Blood glucose data monitoring method for blood glucose monitoring device, and system

Abstract

A blood glucose data monitoring method for a blood glucose monitoring device, and a system, relating to the technical field of continuous glucose monitoring. The method comprises: determining motion state parameters of a user on the basis of test parameters respectively corresponding to an acceleration sensor and an angular velocity sensor at the current moment, wherein the motion state parameters comprise an acceleration vector force and an angular velocity change value; determining a tilt angle value of a blood glucose monitoring device on the basis of the motion state parameters; and determining the current motion state of the user on the basis of the tilt angle value, and matching a corresponding blood glucose monitoring algorithm on the basis of the current motion state, so as to determine the current blood glucose data of the user. The technical solution can achieve accurate identification of motion states of users, so as to achieve adjustment of related blood glucose monitoring algorithms on the basis of the motion states, thereby improving the accuracy of blood glucose value monitoring for the users.

Description

Method and system for blood glucose data monitoring in blood glucose monitoring devices

[0001] This application claims priority to Chinese Patent Application No. 202411824769.5, filed on December 11, 2024, entitled “Method and System for Monitoring Blood Glucose Data in a Blood Glucose Monitoring Device”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This invention relates to the field of continuous glucose monitoring technology, and in particular to a method and system for monitoring glucose data in a glucose monitoring device. Background Technology

[0003] With the increasing global prevalence of diabetes, blood glucose management has become a significant challenge in the healthcare field. Continuous glucose monitoring (CGM) devices help doctors assess patients' blood glucose control and guide adjustments to treatment plans. Existing CGM devices are implanted under the user's skin as chips to monitor blood glucose levels in real time.

[0004] However, clinical test results show that blood glucose levels vary depending on the user's exercise state, which can reduce the accuracy of blood glucose monitoring devices. Therefore, there is an urgent need to find a new method for blood glucose monitoring to improve its accuracy. Summary of the Invention

[0005] This invention provides a method and system for monitoring blood glucose data in a blood glucose monitoring device, which can accurately identify the user's exercise state and adjust the relevant monitoring algorithm according to the exercise state to improve the accuracy of blood glucose monitoring.

[0006] The embodiments of the present invention adopt the following technical solutions:

[0007] On one hand, embodiments of the present invention provide a method for monitoring blood glucose data in a blood glucose monitoring device, the blood glucose monitoring device including an accelerometer and an angular velocity sensor, the method comprising:

[0008] Based on the test parameters corresponding to the accelerometer and the angular velocity sensor at the current moment, the user's motion state parameters are determined; the motion state parameters include the acceleration vector force and the angular velocity change value.

[0009] The tilt angle value of the blood glucose monitoring device is determined based on the motion state parameters;

[0010] The user's current movement state is determined based on the tilt angle value, and a corresponding blood glucose monitoring algorithm is matched according to the current movement state to determine the user's current blood glucose data.

[0011] In one feasible implementation, the test parameters corresponding to the accelerometer at the current moment include a first reference voltage, an initial acceleration voltage, the accelerometer sensitivity, and the register values ​​and register bit numbers corresponding to each axis of the accelerometer in a first preset coordinate system.

[0012] In one feasible implementation, the method for determining the acceleration vector force at the current moment includes:

[0013] The first voltage value corresponding to each axis of the accelerometer is determined based on the first reference voltage of the accelerometer and the register value and register bit number corresponding to each axis.

[0014] Based on the first voltage value corresponding to each axis, the initial acceleration voltage, and the sensitivity of the acceleration sensor, the acceleration vector force of the acceleration sensor at the current moment is determined.

[0015] In one feasible implementation, the formula for calculating the acceleration vector force is: AccR(n)=[R x (n), R y (n), R z (n)];

[0016] Among them, R i (n)=VoltsR i (n)*K-VzeroG, i∈{x,y,z};

[0017] Among them, R i (n) represents the acceleration along the i-axis at time n; the i-axis represents the x-axis, y-axis, or z-axis in the first preset coordinate system; VoltsR i (n) represents the first voltage value of the accelerometer on the i-axis at time n; time n is the current time; K is the sensitivity of the accelerometer; VzeroG is the initial acceleration voltage.

[0018] In one feasible implementation, the test parameters of the angular velocity sensor include a second reference voltage, an initial angular velocity change value, a sensitivity coefficient, and the register values ​​and register bit numbers corresponding to each axis of the angular velocity sensor in a second preset coordinate system.

[0019] In one feasible implementation, the method for determining the change in angular velocity at the current moment includes:

[0020] The second voltage value corresponding to each axis of the angular velocity sensor is determined based on the second reference voltage of the angular velocity sensor and the register value and register bit number corresponding to each axis.

[0021] The angular velocity change value of the angular velocity sensor at the current moment is determined based on the second voltage value corresponding to each axis, the initial angular velocity change value, and the sensitivity coefficient.

[0022] In one feasible implementation, the formula for calculating the change in angular velocity is: RateR xz (n) = VR xz (n)Gyro*K r -VzeroRate; RateR yz (n) = VR yz (n)Gyro*K r -VzeroRate;

[0023] RateR xz (n) represents the change in angular velocity along the y-axis at time n of the angular velocity sensor;

[0024] VR xz (n)Gyro represents the second voltage value of the angular velocity sensor on the y-axis at time n; RateR yz (n) represents the change in angular velocity along the x-axis at time n of the angular velocity sensor; VR yz (n)Gyro represents the second voltage value of the angular velocity sensor on the x-axis at time n; where time n is the current time; K r VzeroG is the sensitivity coefficient; VzeroG is the initial angular velocity change value.

[0025] In one feasible implementation, determining the tilt angle value of the blood glucose monitoring device based on the motion state parameters includes:

[0026] The angular velocity vector force at the current moment is determined based on the angular velocity change value at the current moment and the angular velocity change value at each moment before the current moment;

[0027] The tilt angle of the blood glucose monitoring device at the current moment is determined based on the acceleration vector force and the angular velocity vector force.

[0028] In one feasible implementation, the formula for calculating the angular velocity vector force is: RGyro(n)=[R x Gyro(n), R y Gyro(n), R z Gyro(n)];

[0029] in,

[0030] Among them, A xz (n)=A xz(n-1)+RateR xz (n)*T,A xz (n) represents the angle of rotation of the angular velocity sensor around the y-axis at time n, A xz (n-1) represents the angle of rotation of the angular velocity sensor around the y-axis at time n-1;

[0031] A yz (n)=A yz (n-1)+RateR yz (n)*T,A yz (n) represents the angular velocity of the angular velocity sensor rotating about the x-axis at time n, A yz (n-1) represents the angle of rotation of the angular velocity sensor around the x-axis at time n-1; T is the time interval between time n and time n-1; and time n is the current time.

[0032] In one feasible implementation, the formula for calculating the tilt angle is: Rest(n)=(AccR(n)*w1(n)+RGyro(n)*w2(n)) / (w1(n)+w2(n));

[0033] Where AccR(n) is the acceleration vector force at time n, RGyro(n) is the angular velocity vector force at time n, w1(n) and w2(n) represent the weighting coefficients assigned to the acceleration sensor and the angular velocity sensor, respectively, and time n is the current time.

[0034] In one feasible implementation, the user's current motion state includes at least one of the following: sleep state, general activity state, and motion state.

[0035] In one feasible implementation, the user's current motion state is determined based on the tilt angle value, and a corresponding blood glucose monitoring algorithm is matched according to the current motion state to determine the user's current blood glucose data, specifically including:

[0036] The formula for obtaining the blood glucose fitting curve in the blood glucose monitoring algorithm is: y = kI + b; where y represents the blood glucose value, k represents the sensitivity of the blood glucose monitoring device, I represents the operating current of the blood glucose monitoring device, and b is the intercept.

[0037] When the tilt angle value is within the interval [a0, a1], it is determined that the current user is in a sleep state, and the sensitivity k0 is substituted into the blood glucose fitting curve formula to perform blood glucose fitting.

[0038] When the tilt angle value is within the interval [a2, a3], it is determined that the current user is in a normal activity state, and the sensitivity k1 is substituted into the blood glucose fitting curve formula to perform blood glucose fitting;

[0039] When the tilt angle is within the range [a4, a5], it is determined that the current user is in motion, and the sensitivity k2 is substituted into the blood glucose fitting curve formula to perform blood glucose fitting.

[0040] On the other hand, embodiments of the present invention also provide a method for monitoring analyte data in an analyte monitoring device, the analyte monitoring device including an accelerometer and an angular velocity sensor, the method comprising:

[0041] Based on the test parameters corresponding to the accelerometer and the angular velocity sensor at the current moment, the user's motion state parameters are determined; the motion state parameters include the acceleration vector force and the angular velocity change value.

[0042] The tilt angle value of the analyte monitoring device is determined based on the motion state parameters;

[0043] The user's current motion state is determined based on the tilt angle value, and the corresponding analyte monitoring algorithm is matched according to the current motion state to determine the user's current analyte data.

[0044] In one feasible implementation, the analytes include blood glucose, lactate, blood ketones, and blood oxygen.

[0045] Finally, this embodiment of the invention also provides a blood glucose data monitoring system, the system comprising:

[0046] The acquisition unit is used to determine the user's motion state parameters based on the test parameters corresponding to the accelerometer and the angular velocity sensor at the current moment; the motion state parameters include the acceleration vector force and the angular velocity change value.

[0047] The calculation unit is used to determine the tilt angle value of the blood glucose monitoring device based on the motion state parameters;

[0048] The matching unit is used to determine the user's current motion state based on the tilt angle value, and to match the corresponding blood glucose monitoring algorithm according to the current motion state to determine the user's current blood glucose data.

[0049] Compared with the prior art, the blood glucose data monitoring method and system for blood glucose monitoring devices provided in this invention have the following beneficial effects:

[0050] This invention comprehensively calculates the user's current motion state parameters by combining test parameters from accelerometers and angular velocity sensors. The angular velocity sensor compensates for the vibration and mechanical noise problems of the accelerometer, and the accelerometer compensates for the drift problem of the angular velocity sensor. The two work together to obtain a relatively more accurate tilt angle value of the current blood glucose monitoring device. Based on this tilt angle value, the user's motion state is determined, the trend of blood glucose changes is predicted in advance, and the blood glucose monitoring algorithm is adjusted in a timely manner according to the motion state, thereby improving the accuracy of blood glucose monitoring. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0052] Figure 1 is a flowchart of a blood glucose data monitoring method for a blood glucose monitoring device according to an embodiment of the present invention;

[0053] Figure 2 is a schematic diagram of the circuit architecture of a blood glucose monitoring device provided in an embodiment of the present invention;

[0054] Figure 3 is a schematic diagram of an angular velocity vector force provided in an embodiment of the present invention;

[0055] Figure 4 is a schematic diagram of a blood glucose fitting curve provided in an embodiment of the present invention;

[0056] Figure 5 is a schematic diagram of a blood glucose data monitoring system provided in an embodiment of the present invention. Detailed Implementation

[0057] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0058] This invention provides a method for monitoring analyte data using an analyte monitoring device. The analytes include lactic acid, blood ketones, blood glucose, and blood oxygen. The analyte monitoring device enables real-time monitoring of indicators such as lactic acid, blood ketones, blood glucose, and blood oxygen in human body fluids. The following describes a specific method using blood glucose as the analyte.

[0059] As a feasible implementation method, the present invention provides a method for monitoring blood glucose data in a blood glucose monitoring device, as shown in Figure 1, the method including steps S101-S103:

[0060] S101. Based on the test parameters corresponding to the accelerometer and angular velocity sensor at the current moment, determine the user's motion state parameters; the motion state parameters include the acceleration vector force and the change value of angular velocity.

[0061] Furthermore, firstly, the monitoring method provided by the present invention is applied to a blood glucose monitoring device, which includes an accelerometer and an angular velocity sensor.

[0062] As a feasible implementation method, Figure 2 is a schematic diagram of the circuit architecture of a blood glucose monitoring device provided by an embodiment of the present invention. As shown in Figure 2, the present invention integrates an accelerometer, an angular velocity sensor (such as a gyroscope), a three-electrode electrochemical current acquisition module, an impedance acquisition module, and a Bluetooth communication module on a single chip processor. This enables the blood glucose monitoring device to achieve Bluetooth communication function through the Bluetooth communication module, acceleration detection function through the accelerometer, angular velocity detection function through the gyroscope, tissue fluid impedance detection function through impedance acquisition, and current acquisition function through the three-electrode electrochemical current acquisition module.

[0063] Furthermore, when the user uses the blood glucose monitoring device, the test parameters corresponding to the accelerometer and angular velocity sensor at the current moment are obtained.

[0064] The test parameters corresponding to the accelerometer at the current moment include the first reference voltage, the initial acceleration voltage, the accelerometer sensitivity, and the register values ​​and register bit lengths corresponding to each axis of the accelerometer in the first preset coordinate system.

[0065] The test parameters of the angular velocity sensor include the second reference voltage, the initial angular velocity change value, the sensitivity coefficient, and the register values ​​and register bit numbers corresponding to each axis of the angular velocity sensor in the second preset coordinate system.

[0066] Furthermore, based on the test parameters corresponding to the accelerometer and angular velocity sensor at the current moment, the user's motion state parameters are determined, including the acceleration vector force and the change in angular velocity.

[0067] The method for determining the acceleration vector force at the current moment includes: determining the first voltage value corresponding to each axis of the accelerometer based on the first reference voltage of the accelerometer and the register values ​​and register bit numbers corresponding to each axis. Then, determining the acceleration vector force of the accelerometer at the current moment based on the first voltage value corresponding to each axis, the initial acceleration voltage, and the sensitivity of the accelerometer.

[0068] As a feasible implementation method, the formula for calculating the acceleration vector force is: AccR(n) =

[0069] [R x (n), R y (n), R z [(n)]; where R i (n)=VoltsR i (n)*K-VzeroG, i∈{x,y,z}; where R i (n) represents the acceleration along the i-axis at time n; the i-axis represents the x-axis, y-axis, or z-axis in the first preset coordinate system; VoltsR i (n) represents the first voltage value of the accelerometer on the i-axis at time n; time n is the current time; K is the sensitivity of the accelerometer; VzeroG is the initial acceleration voltage, which can be the acceleration voltage in the 0g state.

[0070] As one implementation method, the steps for obtaining the acceleration vector force are as follows:

[0071] 1) Obtain the register values ​​corresponding to the x-axis, y-axis, and z-axis of the accelerometer in the first preset coordinate system: X Accel =AdcR x Y Accel =AdcR y Z Accel =AdcR z Among them, AdcR x AdcR y AdcR z These are the ADC readings of the accelerometer on the x, y, and z axes, respectively.

[0072] 2) According to VoltsR x =X Accel *VREF / 2^register bits, converting the register values ​​on the x-axis into voltage values ​​VoltsR. x According to VoltsR y =Y Accel *VREF / 2^register bits, converting the y-axis register value into a voltage value VoltsR. y According to VoltsR z =Z Accel *VREF / 2^register bits, converting the z-axis register value into a voltage value VoltsR. z Where VREF is the reference voltage value of the accelerometer.

[0073] 3) Obtain the initial acceleration voltage VzeroG of the accelerometer and the accelerometer sensitivity K.

[0074] 4) According to formula R i (n)=VoltsR i (n)*K-VzeroG, i∈{x,y,z}, obtains the components R of the acceleration vector force on each axis at time n. i (n); the i-axis represents the x-axis, y-axis, or z-axis in the first preset coordinate system.

[0075] 5) According to R i (n), the acceleration vector force of the accelerometer at time n is: AccR(n)=[R x (n), R y (n), R z (n)].

[0076] Furthermore, the method for determining the angular velocity change value at the current moment includes: determining the second voltage value corresponding to each axis of the angular velocity sensor based on the second reference voltage of the angular velocity sensor and the register value and register bit number corresponding to each axis. Then, determining the angular velocity change value of the angular velocity sensor at the current moment based on the second voltage value corresponding to each axis, the initial angular velocity change value, and the sensitivity coefficient.

[0077] As a feasible implementation method, the formula for calculating the change in angular velocity is: RateR xz (n) = VR xz (n)Gyro*K r -VzeroRate;RateR yz (n) = VR yz (n)Gyro*K r -VzeroRate;

[0078] RateR xz (n) represents the change in angular velocity along the y-axis at time n of the angular velocity sensor; VR xz (n)Gyro represents the second voltage value of the angular velocity sensor on the y-axis at time n; RateR yz (n) represents the change in angular velocity along the x-axis at time n of the angular velocity sensor; VR yz (n)Gyro represents the second voltage value of the angular velocity sensor on the x-axis at time n; time n is the current time; K r VzeroG is the sensitivity coefficient; VzeroG is the initial angular velocity change value, which can be the angular velocity change value under the 0g state.

[0079] As one implementation method, the steps for obtaining the angular velocity change value are as follows:

[0080] 1) First, read the register values ​​corresponding to the x-axis and y-axis of the angular velocity sensor in the second preset coordinate system: X Gyro =AdcR x Y Gyro =AdcR y .

[0081] 2) According to VR yzGyro =X Gyro *VREF / 2^register bits, converts the register value on the x-axis into a voltage value VR. yzGyro According to VR xzGyr o = Y Gyro *VREF / 2^number of register bits converts the register value on the y-axis into a voltage value VR. xzGyro .

[0082] 3) Obtain the initial angular velocity change value VzreoRate and sensitivity coefficient Kr of the angular velocity sensor.

[0083] 4) According to RateR xz (n) = VR xz (n)Gyro*K r -VzeroRate calculates the change in angular velocity along the y-axis at time n using the angular velocity sensor; based on RateR yz (n) = VR yz (n)Gyro*K r -VzeroRate calculates the change in angular velocity along the x-axis at time n of the angular velocity sensor.

[0084] S102. Determine the tilt angle of the blood glucose monitoring device based on the motion state parameters.

[0085] Furthermore, based on the change in angular velocity at the current moment and the change in angular velocity at every moment before the current moment, the angular velocity vector force at the current moment is determined. Based on the acceleration vector force and the angular velocity vector force, the tilt angle of the blood glucose monitoring device at the current moment is determined.

[0086] Furthermore, the formula for calculating the angular velocity vector force at the current moment is: RGyro(n) =

[0087] [R x Gyro(n), R y Gyro(n), R z Gyro(n)].

[0088] in,

[0089] As shown in Figure 3, A in the figure xz(n)=A xz (n-1)+RateR xz (n)*T,A xz (n) represents the angle of rotation of the angular velocity sensor around the y-axis at time n, A xz (n-1) represents the angle of rotation of the angular velocity sensor around the y-axis at time n-1. A yz (n)=A yz (n-1)+RateR yz (n)*T,A yz (n) represents the angular velocity of the angular velocity sensor rotating about the x-axis at time n, A yz (n-1) represents the angle of rotation of the angular velocity sensor around the x-axis at time n-1; T is the time interval between time n and time n-1; time n is the current time.

[0090] Furthermore, after obtaining the angular velocity vector force at the current moment, the tilt angle of the blood glucose monitoring device is calculated according to the following formula: Rest(n)=(AccR(n)*w1(n)+RGyro(n)*w2(n)) / (w1(n)+w2(n)); where AccR(n) is the acceleration vector force at time n, RGyro(n) is the angular velocity vector force at time n, w1(n) and w2(n) represent the weighting coefficients assigned to the acceleration sensor and the angular velocity sensor, respectively, and time n is the current moment.

[0091] As a feasible implementation method, after the user implants the blood glucose monitoring chip, the initial state values ​​of the accelerometer and angular velocity sensor are first defined. Then, the system collects the test parameters of the accelerometer and angular velocity sensor every time interval T, and calculates the acceleration vector force AccR and the angular velocity change value RateR. Then, based on the angular velocity change value calculated at the nth time moment and the angular velocity change value calculated at the previous time moment, the angular velocity vector force at the nth time moment is iteratively derived. Finally, based on the acceleration vector force AccR(n) and angular velocity vector force Rgyro(n) at the nth time moment, the tilt angle of the blood glucose monitoring device at the nth time moment is calculated.

[0092] This invention comprehensively analyzes the test parameters of the accelerometer and the angular velocity sensor to obtain the user's motion state parameters. The angular velocity sensor compensates for the vibration and mechanical noise problems of the accelerometer, and the accelerometer compensates for the drift problem of the angular velocity sensor. The two work together to obtain a relatively more accurate tilt angle value of the current blood glucose monitoring device, which is better than using an accelerometer alone.

[0093] S103. Determine the user's current motion state based on the tilt angle value, and match the corresponding blood glucose monitoring algorithm according to the current motion state to determine the user's current blood glucose data.

[0094] Furthermore, the user's current activity state includes at least one of the following: sleep state, general activity state, or activity state. The user's current activity state is matched with the calculated tilt angle value at the current moment, thereby selecting different blood glucose monitoring algorithms for blood glucose monitoring based on the user's different states.

[0095] As a feasible implementation method, Figure 4 is a schematic diagram of a blood glucose fitting curve provided by an embodiment of the present invention. As shown in Figure 4, the formula for the blood glucose fitting curve in the blood glucose monitoring algorithm is: y = kI + b; where y represents the blood glucose value, k represents the sensitivity of the blood glucose monitoring device, I represents the operating current of the blood glucose monitoring device, and b is the intercept.

[0096] It should be noted that, according to clinical testing, during the blood glucose rise phase: blood glucose precedes tissue fluid glucose; during the blood glucose fall phase: 1) In non-exercise or sleep states, the main organs consuming glucose are the brain and liver, so changes in tissue fluid glucose detected by subcutaneous sensors should lag behind blood glucose; 2) During high-intensity exercise, the lower oxygen concentration in the blood affects glucose redox reactions, and glucose is primarily consumed by muscle and other tissue cells, therefore, the decrease in tissue fluid glucose precedes the decrease in blood glucose. Therefore, the blood glucose monitoring algorithm should differ depending on the user's exercise state, meaning the sensitivity of the blood glucose monitoring device should vary.

[0097] Therefore, the choice should be based on clinical test data:

[0098] When the tilt angle value Rest(n) is within the interval [a0,a1], it is determined that the current user is in a sleep state, and the sensitivity k0 is substituted into the above curve formula to perform blood glucose fitting.

[0099] When the tilt angle value Rest(n) is within the interval [a2,a3], it is determined that the current user is in a normal activity state, and the sensitivity k1 is substituted into the above curve formula to perform blood glucose fitting.

[0100] When the tilt angle value Rest(n) is within the interval [a4,a5], it is determined that the current user is in motion, and the sensitivity k2 is substituted into the above curve formula to perform blood glucose fitting.

[0101] This invention determines the user's movement state based on the tilt angle value, predicts the trend of blood glucose changes in advance, and adjusts the blood glucose monitoring algorithm in a timely manner according to the movement state, thereby improving the accuracy of blood glucose monitoring.

[0102] In addition, this embodiment of the invention also provides a user blood glucose data monitoring system, as shown in Figure 5. The user blood glucose data monitoring system 500 includes:

[0103] The acquisition unit 510 is used to determine the user's motion state parameters based on the test parameters corresponding to the acceleration sensor and the angular velocity sensor at the current moment; the motion state parameters include the acceleration vector force and the angular velocity change value.

[0104] The calculation unit 520 is used to determine the tilt angle value of the blood glucose monitoring device based on the motion state parameters;

[0105] The matching unit 530 is used to determine the user's current motion state based on the tilt angle value, and to match the corresponding blood glucose monitoring algorithm according to the current motion state to determine the user's current blood glucose data.

[0106] The various embodiments in this invention are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0107] The foregoing has described specific embodiments of the present invention. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0108] The above description is merely an embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, various modifications and variations can be made to the embodiments of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the embodiments of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for monitoring blood glucose data in a blood glucose monitoring device, characterized in that, The blood glucose monitoring device includes an accelerometer and an angular velocity sensor, and the method includes: Based on the test parameters corresponding to the accelerometer and the angular velocity sensor at the current moment, the user's motion state parameters are determined; the motion state parameters include the acceleration vector force and the angular velocity change value. The tilt angle value of the blood glucose monitoring device is determined based on the motion state parameters; The user's current movement state is determined based on the tilt angle value, and a corresponding blood glucose monitoring algorithm is matched according to the current movement state to determine the user's current blood glucose data.

2. The method according to claim 1, characterized in that, The test parameters corresponding to the accelerometer at the current moment include the first reference voltage, the initial acceleration voltage, the accelerometer sensitivity, and the register values ​​and register bit widths corresponding to each axis of the accelerometer in the first preset coordinate system.

3. The method according to claim 2, characterized in that, The method for determining the acceleration vector force at the current moment includes: The first voltage value corresponding to each axis of the accelerometer is determined based on the first reference voltage of the accelerometer and the register value and register bit number corresponding to each axis. Based on the first voltage value corresponding to each axis, the initial acceleration voltage, and the sensitivity of the acceleration sensor, the acceleration vector force of the acceleration sensor at the current moment is determined.

4. The method according to claim 3, characterized in that, The formula for calculating the acceleration vector force is: AccR(n)=[R x (n), R y (n), R z [(n)]; where R i (n)=VoltsR i (n)*K-VzeroG, i∈{x,y,z}; Among them, R i (n) represents the acceleration along the i-axis at time n; the i-axis represents the x-axis, y-axis, or z-axis in the first preset coordinate system; VoltsR i (n) represents the first voltage value of the accelerometer on the i-axis at time n; time n is the current time; K is the sensitivity of the accelerometer; VzeroG is the initial acceleration voltage.

5. The method according to claim 1, characterized in that, The test parameters of the angular velocity sensor include the second reference voltage, the initial angular velocity change value, the sensitivity coefficient, and the register values ​​and register bit numbers corresponding to each axis of the angular velocity sensor in the second preset coordinate system.

6. The method according to claim 5, characterized in that, The method for determining the change in angular velocity at the current moment includes: The second voltage value corresponding to each axis of the angular velocity sensor is determined based on the second reference voltage of the angular velocity sensor and the register value and register bit number corresponding to each axis. The angular velocity change value of the angular velocity sensor at the current moment is determined based on the second voltage value corresponding to each axis, the initial angular velocity change value, and the sensitivity coefficient.

7. The method according to claim 6, characterized in that, The formula for calculating the change in angular velocity is: RateR xz (n) = VR xz (n)Gyro*K r -VzeroRate; RateR yz (n) = VR yz (n)Gyro*K r -VzeroRate; RateR xz (n) represents the change in angular velocity along the y-axis at time n of the angular velocity sensor; VR xz (n)Gyro represents the second voltage value of the angular velocity sensor on the y-axis at time n; RateR yz (n) represents the change in angular velocity along the x-axis at time n of the angular velocity sensor; VR yz (n)Gyro represents the second voltage value of the angular velocity sensor on the x-axis at time n; where time n is the current time; K r VzeroG is the sensitivity coefficient; VzeroG is the initial angular velocity change value.

8. The method according to claim 7, characterized in that, Determining the tilt angle value of the blood glucose monitoring device based on the motion state parameters includes: The angular velocity vector force at the current moment is determined based on the angular velocity change value at the current moment and the angular velocity change value at each moment before the current moment; The tilt angle of the blood glucose monitoring device at the current moment is determined based on the acceleration vector force and the angular velocity vector force.

9. The method according to claim 8, characterized in that, The formula for calculating the angular velocity vector force is: RGyro(n)=[R x Gyro(n), R y Gyro(n), R z Gyro(n)]; in, Among them, A xz (n)=A xz (n-1)+RateR xz (n)*T,A xz (n) represents the angle of rotation of the angular velocity sensor around the y-axis at time n, A xz (n-1) represents the angle of rotation of the angular velocity sensor around the y-axis at time n-1; A yz (n)=A yz (n-1)+RateR yz (n)*T,A yz (n) represents the angular velocity of the angular velocity sensor rotating about the x-axis at time n, A yz (n-1) represents the angle of rotation of the angular velocity sensor around the x-axis at time n-1; T is the time interval between time n and time n-1; and time n is the current time.

10. The method according to claim 7, characterized in that, The formula for calculating the tilt angle is: Rest(n)=(AccR(n)*w1(n)+RGyro(n)*w2(n)) / (w1(n)+w2(n)); Where AccR(n) is the acceleration vector force at time n, RGyro(n) is the angular velocity vector force at time n, w1(n) and w2(n) represent the weighting coefficients assigned to the acceleration sensor and the angular velocity sensor, respectively, and time n is the current time.

11. The method according to claim 1, characterized in that, The user's current activity state includes at least one of the following: sleep state, general activity state, and activity state.

12. The method according to claim 11, characterized in that, Based on the tilt angle value, the user's current movement state is determined, and a corresponding blood glucose monitoring algorithm is matched according to the current movement state to determine the user's current blood glucose data, specifically including: The formula for obtaining the blood glucose fitting curve in the blood glucose monitoring algorithm is: y = kI + b; where y represents the blood glucose value, k represents the sensitivity of the blood glucose monitoring device, I represents the operating current of the blood glucose monitoring device, and b is the intercept. When the tilt angle value is within the interval [a0, a1], it is determined that the current user is in a sleep state, and the sensitivity k0 is substituted into the blood glucose fitting curve formula to perform blood glucose fitting. When the tilt angle value is within the interval [a2, a3], it is determined that the current user is in a normal activity state, and the sensitivity k1 is substituted into the blood glucose fitting curve formula to perform blood glucose fitting; When the tilt angle is within the range [a4, a5], it is determined that the current user is in motion, and the sensitivity k2 is substituted into the blood glucose fitting curve formula to perform blood glucose fitting.

13. A method for monitoring analyte data in an analyte monitoring device, characterized in that, The analyte monitoring device includes an acceleration sensor and an angular velocity sensor, and the method includes: Based on the test parameters corresponding to the accelerometer and the angular velocity sensor at the current moment, the user's motion state parameters are determined; the motion state parameters include the acceleration vector force and the angular velocity change value. The tilt angle value of the analyte monitoring device is determined based on the motion state parameters; The user's current motion state is determined based on the tilt angle value, and the corresponding analyte monitoring algorithm is matched according to the current motion state to determine the user's current analyte data.

14. The method according to claim 13, characterized in that, The analytes include blood glucose, lactate, blood ketones, and blood oxygen.

15. A blood glucose data monitoring system, characterized in that, The system includes: The acquisition unit is used to determine the user's motion state parameters based on the test parameters corresponding to the accelerometer and the angular velocity sensor at the current moment; the motion state parameters include the acceleration vector force and the angular velocity change value. The calculation unit is used to determine the tilt angle value of the blood glucose monitoring device based on the motion state parameters; The matching unit is used to determine the user's current motion state based on the tilt angle value, and to match the corresponding blood glucose monitoring algorithm according to the current motion state to determine the user's current blood glucose data.

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