Blood glucose data monitoring method and system for blood glucose monitoring equipment

Abstract

The invention discloses a blood glucose data monitoring method and system for blood glucose monitoring equipment, and belongs to the technical field of continuous blood glucose monitoring. The method comprises the steps that based on test parameters corresponding to an acceleration sensor and an angular velocity sensor at the current moment, motion state parameters of a user are determined; the motion state parameters comprise an acceleration vector force and an angular velocity change value; determining an inclination angle value of the blood glucose monitoring equipment according to the motion state parameters; and determining a current motion state of the user based on the inclination angle value, and matching a corresponding blood glucose monitoring algorithm according to the current motion state to determine current blood glucose data of the user. Through the technical scheme, the motion state of the user can be accurately recognized, so that a related blood glucose monitoring algorithm is adjusted according to the motion state, and the monitoring accuracy of the blood glucose value of the user is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of continuous blood glucose monitoring, and in particular to a blood glucose data monitoring method and system for a blood glucose monitoring device. Background Art

[0002] As the prevalence of diabetes continues to rise worldwide, blood sugar management has become a major challenge in the healthcare field. Continuous blood sugar monitoring devices can help doctors evaluate patients' blood sugar control and guide the adjustment of treatment plans. Existing continuous blood sugar monitoring devices can be implanted under the user's skin in the form of a chip to monitor the user's blood sugar level in real time.

[0003] However, according to clinical test results, the blood sugar changes of users in different exercise states are different, which will reduce the test accuracy of blood sugar monitoring equipment. Therefore, it is urgent to find a new blood sugar monitoring method to improve the accuracy of blood sugar monitoring. Summary of the invention

[0004] The embodiments of the present invention provide a blood glucose data monitoring method and system for a blood glucose monitoring device, which can accurately identify the user's exercise state, thereby adjusting the relevant monitoring algorithm according to the exercise state, thereby improving the monitoring accuracy of the user's blood glucose value.

[0005] The embodiment of the present invention adopts the following technical solutions:

[0006] In one aspect, an embodiment of the present invention provides a blood glucose data monitoring method for a blood glucose monitoring device, wherein the blood glucose monitoring device includes an acceleration sensor and an angular velocity sensor, and the method includes:

[0007] 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 acceleration vector force and angular velocity change value;

[0008] Determine the inclination value of the blood glucose monitoring device according to the motion state parameter;

[0009] The user's current motion state is determined based on the inclination 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.

[0010] In a feasible implementation manner, the test parameters corresponding to the acceleration sensor at the current moment include a first reference voltage, an initial acceleration voltage, an acceleration sensor sensitivity, and a register value and a register bit number corresponding to each axis of the acceleration sensor in the first preset coordinate system. Correspondingly, the method for determining the acceleration vector force at the current moment includes:

[0011] Determine the first voltage value corresponding to each axis of the acceleration sensor according to the first reference voltage of the acceleration sensor and the register value and the number of register bits corresponding to each axis;

[0012] The acceleration vector force of the acceleration sensor at the current moment is determined according to the first voltage values ​​respectively corresponding to the axes, the initial acceleration voltage and the acceleration sensor sensitivity.

[0013] In a feasible implementation manner, the calculation formula of the acceleration vector force is: AccR(n)=[R x (n), R y (n), R z (n)];

[0014] Among them, R i (n) = VoltsR i (n)*K-VzeroG, i∈{x, y, z};

[0015] Among them, R i (n) represents the acceleration of 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 acceleration sensor on the i-axis at time n; the time n is the current time; K is the sensitivity of the acceleration sensor; VzeroG is the initial acceleration voltage.

[0016] In a feasible implementation manner, the test parameters of the angular velocity sensor include a second reference voltage, an initial angular velocity change value, a sensitivity coefficient, and a register value and a register bit number corresponding to each axis of the angular velocity sensor in the second preset coordinate system. Correspondingly, the method for determining the angular velocity change value at the current moment includes:

[0017] Determine a second voltage value corresponding to each axis of the angular velocity sensor according to a second reference voltage of the angular velocity sensor and a register value and a register bit number corresponding to each axis;

[0018] The angular velocity change value of the angular velocity sensor at the current moment is determined according to the second voltage values ​​respectively corresponding to the axes, the initial angular velocity change value, and the sensitivity coefficient.

[0019] In a feasible implementation manner, the calculation formula for the angular velocity change value is:

[0020] RateR xz (n) = VR xz (n)Gyro*K r -VzeroRate;

[0021] RateR yz (n) = VR yz (n)Gyro*K r -VzeroRate;

[0022] Among them, RateR xz (n) represents the angular velocity change value of the angular velocity sensor on the y-axis at time n;

[0023] 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 angular velocity change value of the angular velocity sensor on the x-axis at time n; VR yz (n) Gyro represents the second voltage value of the angular velocity sensor on the x-axis at time n; the time n is the current time; K r is the sensitivity coefficient; VzeroG is the initial angular velocity change value.

[0024] In a feasible implementation manner, determining the inclination value of the blood glucose monitoring device according to the motion state parameter includes:

[0025] Determine the angular velocity vector force at the current moment according to the angular velocity change value at the current moment and the angular velocity change value at each moment before the current moment;

[0026] The inclination value of the blood glucose monitoring device at the current moment is determined according to the acceleration vector force and the angular velocity vector force.

[0027] In a feasible implementation manner, the calculation formula of the angular velocity vector force is: RGyro(n)=[R x Gyro(n), R y Gyro(n), R z Gyro(n)];

[0028] in,

[0029]

[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) = Ayz (n-1)+RateR yz (n)*T,A yz (n) represents the angular velocity of the angular velocity sensor rotating around 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 a feasible implementation manner, the calculation formula of the inclination value is: Rest(n)=(AccR(n)*w1(n)+RGyro(n)*w2(n)) / (w1(n)+w2(n));

[0033] Among them, 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 weight coefficients assigned to the acceleration sensor and the angular velocity sensor respectively, and the time n is the current time.

[0034] In a feasible implementation manner, the current motion state of the user includes at least any one of the following: sleeping state, general activity state, and motion state.

[0035] On the other hand, an embodiment of the present invention further provides a blood sugar data monitoring system, the system comprising:

[0036] An acquisition unit, configured to determine the motion state parameters of the user 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;

[0037] A computing unit, used for determining the inclination value of the blood glucose monitoring device according to the motion state parameter;

[0038] The matching unit is used to determine the user's current motion state based on the inclination value, and match the corresponding blood glucose monitoring algorithm according to the current motion state to determine the user's current blood glucose data.

[0039] Compared with the prior art, the blood glucose data monitoring method and system for a blood glucose monitoring device provided by the embodiment of the present invention have the following beneficial effects:

[0040] The present invention comprehensively calculates the motion state parameters of the current user through the test parameters of the acceleration sensor and the angular velocity sensor, and compensates for the vibration and mechanical noise problems of the acceleration sensor through the angular velocity sensor, and compensates for the drift problem of the angular velocity sensor through the acceleration sensor. The two work together to obtain a relatively more accurate inclination value of the current blood glucose monitoring device, and judge the user's motion state based on the inclination value, predict the change trend of blood glucose in advance, and adjust the blood glucose monitoring algorithm in time according to the motion state, thereby improving the accuracy of blood glucose monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0042] Figure 1 A flow chart of a blood sugar data monitoring method for a blood sugar monitoring device provided by an embodiment of the present invention;

[0043] Figure 2 A schematic diagram of a circuit architecture of a blood glucose monitoring device provided by an embodiment of the present invention;

[0044] Figure 3 A schematic diagram of an angular velocity vector force provided by an embodiment of the present invention;

[0045] Figure 4 A schematic diagram of a blood glucose fitting curve provided by an embodiment of the present invention;

[0046] Figure 5 A schematic diagram of the structure of a blood sugar data monitoring system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0049] The embodiment of the present invention provides a blood sugar data monitoring method for a blood sugar monitoring device, such as Figure 1 As shown, the method specifically includes steps S101-S103:

[0050] S101. Determine the motion state parameters of the user 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.

[0051] Specifically, firstly, the monitoring method provided by the present invention is applied to a blood glucose monitoring device, and the blood glucose monitoring device includes an acceleration sensor and an angular velocity sensor.

[0052] As a feasible implementation method, Figure 2 A circuit diagram of a blood glucose monitoring device provided by an embodiment of the present invention is shown in FIG. Figure 2 As shown, the present invention integrates an acceleration sensor, 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 processor of a chip, so that the blood glucose monitoring device can realize the Bluetooth communication function through the Bluetooth communication module, realize the acceleration detection function through the acceleration sensor, realize the angular velocity detection function through the gyroscope, realize the tissue fluid impedance detection function through impedance acquisition, and realize the current acquisition function through the three-electrode electrochemical current acquisition module.

[0053] Furthermore, when the user uses the blood glucose monitoring device, the test parameters corresponding to the acceleration sensor and the angular velocity sensor at the current moment are obtained.

[0054] The test parameters corresponding to the acceleration sensor at the current moment include a first reference voltage, an initial acceleration voltage, the acceleration sensor sensitivity, and register values ​​and register bit numbers corresponding to each axis of the acceleration sensor in the first preset coordinate system.

[0055] The test parameters of the angular velocity sensor include a second reference voltage, an initial angular velocity change value, a sensitivity coefficient, and register values ​​and register bit numbers corresponding to each axis of the angular velocity sensor in the second preset coordinate system.

[0056] Furthermore, the motion state parameters of the user are determined according to the test parameters respectively corresponding to the acceleration sensor and the angular velocity sensor at the current moment, wherein the motion state parameters include the acceleration vector force and the angular velocity change value.

[0057] The method for determining the acceleration vector force at the current moment includes: determining the first voltage value corresponding to each axis of the acceleration sensor according to the first reference voltage of the acceleration sensor and the register value and the number of register bits corresponding to each axis respectively. Then, determining the acceleration vector force of the acceleration sensor at the current moment according to the first voltage value corresponding to each axis respectively, the initial acceleration voltage and the acceleration sensor sensitivity.

[0058] As a feasible implementation method, the calculation formula of 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}; where R i (n) represents the acceleration of 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 acceleration sensor on the i-axis at time n; time n is the current time; K is the sensitivity of the acceleration sensor; VzeroG is the initial acceleration voltage, which can be specifically the acceleration voltage in the 0g state.

[0059] As a specific implementation method, the specific steps of obtaining the acceleration vector force are as follows:

[0060] 1) Obtain the register values ​​corresponding to the x-axis, y-axis and z-axis of the acceleration sensor in the first preset coordinate system respectively: 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 acceleration sensor on the x-axis, y-axis, and z-axis respectively.

[0061] 2) According to VoltsR x =X Accel *VREF / 2^register bit number, convert the x-axis register value into voltage value VoltsR x ; According to VoltsR y =Y Accel *VREF / 2^register bit number, convert the y-axis register value into a voltage value VoltsR y ; According to VoltsR z =Z Accel *VREF / 2^register bit number, convert the z-axis register value into voltage value VoltsR z Wherein, VREF is the reference voltage value of the acceleration sensor.

[0062] 3) Obtain the initial acceleration voltage VzeroG and accelerometer sensitivity K of the acceleration sensor.

[0063] 4) According to formula Ri (n) = VoltsR i (n)*K-VzeroG, i∈{x, y, z}, obtain the component R of the acceleration vector force on each axis at the nth moment i (n); the i-axis represents the x-axis, y-axis or z-axis in the first preset coordinate system.

[0064] 5) According to R i (n), the acceleration vector force of the acceleration sensor at time n is obtained as: AccR(n) = [R x (n), R y (n), R z (n)].

[0065] 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 according to the second reference voltage of the angular velocity sensor and the register value and the number of register bits corresponding to each axis respectively. Then, determining the angular velocity change value of the angular velocity sensor at the current moment according to the second voltage value corresponding to each axis respectively, the initial angular velocity change value and the sensitivity coefficient.

[0066] As a feasible implementation method, the calculation formula of the angular velocity change value is: RateR xz (n) = VR xz (n)Gyro*K r -VzeroRate;RateR yz (n) = VR yz (n)Gyro*K r -VzeroRate;

[0067] Among them, RateR xz (n) represents the angular velocity change value of the angular velocity sensor on the y-axis at time n;

[0068] 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 angular velocity change value of the angular velocity sensor on the x-axis at time n; 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 is the sensitivity coefficient; VzeroG is the initial angular velocity change value, which can be the angular velocity change value in the 0g state.

[0069] As a specific implementation, the specific steps of obtaining the angular velocity change value are as follows:

[0070] 1) First read the register values ​​of the angular velocity sensor corresponding to the x-axis and y-axis in the second preset coordinate system: Gyro =AdcR x , Y Gyro =AdcR y .

[0071] 2) According to VR yzGyro =X Gyro *VREF / 2^number of register bits, convert the x-axis register value into voltage value VR yzGyro According to VR xzGyro =Y Gyro *VREF / 2^register bit number, convert the y-axis register value into voltage value VR xzGyro .

[0072] 3) Obtain the initial angular velocity change value VzreoRate and sensitivity coefficient Kr of the angular velocity sensor.

[0073] 4) According to RateR xz (n) = VR xz (n)Gyro*K r -VzeroRate, calculate the angular velocity change value of the angular velocity sensor on the y-axis at time n; according to RateR yz (n) = VR yz (n)Gyro*K r -VzeroRate, calculates the angular velocity change value of the angular velocity sensor on the x-axis at time n.

[0074] S102. Determine the inclination value of the blood glucose monitoring device according to the motion state parameters.

[0075] Specifically, the angular velocity vector force at the current moment is determined according to the angular velocity change value at the current moment and the angular velocity change value at each moment before the current moment. The inclination value of the blood glucose monitoring device at the current moment is determined according to the acceleration vector force and the angular velocity vector force.

[0076] Furthermore, the calculation formula of the angular velocity vector force at the current moment is: RGyro(n) = [R x Gyro(n), R y Gyro(n), R z Gyro(n)].

[0077] in,

[0078]

[0079] Among them, Figure 3 As shown in the figure, A xz (n) = Axz (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. yz (n) = A yz (n-1)+RateR yz (n)*T,A yz (n) represents the angular velocity of the angular velocity sensor rotating around 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.

[0080] Furthermore, after obtaining the angular velocity vector force at the current moment, the inclination value 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)); wherein AccR(n) is the acceleration vector force at moment n, RGyro(n) is the angular velocity vector force at moment n, w1(n) and w2(n) respectively represent the weight coefficients assigned to the acceleration sensor and the angular velocity sensor, and moment n is the current moment.

[0081] As a feasible implementation method, after the user implants the blood glucose monitoring chip, the initial state values ​​of the acceleration sensor and the angular velocity sensor are first defined, and then the system collects the test parameters of the acceleration sensor and the angular velocity sensor once every time interval T, and calculates the acceleration vector force AccR and the angular velocity change value RateR. Then, according to the angular velocity change value calculated at the nth moment and the angular velocity change value calculated at the previous moment, the angular velocity vector force at the nth moment is iteratively derived. Then, according to the acceleration vector force AccR(n) and the angular velocity vector force Rgyro(n) at the nth moment, the inclination value of the blood glucose monitoring device at the nth moment is calculated.

[0082] The present invention comprehensively analyzes the test parameters of the acceleration sensor and the angular velocity sensor to obtain the user's motion state parameters, and uses the angular velocity sensor to compensate for the vibration and mechanical noise problems of the acceleration sensor, and uses the acceleration sensor to compensate for the drift problem of the angular velocity sensor. The two work together to obtain a relatively more accurate inclination value of the current blood glucose monitoring device, which is better than using an accelerometer alone.

[0083] S103. Determine the user's current motion state based on the inclination value, and match the corresponding blood glucose monitoring algorithm according to the current motion state to determine the user's current blood glucose data.

[0084] Specifically, the current motion state of the user includes at least any one of the following: sleeping state, general activity state, and motion state. The current motion state of the user is matched according to the calculated inclination value at the current moment, so that different blood glucose monitoring algorithms are selected for blood glucose monitoring according to different states of the user.

[0085] As a feasible implementation method, Figure 4 A schematic diagram of a blood glucose fitting curve provided by an embodiment of the present invention is shown in FIG. Figure 4 As shown, the blood glucose fitting curve formula in the blood glucose monitoring algorithm is: y=kI+b; wherein y represents the blood glucose value, k represents the sensitivity of the blood glucose monitoring device, I represents the working current of the blood glucose monitoring device, and b is the intercept.

[0086] It should be noted that according to clinical tests, during the blood sugar rising stage: blood glucose leads tissue fluid glucose; during the blood sugar falling stage: 1) in the non-exercise or sleep state, the main organs consuming glucose are the brain and liver, and the changes in tissue fluid glucose monitored by the subcutaneous sensor should lag behind blood glucose; 2) in the high-intensity exercise state, the oxygen concentration in the blood is less, which affects the glucose redox reaction. At this time, the main consumption of glucose is by cells in muscles and other tissues, so the decrease in tissue fluid glucose leads the decrease in blood glucose. It can be seen from this that the blood sugar monitoring algorithms corresponding to different exercise states of users are different, that is, the sensitivity of blood sugar monitoring equipment should be different.

[0087] Therefore, the choice is based on clinical test data:

[0088] When the inclination value Rest(n) is within the interval [a0, a1], it is determined that the current user is in a sleeping state, and the sensitivity k0 is substituted into the above curve formula for blood glucose fitting.

[0089] When the inclination value Rest(n) is within the interval [a2, a3], it is determined that the current user is in a general activity state, and the sensitivity k1 is substituted into the above curve formula for blood glucose fitting.

[0090] When the inclination 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 for blood glucose fitting.

[0091] The present invention determines the user's exercise state according to the inclination value, predicts the change trend of blood sugar in advance, and adjusts the blood sugar monitoring algorithm according to the exercise state in time, thereby improving the accuracy of blood sugar monitoring.

[0092] In addition, the embodiment of the present invention also provides a system for monitoring user blood sugar data. Figure 5 As shown, the monitoring system 500 of the user's blood glucose data specifically includes:

[0093] The acquisition unit 510 is used to determine the motion state parameters of the user 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;

[0094] A calculation unit 520, configured to determine the inclination value of the blood glucose monitoring device according to the motion state parameter;

[0095] The matching unit 530 is used to determine the user's current motion state based on the inclination value, and match the corresponding blood glucose monitoring algorithm according to the current motion state to determine the user's current blood glucose data.

[0096] Each embodiment of the present invention is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0097] The above describes specific embodiments of the present invention. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0098] The above description is only an embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the embodiments of the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present invention should be included in the protection scope of the present invention.

Claims

1. A blood glucose data monitoring method for a blood glucose monitoring device, characterized in that: The blood glucose monitoring device includes an acceleration sensor and an angular velocity sensor, and the method includes: 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 acceleration vector force and angular velocity change value; Determine the inclination value of the blood glucose monitoring device according to the motion state parameter; The user's current motion state is determined based on the inclination 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.

2. The method according to claim 1, characterized in that The test parameters corresponding to the acceleration sensor at the current moment include a first reference voltage, an initial acceleration voltage, an acceleration sensor sensitivity, and a register value and a register bit number corresponding to each axis of the acceleration sensor in a first preset coordinate system. Correspondingly, the method for determining the acceleration vector force at the current moment includes: Determine the first voltage value corresponding to each axis of the acceleration sensor according to the first reference voltage of the acceleration sensor and the register value and the number of register bits corresponding to each axis; The acceleration vector force of the acceleration sensor at the current moment is determined according to the first voltage values ​​respectively corresponding to the axes, the initial acceleration voltage and the acceleration sensor sensitivity.

3. The method according to claim 2, characterized in that The calculation formula of 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 of 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 acceleration sensor on the i-axis at time n; the time n is the current time; K is the sensitivity of the acceleration sensor; VzeroG is the initial acceleration voltage.

4. The method according to claim 1, characterized in that: The test parameters of the angular velocity sensor include a second reference voltage, an initial angular velocity change value, a sensitivity coefficient, and a register value and a register bit number corresponding to each axis of the angular velocity sensor in a second preset coordinate system. Correspondingly, the method for determining the angular velocity change value at the current moment includes: Determine a second voltage value corresponding to each axis of the angular velocity sensor according to a second reference voltage of the angular velocity sensor and a register value and a register bit number corresponding to each axis; The angular velocity change value of the angular velocity sensor at the current moment is determined according to the second voltage values ​​respectively corresponding to the axes, the initial angular velocity change value, and the sensitivity coefficient.

5. The method according to claim 4, characterized in that The calculation formula of the angular velocity change value is: RateR xz (n)=VR xz (n)Gyro*K r -VzeroRate; RateR yz (n)=VR yz (n)Gyro*K r -VzeroRate; Among them, RateR xz (n) represents the angular velocity change value of the angular velocity sensor on the y-axis at time n; 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 angular velocity change value of the angular velocity sensor on the x-axis at time n; VR yz (n) Gyro represents the second voltage value of the angular velocity sensor on the x-axis at time n; the time n is the current time; K r is the sensitivity coefficient; VzeroG is the initial angular velocity change value.

6. The method according to claim 5, characterized in that Determining the inclination value of the blood glucose monitoring device according to the motion state parameter includes: Determine the angular velocity vector force at the current moment according to the angular velocity change value at the current moment and the angular velocity change value at each moment before the current moment; The inclination value of the blood glucose monitoring device at the current moment is determined according to the acceleration vector force and the angular velocity vector force.

7. The method according to claim 6, characterized in that The calculation formula of 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 around 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.

8. The method according to claim 5, characterized in that The calculation formula of the inclination value is: Rest(n)=(AccR(n)*w1(n)+RGyro(n)*w2(n)) / (w1(n)+w2(n)); Among them, 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 weight coefficients assigned to the acceleration sensor and the angular velocity sensor respectively, and the time n is the current time.

9. The method according to claim 1, characterized in that: The current motion state of the user includes at least any one of the following: sleeping state, general activity state, and motion state.

10. A blood sugar data monitoring system, characterized in that: The system comprises: An acquisition unit, configured to determine the motion state parameters of the user 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; A computing unit, used for determining the inclination value of the blood glucose monitoring device according to the motion state parameter; The matching unit is used to determine the user's current motion state based on the inclination value, and 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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