Noninvasive blood glucose measurement method, device and equipment and storage medium

Abstract

The embodiment of the invention discloses a non-invasive blood glucose measurement method, device and equipment and a storage medium, the method comprises the steps of obtaining skin contact data of a to-be-detected user through a fingerprint sensor, then determining a skin contact area according to the skin contact data, and when a contact state meets a preset condition, determining that the to-be-detected user is in contact with the skin contact area; if yes, skin texture information of the to-be-detected user is obtained from the skin contact data, a spectral measurement value of the to-be-detected user is obtained through an optical detector, and then corresponding target blood glucose calibration data is called from a blood glucose calibration database of the to-be-detected user according to the skin texture information; and determining a blood glucose result of the to-be-detected user according to the spectral measurement value and the target blood glucose calibration data. According to the method, on one hand, light leakage caused by poor contact between the to-be-detected user and the optical detector and influence on the detection result can be avoided, and on the other hand, errors caused by different contact positions measured by the to-be-detected user each time 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, device, equipment and storage medium. Background Art

[0002] According to statistics in 2015, there are about 130 million diabetic patients in my country, and diabetes has become one of the major problems that seriously affect the health of Chinese citizens. At present, there is no effective cure for diabetes, and controlling blood sugar concentration is the only treatment option. Timely blood sugar concentration testing is of great significance for controlling diabetes, preventing complications, and improving the quality of life of diabetic patients. At present, in the field of blood sugar concentration testing, most of them are tested by invasive blood glucose meters. Blood sampling is required during the testing process, which will cause trauma and pain to people, as well as the risk of wound infection. Therefore, non-invasive blood sugar measurement technology has always been a hot spot in cutting-edge technology research, among which optical methods are one of the most promising technical paths to achieve accurate non-invasive blood sugar measurement.

[0003] However, in the process of non-invasively measuring blood sugar using optical methods, there is often a problem of large measurement errors. On the one hand, the optical detector contacts the skin at different positions each time the user measures, resulting in significant errors in the measurement results. On the other hand, if the user does not operate properly and the skin is not in close contact with the optical detector, external ambient light will leak into the optical detector, causing large 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, wherein the non-invasive blood glucose measurement device comprises: a fingerprint sensor and an optical detector, wherein the fingerprint sensor is 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 according to the skin contact data, and when the skin contact area is higher than a first preset threshold, determining skin texture information of the user to be detected according to the skin contact data, and obtaining a spectral measurement value of the user to be detected through the optical detector;

[0009] According to the skin texture information, corresponding target blood glucose calibration data is called from a blood glucose calibration database of the user to be detected, 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 detected, each blood glucose measurement data in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectrum measurement value, and each blood glucose measurement data generates 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 comprises:

[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 detecting that the skin contact data is higher than a second preset threshold.

[0016] Wherein, the blood glucose calibration database is constructed in the following manner:

[0017] Acquire a blood sugar measurement data set and blood sugar standard data of the user to be detected, wherein each blood sugar measurement data in the blood sugar 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 called 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 comprises:

[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] Wherein, 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, wherein 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 sugar measuring device comprises:

[0028] An information acquisition module, used 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 according to the skin contact data, and when the skin contact area is higher than a first preset threshold, determine skin texture information of the user to be detected according to the skin contact data, and obtain a spectral measurement value of the user to be detected through the optical detector;

[0030] a blood glucose calibration module, configured to call corresponding target blood glucose calibration data from a blood glucose calibration database of the user to be detected according to 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 detected, wherein each blood glucose measurement data in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectrum measurement value, and each blood glucose measurement data 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, used for acquiring 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 used 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] Wherein, the blood glucose calibration database is constructed in the following manner:

[0038] Acquire a blood sugar measurement data set and blood sugar standard data of the user to be detected, wherein each blood sugar measurement data in the blood sugar 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 sugar calibration module comprises:

[0042] An information comparison unit, used 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 used 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 reminder information when the skin contact area is lower than a first preset threshold, wherein the reminder information is used to remind the user to be detected to adjust the contact state with the fingerprint sensor.

[0046] Wherein, 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 comprising 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] The embodiment of the present application obtains the skin contact data of the user to be detected through the fingerprint sensor, and then determines the skin contact area based on the skin contact data, thereby judging the contact state between the user to be detected and the fingerprint sensor based on the skin contact area. When the contact state meets the preset conditions, the skin texture information of the user to be detected is obtained from the skin contact data, and the spectral measurement value of the user to be detected is obtained through the optical detector. Then, the corresponding target blood glucose calibration data is called from the blood glucose calibration database of the user to be detected based on the skin texture information, thereby determining the blood glucose result of the user to be detected based on the spectral measurement value and the target blood glucose calibration data. This method can, on the one hand, judge the contact state between the user to be detected and the fingerprint sensor based on the skin contact area, thereby avoiding the situation where the user to be detected has poor contact with the optical detector, resulting in light leakage and thus affecting the detection result. On the other hand, the corresponding target blood glucose calibration data can be called 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 is a flow chart of a non-invasive blood glucose measurement method provided in an embodiment of the present application;

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

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

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

[0056] Figure 5 It is a structural schematic diagram of the non-invasive blood glucose measuring 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 scheme 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, rather than to limit the present application. It should also be noted that, for the convenience of description, only the part related to the present application but not all 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 chart describes 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 each operation can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0059] It should be noted that the present application specification does not enumerate all optional implementation modes. After reading the present 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 the technical features can constitute an optional implementation mode.

[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 sampling method is 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, the user often faces the problem that the contact position between the optical detector and the skin changes every time the instrument is used, resulting in significant errors in the measurement results. At the same time, improper user operation often causes the skin to be not in close contact with 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 is a flow chart of the non-invasive blood glucose measurement method provided by the present invention, and the non-invasive blood glucose measurement method is applied to a non-invasive blood glucose measurement device, referring to Figure 2 , Figure 2 The non-invasive blood glucose measuring device provided by the present invention is a schematic diagram of the structure. The non-invasive blood glucose measuring 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 shown, 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, it is necessary to obtain skin contact data of the user to be detected through the fingerprint sensor in the non-invasive blood glucose measurement device. The skin contact data is used to judge the contact situation between the contact part of the user to be detected and the fingerprint sensor. The specific form of the skin contact data is determined according to the type of the fingerprint sensor. For example, when the fingerprint sensor is a capacitive fingerprint sensor, the skin contact data is capacitance value data, when the fingerprint sensor is an optical fingerprint sensor, the skin contact data is a pulse signal or a video image signal, and 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 obtain skin contact data according to actual conditions.

[0064] Step 120: determine a skin contact area according to 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 according to the skin contact data, and obtain a spectral measurement value of the user to be detected through the optical detector.

[0065] In step 120, in order to reduce the risk of light leakage during the measurement process, it is necessary to determine the skin contact area based on the skin contact data, and then determine the contact situation between the user to be detected and the non-invasive blood glucose measurement device by comparing the skin contact area with the preset area. When the contact situation meets the preset conditions, the skin texture information of the user to be detected is further determined based on the acquired skin contact data, and the spectrum measurement value of the user to be detected is obtained through the optical detector. For example, taking the fingerprint sensor as an array capacitive fingerprint sensor as an example, the array capacitive fingerprint sensor includes a plurality of sensor units. After the user to be detected performs the measurement operation, that is, presses the non-invasive blood glucose measurement device, 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. Among them, the contact change threshold value can be a preset threshold value, and can also be set and adjusted according to the actual skin data of 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 in this blood glucose measurement operation.

[0066] It should be noted that the skin contact data is collected based on the fingerprint sensor arranged around the optical detector, so the skin contact area determined based on the skin contact data is the area surrounding the optical detector. Further, when it is judged that the skin contact area is higher than the first preset threshold, it means that the skin of the user to be detected is in close contact with the annular area around the optical detector, and the optical detector is arranged at the center of the annular area, and the skin of the user to be detected is in close contact with the optical detector, then it can be considered that the current measurement operation is normal and there is no risk of light leakage.

[0067] After determining that the skin of the user to be detected is in close contact with the non-invasive blood glucose measurement device, the skin texture information of the user to be detected is determined based on the skin contact data, and the spectral measurement value of the user to be detected is obtained through the optical detector. Among them, the skin texture information represents the skin texture characteristics, and the skin texture information can be an image of the fingerprint texture, or it can be the characteristic information of the skin texture, which is not specifically limited here. The spectral measurement value is used to characterize the reflection and absorption of the light irradiated on the skin of the user to be detected, and the light is emitted by the laser excitation light source on the optical detector. By detecting the reflection and absorption of the light irradiated on the skin, the blood glucose value can be calculated.

[0068] Step 130: Call corresponding target blood glucose calibration data from the blood glucose calibration database of the user to be detected according to the skin texture information, wherein the blood glucose calibration database is constructed based on the blood glucose measurement data set and the blood glucose standard data of the user to be detected, and each blood glucose measurement data in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectral measurement value, and 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 the error caused by the measurement position, it is necessary to first determine the relative position where the optical detector contacts the skin according to the skin texture information, and then obtain the target blood glucose calibration data corresponding to the relative position, so as to calibrate the measured spectral measurement value. Among them, 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 detected. Each blood glucose measurement data in the blood glucose measurement data set contains corresponding pre-test texture information and pre-test spectral measurement value, and then the corresponding blood glucose calibration data is generated by comparing the pre-test spectral measurement value with the blood glucose standard data, that is, each pre-test texture information corresponds to blood glucose calibration data.

[0070] Both the blood glucose measurement data set and the blood glucose standard data are obtained during the pre-test of the user to be tested, wherein the blood glucose measurement data set is the data measured after the user to be tested slightly adjusts the measurement position on the non-invasive blood glucose measurement device for multiple times, and the 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 blood glucose standard data is the precise blood glucose value of the user to be tested during the pre-test process, and the precise blood glucose value can be obtained through invasive blood glucose measurement or other methods, which are not limited here.

[0071] For example, refer to Figure 3 , Figure 3 The present invention provides a flow chart for calling blood glucose calibration data. The skin texture information extracted from the skin contact data is compared with the pre-test texture information in the blood glucose calibration database of the user to be tested. When it is determined that there is pre-test texture information matching the skin texture information, the target blood glucose calibration data corresponding to the pre-test texture information can be obtained.

[0072] It should be noted that the skin texture information determined by 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, so as to determine the relative position of the skin of the user to be detected in contact with the fingerprint sensor. Because the fingerprint sensor is arranged around the optical sensor, when the relative position of the skin of the user to be detected in contact with the fingerprint sensor is determined, the relative position of the skin of the user to be detected in contact with the optical sensor is also determined.

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

[0074] In step 140, it is necessary to determine the blood sugar result of the user to be tested based on the spectral measurement value and the target blood sugar calibration data. The non-invasive blood sugar device will emit light of a specific wavelength through the laser excitation light source of the optical detector. This light beam will irradiate 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, part 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 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, and the information of the glucose molecule absorbing the light (i.e., the spectral measurement value) can be obtained. Next, the measured spectral measurement value and the matched target blood sugar 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 sugar level based on the absorption and reflection information of the light.

[0075] This embodiment obtains the skin contact data of the user to be detected through the fingerprint sensor, and then determines the skin contact area based on the skin contact data, thereby judging the contact state between the user to be detected and the fingerprint sensor based on the skin contact area. When the contact state meets the preset conditions, the skin texture information of the user to be detected is obtained from the skin contact data, and the spectral measurement value of the user to be detected is obtained through the optical detector. Then, the corresponding target blood glucose calibration data is called from the blood glucose calibration database of the user to be detected based on the skin texture information, thereby determining the blood glucose result of the user to be detected based on the spectral measurement value and the target blood glucose calibration data. This method can, on the one hand, judge the contact state between the user to be detected and the fingerprint sensor based on the skin contact area, thereby avoiding the situation where the user to be detected has poor contact with the optical detector, resulting in light leakage and thus affecting the detection result. On the other hand, the corresponding target blood glucose calibration data can be called 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.

[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, which 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 4: 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 unit 1, sensor unit 2, sensor unit 3 and sensor unit 4. In this embodiment, by arranging the sensor units around the optical detector, the relative position of the skin of the user to be detected and the non-invasive blood glucose measurement device can be obtained. Through the coordinated work of multiple sensor elements, the quality and accuracy of the data are improved, and more abundant judgment basis is provided.

[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 detecting 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. Exemplarily, 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. Next, determine the number of sensor units whose skin contact data is higher than the second preset threshold, and determine the skin contact area based on the number of sensor units whose skin contact data is higher than the second preset threshold.

[0083] For example, reference Figure 4 , Figure 4It is a structural schematic diagram of another non-invasive blood glucose measuring 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 measuring 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 in this blood glucose measurement operation, the skin of the user to be detected is in close contact with the non-invasive blood glucose measuring device. For example, taking the case where the capacitance values ​​of sensor unit 1, sensor unit 2, and sensor unit 3 are greater than the contact change threshold value and the first preset threshold value is 50% (the ratio of the contact area to the total area), the areas with 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 sugar measurement data set and blood sugar standard data of the user to be detected, wherein each blood sugar measurement data in the blood sugar 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, it is necessary to construct a blood glucose calibration database so that the corresponding blood glucose calibration data can be called during the blood glucose measurement process. In order to construct the blood glucose calibration database, it is necessary to obtain the blood glucose measurement data set and blood glucose standard data of the user to be detected. The blood glucose measurement data set is the data measured after the user to be detected slightly adjusts the measurement position on the non-invasive blood glucose measurement device for multiple times. The 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 detected during the pre-test process. The precise blood glucose value can be obtained by invasive blood glucose measurement or by other means, which is not limited here. Then, the blood glucose calibration data is determined by the pre-test spectral measurement value and the blood glucose standard data. The blood glucose calibration data is used to characterize 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 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 saved in the blood glucose calibration database. The blood glucose calibration database can be a local database in 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 called from the blood glucose calibration database of the target detection user according to the skin texture information.

[0092] In this embodiment, the skin texture information needs to be matched before blood glucose detection can be performed. Specifically, the skin texture information needs to be compared with the pre-check texture information to determine that the user to be detected is the target detection user, and then the corresponding blood glucose calibration data is called from the blood glucose calibration database of the target detection user. For the comparison of skin texture information with pre-check texture information, feature points can be extracted from the skin texture information. These feature points are also called "detail features", including 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-check texture information fingerprint features. This is usually achieved by calculating the similarity between two fingerprint features. If the similarity exceeds a preset threshold, the two fingerprints are considered to match. Exemplarily, it can be determined by calculating the distance and direction difference between each feature point. If the distance and direction difference of 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 lower than the first preset threshold, it means that the contact between the user to be detected and the non-invasive blood glucose measurement device is not close during measurement, and there is a high risk of light leakage, thereby affecting the accuracy of the measurement. Therefore, when the skin contact area is lower than the first preset threshold, a corresponding reminder message is generated and output to remind the user to be detected to adjust the contact state with the fingerprint sensor. Among them, the reminder message can be a sound message, such as reminding the user through an output device such as a buzzer, a speaker, and a sound. For the sound, a preset reminder voice message can also be output. The voice message can be in Chinese or English. The content of the reminder message can be set by the user according to actual needs. The reminder message can also be a visual information on a display device. When the non-invasive blood glucose measurement device is provided with a display, a touch tablet or is connected to a smart terminal for communication, a corresponding text reminder message can be generated in the above-mentioned display device, such as displaying the text "Poor contact, please try again" on the screen, or the first reminder color can be changed to the second reminder color in a preset position on the screen, such as green to red.

[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 spectrum measurement value of the user to be detected through the optical detector;

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

[0100] The blood glucose result of the user to be detected 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 when the user to be detected is measured, the contact with the non-invasive blood glucose measurement device is not close, 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. Different from the above embodiment, this embodiment also needs to input the measured spectral measurement value, ambient light intensity data and the matched target blood glucose calibration data 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] For capacitive fingerprint sensors, the fingerprint image is created by using the body's own electrical conductivity. When a finger touches the surface of a capacitive sensor, the capacitance changes between the ridges and valleys of the fingerprint because 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] For optical fingerprint sensors, optical imaging technology is used to capture the fingerprint image. When the finger is placed on the optical sensor, the sensor emits light and captures their reflection on the fingerprint. The ridges and valleys of the fingerprint reflect light in different ways, and these differences are captured by the sensor and converted into a fingerprint image.

[0106] For ultrasonic fingerprint sensors, sound waves are used to map the details of the fingerprint. The sensor emits ultrasonic waves, and these waves reflect differently between 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 stains and dirt.

[0107] Reference Figure 5 , Figure 5 It 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 measuring device comprises:

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

[0110] a spectrum measurement module 520, configured to determine a skin contact area according to the skin contact data, and when the skin contact area is higher than a first preset threshold, determine skin texture information of the user to be detected according to the skin contact data, and obtain a spectrum measurement value of the user to be detected through the optical detector;

[0111] A blood glucose calibration module 530 is used to call corresponding target blood glucose calibration data from a blood glucose calibration database of the user to be detected according to 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 detected, wherein each blood glucose measurement data in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectrum measurement value, and each blood glucose measurement data generates corresponding blood glucose calibration data;

[0112] The blood glucose detection module 540 is used to determine the blood glucose result of the user to be detected according to 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, used for acquiring 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 used 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 sugar measurement data set and blood sugar standard data of the user to be detected, wherein each blood sugar measurement data in the blood sugar 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, used 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 used 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 reminder information when the skin contact area is lower than a first preset threshold, wherein the reminder information 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 A processor 610 is taken 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 example of connecting through bus is taken in the following.

[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 embodiment of the present application (for example, the information acquisition module 510, the spectrum 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 various functional applications and data processing of the electronic device by running the software programs, instructions and modules stored in the memory 620, that is, realizing 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 at least one application required for a function; the data storage area may store data created according to 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 arranged 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 may be used to receive the skin contact data acquired by the fingerprint sensor. The output device 640 may include a display device such as a display screen for displaying the blood glucose result 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 measuring device, which can be used to perform any non-invasive blood glucose measuring 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. 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 functions 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 an instruction device, which implements the functions 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, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

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

[0137] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. 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 disk read-only memory (CD-ROM), digital versatile disk (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 temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0138] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0139] Note that the above are only preferred embodiments of the present application and the technical principles used. 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 is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and 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 according to the skin contact data, and when the skin contact area is higher than a first preset threshold, determining skin texture information of the user to be detected according to the skin contact data, and obtaining a spectral measurement value of the user to be detected through the optical detector; According to the skin texture information, corresponding target blood glucose calibration data is called from a blood glucose calibration database of the user to be detected, 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 detected, each blood glucose measurement data in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectrum measurement value, and each blood glucose measurement data generates 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, characterized in that: 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 detecting that the skin contact data is higher than a second preset threshold.

4. The non-invasive blood glucose measurement method according to claim 1, characterized in that: The blood glucose calibration database is constructed in the following manner: Acquire a blood sugar measurement data set and blood sugar standard data of the user to be detected, wherein each blood sugar measurement data in the blood sugar 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 calling corresponding blood glucose calibration data from the 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 called 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 measuring device, characterized in that: include: The non-invasive blood glucose measurement device is applied to a non-invasive blood glucose measurement device, the non-invasive blood glucose measurement device comprises a fingerprint sensor and an optical detector, the fingerprint sensor is arranged around the optical detector; The non-invasive blood glucose measuring device comprises: An information acquisition module, used 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 according to the skin contact data, and when the skin contact area is higher than a first preset threshold, determine skin texture information of the user to be detected according to the skin contact data, and obtain a spectral measurement value of the user to be detected through the optical detector; a blood glucose calibration module, configured to call corresponding target blood glucose calibration data from a blood glucose calibration database of the user to be detected according to 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 detected, wherein each blood glucose measurement data in the blood glucose measurement data set includes corresponding pre-test texture information and pre-test spectrum measurement value, and each blood glucose measurement data 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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