texture information, and the blood glucose result of the user to be detected is determined based on the spectral measurement value and the target blood glucose calibration data. This method can, on the one hand, determine the contact state between the user to be detected and the fingerprint sensor based on the skin contact area, thereby avoiding situations where poor contact between the user to be detected and the optical detector causes light leakage that affects the detection result. On the other hand, the corresponding target blood glucose calibration data can be retrieved from the blood glucose calibration database to calibrate the spectral measurement value, thereby avoiding errors caused by different contact positions of the user to be detected each time. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a flow chart of a non-invasive blood glucose measurement method provided in an embodiment of the present application;

[0053] Figure 2 This is a schematic structural diagram of the non-invasive blood glucose measurement device provided by the present invention;

[0054] Figure 3 This is a schematic diagram of the process of calling blood glucose calibration data provided by the present invention;

[0055] Figure 4 This is a schematic structural diagram of another non-invasive blood glucose measurement device provided by the present invention;

[0056] Figure 5 This is a schematic structural diagram of the non-invasive blood glucose measurement device provided by the present invention;

[0057] Figure 6 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solutions and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. It should also be noted that, for ease of description, only parts related to the present application, not all of the contents, are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0059] It should be noted that this application specification does not enumerate all optional implementation methods. After reading this application specification, those skilled in the art should be able to understand that as long as the technical features do not conflict with each other, any combination of technical features can constitute an optional implementation method.

[0060] There are 130 million diabetic patients in my country who need to test their blood sugar levels on a daily basis. The traditional fingertip blood collection method is very painful, resulting in low patient compliance. Therefore, non-invasive blood sugar measurement technology has always been a hot topic in cutting-edge technology research. Among them, optical methods (Raman spectroscopy, infrared absorption spectroscopy, optical OCT, fluorescence spectroscopy, photoacoustic spectroscopy, etc.) are one of the most promising technical paths to achieve accurate non-invasive blood sugar measurement. However, in the process of non-invasive blood sugar measurement using optical methods, it is often faced with the problem that the contact position between the optical detector and the skin changes every time the user uses the instrument to measure, resulting in significant errors in the measurement results. At the same time, improper user operation often occurs, resulting in insufficient close contact between the skin and the optical detector, so that external ambient light leaks into the optical detector, causing large errors in the measurement results.

[0061] In view of the problems existing in the prior art mentioned above, refer to Figure 1 , Figure 1 This is a flow chart of the non-invasive blood glucose measurement method provided by the present invention, which is applied to a non-invasive blood glucose measurement device. Figure 2 , Figure 2 This is a structural diagram of the non-invasive blood glucose measurement device provided by the present invention. The non-invasive blood glucose measurement device includes: a fingerprint sensor and an optical detector. The fingerprint sensor is arranged around the optical detector. Figure 2 For non-invasive blood glucose measurement devices, please refer to Figure 1 The non-invasive blood glucose measurement method includes but is not limited to steps 110 to 140:

[0062] Step 110: Acquire skin contact data of the user to be detected through the fingerprint sensor.

[0063] In step 110, the fingerprint sensor in the non-invasive blood glucose measurement device needs to acquire skin contact data of the user to be detected. This skin contact data is used to judge the contact between the contact part of the user to be detected and the fingerprint sensor. The specific form of the skin contact data is determined by the type of fingerprint sensor. For example, when the fingerprint sensor is a capacitive fingerprint sensor, the skin contact data is capacitance data; when the fingerprint sensor is an optical fingerprint sensor, the skin contact data is a pulse signal or a video image signal; when the fingerprint sensor is an ultrasonic fingerprint sensor, the skin contact data is an ultrasonic signal. Those skilled in the art can select the corresponding fingerprint sensor to acquire skin contact data according to actual conditions.

[0064] Step 120: Determine a skin contact area based on the skin contact data. When the skin contact area is higher than a first preset threshold, determine skin texture information of the user to be detected based on the skin contact data, and obtain a spectral measurement value of the user to be detected through the optical detector.

[0065] In step 120, to reduce the risk of light leakage during the measurement process, the skin contact area is determined based on the skin contact data. The contact between the user to be detected and the non-invasive blood glucose measurement device is then compared with a preset area to determine the contact between the user to be detected and the non-invasive blood glucose measurement device. If the contact meets the preset conditions, the user's skin texture information is further determined based on the acquired skin contact data, and the optical detector obtains the user's spectral measurement value. For example, taking the fingerprint sensor as an array capacitive fingerprint sensor, the array capacitive fingerprint sensor includes multiple sensor units. After the user to be detected performs a measurement operation, i.e., presses the non-invasive blood glucose measurement device, each sensor unit can obtain a capacitance value. When the capacitance value exceeds a contact change threshold, it is determined that the location corresponding to the sensor unit is in close contact with the user to be detected. The contact change threshold can be a preset threshold or can be set and adjusted based on the actual skin data of the user to be detected. The location and number of sensors with capacitance values ​​greater than the contact change threshold are then counted to obtain the corresponding skin contact area. When the skin contact area exceeds a first preset threshold, it is determined that the user's skin is in close contact with the non-invasive blood glucose measurement device during this blood glucose measurement operation.

[0066] It should be noted that skin contact data is collected based on the fingerprint sensor positioned around the optical detector. Therefore, the skin contact area determined based on this skin contact data is the area surrounding the optical detector. Furthermore, if the skin contact area is determined to be above a first preset threshold, it indicates that the user's skin is in close contact with the annular area surrounding the optical detector. Furthermore, since the optical detector is positioned at the center of this annular area, and the user's skin is in close contact with the optical detector, it can be assumed that the measurement is currently operating normally, with no risk of light leakage.

[0067] After confirming close contact between the user's skin and the non-invasive blood glucose measurement device, the device then determines the user's skin texture information based on the skin contact data, and acquires a spectral measurement of the user's skin using an optical detector. The skin texture information represents skin texture characteristics and can be an image of a fingerprint texture or other characteristic information, without specific limitation. The spectral measurement characterizes the reflection and absorption of light irradiated by the user's skin. This light is emitted by the laser excitation light source on the optical detector. By detecting the reflection and absorption of this light on the skin, the blood glucose level can be calculated.

[0068] Step 130: Call corresponding target blood glucose calibration data from the blood glucose calibration database of the user to be tested based on the skin texture information. The blood glucose calibration database is constructed based on the blood glucose measurement data set and blood glucose standard data of the user to be tested. Each blood glucose measurement data in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectral measurement values. Each blood glucose measurement data generates corresponding blood glucose calibration data.

[0069] In step 130, because the blood glucose measurement result is affected by the position where the optical detector contacts the skin, in order to avoid errors caused by the measurement position, it is necessary to first determine the relative position of the optical detector in contact with the skin based on the skin texture information, and then obtain the target blood glucose calibration data corresponding to this relative position to facilitate calibration of the measured spectral measurement value. The blood glucose calibration database is constructed based on the blood glucose measurement dataset and blood glucose standard data of the user to be tested. Each blood glucose measurement data in the blood glucose measurement dataset contains corresponding pre-test texture information and pre-test spectral measurement value. The corresponding blood glucose calibration data is then generated by comparing the pre-test spectral measurement value with the blood glucose standard data. In other words, each pre-test texture information corresponds to blood glucose calibration data.

[0070] Both the blood glucose measurement dataset and the standard blood glucose data are obtained during the pre-test of the user to be tested. The blood glucose measurement dataset is the data measured after the user to be tested has made multiple slight adjustments to the measurement position on the non-invasive blood glucose measurement device. This data includes the measurement position corresponding to each adjustment (i.e., pre-test texture information) and the spectral measurement value measured by the optical detector corresponding to the measurement position (i.e., pre-test spectral measurement value). The standard blood glucose data is the precise blood glucose value of the user to be tested during the pre-test. This precise blood glucose value can be obtained through invasive blood glucose measurement or other methods, and is not limited here.

[0071] For example, referring to Figure 3 , Figure 3 This is a schematic diagram of the process for retrieving blood glucose calibration data provided by the present invention. Skin texture information extracted from the skin contact data is compared with pre-test texture information in the blood glucose calibration database of the user to be tested. If pre-test texture information is determined to match the skin texture information, the target blood glucose calibration data corresponding to the pre-test texture information is retrieved.

[0072] It should be noted that the skin texture information determined from the skin contact data can be compared with the feature information contained in the blood glucose calibration database based on the feature information contained therein, thereby determining the relative position of the user's skin in contact with the fingerprint sensor. Because the fingerprint sensor is positioned around the optical sensor, once the relative position of the user's skin in contact with the fingerprint sensor is determined, the relative position of the user's skin in contact with the optical sensor is also determined.

[0073] Step 140: Determine the blood glucose result of the user to be tested based on the spectral measurement value and the target blood glucose calibration data.

[0074] In step 140, the blood glucose result of the user to be tested needs to be determined based on the spectral measurement value and the target blood glucose calibration data. The non-invasive blood glucose device emits light of a specific wavelength through the laser excitation light source of the optical detector. This light beam will be irradiated on the user's skin and then penetrate the skin into the subcutaneous tissue. When the light beam penetrates the skin and irradiates the subcutaneous tissue, a portion of the light will be absorbed by the glucose molecules in the skin and subcutaneous tissue. This is because glucose molecules have specific absorption characteristics at specific infrared or near-infrared wavelengths. After being absorbed by the glucose molecules, the intensity of the light will change. Part of the light will be reflected back, and part of the light will be transmitted. At this time, the intensity of the reflected or transmitted light is measured by the optical detector to obtain information about the absorption of light by the glucose molecules (i.e., the spectral measurement value). Next, the measured spectral measurement value and the matched target blood glucose calibration data are input into a pre-programmed algorithm. This algorithm is based on the principles of spectroscopy and biostatistics and can calculate the blood glucose level based on the absorption and reflection information of the light.

[0075] This embodiment uses a fingerprint sensor to obtain skin contact data from the user to be detected, then determines the skin contact area based on this skin contact data. The contact state between the user to be detected and the fingerprint sensor is then determined based on the skin contact area. When the contact state meets preset conditions, the user's skin texture information is obtained from the skin contact data, and a spectral measurement value of the user to be detected is obtained through an optical detector. Subsequently, the corresponding target blood glucose calibration data is retrieved from a blood glucose calibration database for the user to be detected based on the skin texture information. The blood glucose result of the user to be detected is then determined based on the spectral measurement value and the target blood glucose calibration data. This method not only determines the contact state between the user to be detected and the fingerprint sensor based on the skin contact area, thereby preventing light leakage caused by poor contact between the user to be detected and the optical detector, which could affect the detection results. It also calibrates the spectral measurement value by retrieval of the corresponding target blood glucose calibration data from the blood glucose calibration database, thus avoiding errors caused by different contact positions of the user to be detected each time they are measured.

[0076] As a further optional embodiment, the fingerprint sensor includes several sensor units.

[0077] In this embodiment, the fingerprint sensor adopts an array sensor, which is a device composed of multiple sensor units. These units are arranged in a specific layout (such as linear, planar or three-dimensional) and work together to detect specific physical or chemical phenomena. Figure 4 , Figure 4This is a schematic diagram of the structure of another non-invasive blood glucose measurement device provided by the present invention. The fingerprint sensor may include sensor units 1, 2, 3, and 4. In this embodiment, by surrounding the optical detector with the sensor units, the relative position of the user's skin and the non-invasive blood glucose measurement device can be acquired. The coordinated operation of multiple sensor elements improves data quality and accuracy, providing a richer basis for judgment.

[0078] As a further optional embodiment, determining the skin contact area according to the skin contact data includes:

[0079] Acquiring skin contact data of the user to be detected through the sensor unit;

[0080] Counting the number of sensor units that detect that the skin contact data is higher than a second preset threshold;

[0081] The skin contact area is determined according to the number of sensor units that detect that the skin contact data is higher than a second preset threshold.

[0082] In this embodiment, in order to obtain the skin contact area more accurately, it is necessary to detect the skin contact data through the array sensor to further determine the skin contact area. Specifically, each sensor unit in the array sensor can measure the skin contact data and compare the skin contact data with the second preset threshold. The second preset threshold is the contact change threshold. When the skin contact data is greater than the contact change threshold, it is determined that the position corresponding to the sensor unit is in close contact with the user to be detected, and the specific form and specific value of the second preset threshold are determined according to the type of sensor. For example, when the array sensor is a capacitive array sensor, the skin contact data measured by the sensor unit is a capacitance value, and the second preset threshold should also be a capacitance value. Then, the number of sensor units whose skin contact data is higher than the second preset threshold is determined, and the skin contact area is determined based on the number of sensor units whose skin contact data is higher than the second preset threshold.

[0083] For example, refer to Figure 4 , Figure 4This is a structural diagram of another non-invasive blood glucose measurement device provided by the present invention. The fingerprint sensor may include sensor unit 1, sensor unit 2, sensor unit 3, and sensor unit 4. After the user to be detected performs the measurement operation, that is, presses the non-invasive blood glucose measurement device, if the fingerprint sensor is a capacitive fingerprint sensor, each sensor unit can obtain a capacitance value. When the capacitance value is greater than the contact change threshold value, it is determined that the position corresponding to the sensor unit is in close contact with the user to be detected. Then, the position and number of sensors whose capacitance values ​​are greater than the contact change threshold value are counted to obtain the corresponding skin contact area. When the skin contact area is higher than the first preset threshold value, it is determined that the skin of the user to be detected is in close contact with the non-invasive blood glucose measurement device during this blood glucose measurement operation. For example, taking the capacitance values ​​of sensor unit 1, sensor unit 2, and sensor unit 3 as greater than the contact change threshold value and the first preset threshold value as 50% (the ratio of the contact area to the total area), the areas of close contact are the sensor unit 1 area, the sensor unit 2 area, and the sensor unit 3 area. Therefore, the skin contact area is the sum of the areas of the sensor unit 1 area, the sensor unit 2 area, and the sensor unit 3 area divided by the total area, which is 75%. 75% is greater than the first preset threshold value of 50%. Therefore, it is determined that in this blood glucose measurement operation, the skin of the user to be tested is in close contact with the non-invasive blood glucose measurement device.

[0084] As a further optional embodiment, the blood glucose calibration database is constructed in the following manner:

[0085] Acquire a blood glucose measurement data set and blood glucose standard data of the user to be detected, wherein each piece of blood glucose measurement data in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectrum measurement value;

[0086] determining the blood glucose calibration data according to the pre-test spectrum measurement value and the blood glucose standard data, wherein the blood glucose calibration data is used to characterize a mapping relationship between the pre-test spectrum measurement value and the blood glucose standard data;

[0087] The blood glucose calibration data is associated with the corresponding pre-check texture information and saved in the blood glucose calibration database.

[0088] In this embodiment, a blood glucose calibration database needs to be constructed so that corresponding blood glucose calibration data can be retrieved during the blood glucose measurement process. To construct the blood glucose calibration database, a blood glucose measurement dataset and blood glucose standard data of the user to be tested are obtained. The blood glucose measurement dataset is the data obtained after the user to be tested has slightly adjusted the measurement position on the non-invasive blood glucose measurement device multiple times. This data includes the adjusted measurement position (i.e., pre-test texture information) and the spectral measurement value measured by the optical detector (i.e., pre-test spectral measurement value). The blood glucose standard data is the precise blood glucose value of the user to be tested during the pre-test process. This precise blood glucose value can be obtained through invasive blood glucose measurement or other methods, which are not limited here. Next, the blood glucose calibration data is determined based on the pre-test spectral measurement value and the blood glucose standard data. This blood glucose calibration data is used to represent the mapping relationship between the pre-test spectral measurement value and the blood glucose standard data, that is, the blood glucose standard data can be obtained by using the pre-test spectral measurement value and the corresponding blood glucose calibration data. Subsequently, the blood glucose calibration data is associated with the corresponding pre-test texture information and stored in the blood glucose calibration database. The blood glucose calibration database can be a local database within the non-invasive blood glucose measurement device or a cloud database, which is not specifically limited here.

[0089] As a further optional embodiment, calling corresponding blood glucose calibration data from a blood glucose calibration database of the user to be detected according to the skin texture information includes:

[0090] Comparing the skin texture information with the pre-detection texture information to determine that the user to be detected is a target detection user;

[0091] When the user to be detected is the target detection user, corresponding blood glucose calibration data is retrieved from the blood glucose calibration database of the target detection user according to the skin texture information.

[0092] In this embodiment, blood glucose testing can only be performed if skin texture information matching is satisfied. Specifically, the skin texture information needs to be compared with the pre-test texture information to determine that the user to be tested is the target test user, and then the corresponding blood glucose calibration data is called from the target test user's blood glucose calibration database. For the comparison of skin texture information with pre-test texture information, feature points can be extracted from the skin texture information. These feature points are also called "detail features" and include the local structure of the fingerprint, such as end points, bifurcation points (called minutiae), etc. The position and relative relationship of these features constitute a unique pattern of a fingerprint. Then, the extracted fingerprint features are compared with the stored pre-test texture information fingerprint features. This is usually achieved by calculating the similarity between the two fingerprint features. If the similarity exceeds a preset threshold, the two fingerprints are considered to match. Exemplarily, this can be determined by calculating the distance and direction difference between each feature point. If the distance and direction difference between the two feature points are both less than a certain threshold, they are considered to match.

[0093] As a further optional embodiment, the non-invasive blood glucose measurement method further includes:

[0094] When the skin contact area is lower than a first preset threshold, a reminder message is generated and output, where the reminder message is used to remind the user to be detected to adjust the contact state with the fingerprint sensor.

[0095] In this embodiment, when the skin contact area is below a first preset threshold, it indicates that the user's contact with the non-invasive blood glucose meter is not tight during measurement, resulting in a high risk of light leakage, which could affect measurement accuracy. Therefore, when the skin contact area is below the first preset threshold, a corresponding reminder message is generated and output to remind the user to adjust the contact state with the fingerprint sensor. The reminder message can be an audio message, such as a buzzer, speaker, or other output device. For audio devices, a preset reminder voice message can also be output. This voice message can be in Chinese or English, and the content of the reminder message can be customized by the user based on actual needs. The reminder message can also be a visual message displayed on a display device. If the non-invasive blood glucose meter is equipped with a display, touchscreen tablet, or is connected to a smart terminal, a corresponding text reminder message can be generated on the display device, such as displaying the text "Poor contact, please try again" on the screen. Alternatively, the first reminder color can be changed to a second reminder color, such as from green to red, at a preset location on the screen.

[0096] As another optional embodiment, the non-invasive blood glucose measurement method further includes:

[0097] When the skin contact area is lower than a first preset threshold, obtaining ambient light intensity data through an optical sensor;

[0098] Acquire skin texture information of the user to be detected through the fingerprint sensor, and acquire spectral measurement values ​​of the user to be detected through the optical detector;

[0099] Retrieving corresponding blood glucose calibration data from a blood glucose calibration database of the user to be tested according to the skin texture information;

[0100] The blood glucose result of the user to be tested is determined according to the ambient light intensity data, the spectrum measurement value and the blood glucose calibration data.

[0101] In this embodiment, when the skin contact area is lower than the first preset threshold, it means that the contact between the user to be tested and the non-invasive blood glucose measurement device is not close during the measurement, and there is a high risk of light leakage, which affects the accuracy of the measurement. Therefore, when the skin contact area is lower than the first preset threshold, the ambient light intensity data is obtained by the optical sensor, and the ambient light intensity data is used to characterize the light intensity in the measurement environment. Unlike the above embodiment, this embodiment also requires the measured spectral measurement value, ambient light intensity data, and the matched target blood glucose calibration data to be input into a pre-programmed algorithm to obtain the final calibrated blood glucose result.

[0102] As a further optional embodiment, the fingerprint sensor is a capacitive fingerprint sensor, an optical fingerprint sensor, or an ultrasonic fingerprint sensor.

[0103] In this embodiment, the fingerprint sensor may be a capacitive fingerprint sensor, an optical fingerprint sensor, or an ultrasonic fingerprint sensor.

[0104] Capacitive fingerprint sensors use the body's own electrical conductivity to create a fingerprint image. When your finger touches the surface of the capacitive sensor, the capacitance changes between the ridges and valleys of the fingerprint as the ridges touch the sensor and the valleys do not. These changes are read by the sensor and converted into a digitized fingerprint image.

[0105] Optical fingerprint sensors use optical imaging technology to capture fingerprint images. When a finger is placed on the optical sensor, it emits light and captures its reflection off the fingerprint. The ridges and valleys of a fingerprint reflect light differently, and these differences are captured by the sensor and converted into a fingerprint image.

[0106] Ultrasonic fingerprint sensors use sound waves to map the fingerprint's details. The sensor emits ultrasonic waves, which reflect differently from the ridges and valleys of the fingerprint. These reflected sound waves are read by the sensor and converted into a detailed image of the fingerprint. The advantage of this sensor is that it can read fingerprints through smudges and dirt.

[0107] Reference Figure 5 , Figure 5 This is a structural schematic diagram of the non-invasive blood glucose measuring device provided by the present invention. The non-invasive blood glucose measuring device is applied to a non-invasive blood glucose measuring device. The non-invasive blood glucose measuring device includes a fingerprint sensor and an optical detector. The fingerprint sensor is arranged around the optical detector. The non-invasive blood glucose measuring device provided by the present invention is described below. The non-invasive blood glucose measuring device described below and the non-invasive blood glucose measuring method described above can be referenced to each other.

[0108] The non-invasive blood glucose measurement device comprises:

[0109] An information acquisition module 510 is configured to acquire skin contact data of a user to be detected through the fingerprint sensor;

[0110] a spectral measurement module 520 for determining a skin contact area based on the skin contact data, determining skin texture information of the user to be detected based on the skin contact data when the skin contact area is greater than a first preset threshold, and obtaining a spectral measurement value of the user to be detected through the optical detector;

[0111] a blood glucose calibration module 530 configured to retrieve corresponding target blood glucose calibration data from a blood glucose calibration database of the user to be tested based on the skin texture information, wherein the blood glucose calibration database is constructed based on a blood glucose measurement dataset and blood glucose standard data of the user to be tested, wherein each blood glucose measurement data item in the blood glucose measurement dataset includes corresponding pre-test texture information and pre-test spectral measurement values, and each blood glucose measurement data item generates corresponding blood glucose calibration data;

[0112] The blood glucose detection module 540 is configured to determine the blood glucose result of the user to be detected based on the spectral measurement value and the blood glucose calibration data.

[0113] As an optional embodiment, the fingerprint sensor includes several sensor units.

[0114] As an optional embodiment, the spectrum measurement module 520 includes:

[0115] a data acquisition unit, configured to acquire skin contact data of a user to be detected through the sensor unit;

[0116] a statistical data unit, configured to count the number of sensor units detecting that the skin contact data is higher than a second preset threshold;

[0117] The area determination unit is configured to determine the skin contact area according to the number of sensor units that detect that the skin contact data is higher than a second preset threshold.

[0118] As an optional embodiment, the blood glucose calibration database is constructed in the following manner:

[0119] Acquire a blood glucose measurement data set and blood glucose standard data of the user to be detected, wherein each piece of blood glucose measurement data in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectrum measurement value;

[0120] determining the blood glucose calibration data according to the pre-test spectrum measurement value and the blood glucose standard data, wherein the blood glucose calibration data is used to characterize a mapping relationship between the pre-test spectrum measurement value and the blood glucose standard data;

[0121] The blood glucose calibration data is associated with the corresponding pre-check texture information and saved in the blood glucose calibration database.

[0122] As an optional embodiment, the blood glucose calibration module 530 includes:

[0123] an information comparison unit, configured to compare the skin texture information with the pre-detection texture information to determine that the user to be detected is a target detection user;

[0124] A data calling unit is configured to call corresponding blood glucose calibration data from a blood glucose calibration database of the target detection user according to the skin texture information when the user to be detected is the target detection user.

[0125] As an optional embodiment, the non-invasive blood glucose measurement device further includes:

[0126] The reminder output module is used to generate and output a reminder message when the skin contact area is lower than a first preset threshold, wherein the reminder message is used to remind the user to be detected to adjust the contact state with the fingerprint sensor.

[0127] As an optional embodiment, the fingerprint sensor is a capacitive fingerprint sensor, an optical fingerprint sensor, or an ultrasonic fingerprint sensor.

[0128] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 6 As shown, the electronic device includes a processor 610 and a memory 620. In a common product form, it may also include an input device 630, an output device 640, and a communication device 650. The number of processors 610 in the electronic device may be one or more. Figure 6 In the figure, a processor 610 is used as an example; the processor 610, the memory 620, the input device 630, the output device 640 and the communication device 650 in the electronic device can be connected via a bus or other means. Figure 6 The bus connection is taken as an example.

[0129] The memory 620, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the non-invasive blood glucose measurement method in the embodiments of the present application (for example, the information acquisition module 510, the spectral measurement module 520, the blood glucose calibration module 530, and the blood glucose detection module 540 in the non-invasive blood glucose measurement device). The processor 610 executes the software programs, instructions, and modules stored in the memory 620 to execute various functional applications and data processing of the electronic device, thereby implementing the above-mentioned non-invasive blood glucose measurement method.

[0130] The memory 620 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and applications required for at least one function; the data storage area may store data created based on the use of the electronic device, etc. In addition, the memory 620 may include a high-speed random access memory and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 620 may further include a memory remotely located relative to the processor 610, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0131] The input device 630 can be used to receive skin contact data obtained by the fingerprint sensor. The output device 640 can include a display device such as a display screen for displaying the blood glucose results of the user to be tested. The communication device 650 is used to communicate with the blood glucose calibration database.

[0132] The above-mentioned electronic device includes a non-invasive blood glucose measurement device, which can be used to perform any non-invasive blood glucose measurement method and has corresponding functions and beneficial effects.

[0133] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by an electronic device, it implements the relevant operations in the non-invasive blood glucose measurement method provided in any embodiment of the present application and has corresponding functions and beneficial effects.

[0134] Those skilled in the art should understand that the embodiments of the present application may be provided as methods, systems, or computer program products.

[0135] Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including the instruction device, which implements the function specified in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0136] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory. Memory may include non-permanent storage in a computer-readable medium, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0137] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0138] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0139] Note that the above are only preferred embodiments of the present application and the technical principles employed. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments, and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments and may include many other equivalent embodiments without departing from the scope of the present application. The scope of the present application is determined by the scope of the appended claims.

Claims

1. A non-invasive blood glucose measurement method, characterized in that: The non-invasive blood glucose measurement method is applied to a non-invasive blood glucose measurement device, which includes: a fingerprint sensor and an optical detector, wherein the fingerprint sensor is arranged around the optical detector; The non-invasive blood glucose measurement method comprises: Acquiring skin contact data of the user to be detected through the fingerprint sensor; determining a skin contact area based on the skin contact data, and when the skin contact area is greater than a first preset threshold, determining skin texture information of the user to be detected based on the skin contact data, and obtaining a spectral measurement value of the user to be detected through the optical detector; Retrieving corresponding target blood glucose calibration data from a blood glucose calibration database of the user to be detected based on the skin texture information, the blood glucose calibration database being constructed based on a blood glucose measurement dataset and blood glucose standard data of the user to be detected, each blood glucose measurement data in the blood glucose measurement dataset including corresponding pre-test texture information and pre-test spectral measurement values, and each blood glucose measurement data generating corresponding blood glucose calibration data; The blood glucose result of the user to be tested is determined according to the spectral measurement value and the target blood glucose calibration data.

2. The non-invasive blood glucose measurement method according to claim 1, wherein: The fingerprint sensor includes several sensor units.

3. The non-invasive blood glucose measurement method according to claim 2, characterized in that: Determining the skin contact area according to the skin contact data includes: Acquiring skin contact data of the user to be detected through the sensor unit; Counting the number of sensor units that detect that the skin contact data is higher than a second preset threshold; The skin contact area is determined according to the number of sensor units that detect that the skin contact data is higher than a second preset threshold.

4. The non-invasive blood glucose measurement method according to claim 1, wherein: The blood glucose calibration database is constructed in the following manner: Acquire a blood glucose measurement data set and blood glucose standard data of the user to be detected, wherein each piece of blood glucose measurement data in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectrum measurement value; determining the blood glucose calibration data according to the pre-test spectrum measurement value and the blood glucose standard data, wherein the blood glucose calibration data is used to characterize a mapping relationship between the pre-test spectrum measurement value and the blood glucose standard data; The blood glucose calibration data is associated with the corresponding pre-check texture information and saved in the blood glucose calibration database.

5. The non-invasive blood glucose measurement method according to claim 4, characterized in that: The step of calling corresponding blood glucose calibration data from a blood glucose calibration database of the user to be detected according to the skin texture information includes: Comparing the skin texture information with the pre-detection texture information to determine that the user to be detected is a target detection user; When the user to be detected is the target detection user, corresponding blood glucose calibration data is retrieved from the blood glucose calibration database of the target detection user according to the skin texture information.

6. The non-invasive blood glucose measurement method according to claim 1, characterized in that: The non-invasive blood glucose measurement method further comprises: When the skin contact area is lower than a first preset threshold, a reminder message is generated and output, where the reminder message is used to remind the user to be detected to adjust the contact state with the fingerprint sensor.

7. The non-invasive blood glucose measurement method according to claim 1, characterized in that: The fingerprint sensor is a capacitive fingerprint sensor, an optical fingerprint sensor or an ultrasonic fingerprint sensor.

8. A non-invasive blood glucose measurement device, characterized in that: include: The non-invasive blood glucose measurement device is applied to a non-invasive blood glucose measurement device, which includes a fingerprint sensor and an optical detector, wherein the fingerprint sensor is arranged around the optical detector; The non-invasive blood glucose measuring device comprises: An information acquisition module, configured to acquire skin contact data of a user to be detected through the fingerprint sensor; a spectral measurement module, configured to determine a skin contact area based on the skin contact data, determine skin texture information of the user to be detected based on the skin contact data when the skin contact area is greater than a first preset threshold, and obtain a spectral measurement value of the user to be detected through the optical detector; a blood glucose calibration module, configured to retrieve corresponding target blood glucose calibration data from a blood glucose calibration database of the user to be tested based on the skin texture information, wherein the blood glucose calibration database is constructed based on a blood glucose measurement data set and blood glucose standard data of the user to be tested, wherein each blood glucose measurement data item in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectral measurement values, and each blood glucose measurement data item generates corresponding blood glucose calibration data; The blood glucose detection module is used to determine the blood glucose result of the user to be detected based on the spectral measurement value and the blood glucose calibration data.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the non-invasive blood glucose measurement method according to any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the non-invasive blood glucose measurement method according to any one of claims 1 to 7 is implemented.

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