Processing module, equipment and system for glucose concentration before and after movement

Abstract

The invention provides a processing module, equipment and system for glucose concentration before and after movement, and the processing module is used for detecting the glucose concentration of a to-be-detected object and giving guidance information. The processing module is configured to determine the fluctuation type of a glucose concentration curve before and after movement on the basis of glucose data including the time-varying glucose concentration before and after movement of the to-be-detected object, and the fluctuation type reflects the variation trend of the glucose concentration before and after movement; and generating guidance information or suggestions related to the motion behavior according to the fluctuation type. Therefore, the time for seeking suggestions of doctors can be reduced.

Description

[0001] This application is a divisional application of a patent application with an application date of 2021-09-15, an application number of 2021110783351, and an invention name of a glucose monitoring system for glucose concentration levels before and after exercise. Technical Field

[0002] The present invention specifically relates to a processing module, device and system for glucose concentration before and after exercise. Background Art

[0003] Diabetes and its chronic complications have become one of the diseases that seriously affect human health today. In order to delay and reduce the chronic complications of diabetes, glucose needs to be strictly controlled. Therefore, the continuous glucose monitoring system (CGMS) used to dynamically reflect glucose fluctuations is widely used. At present, there are many dynamic glucose monitoring systems that have been approved by the US FDA and / or CE for use in Europe and the United States. Most of them are minimally invasive and use subcutaneous probes to monitor interstitial fluid glucose, and a few monitor on the skin surface. The interstitial fluid glucose concentration measured by CGMS has a good correlation with the venous glucose concentration and the fingertip glucose concentration, and can be used as an auxiliary glucose monitoring method.

[0004] At present, dynamic glucose monitoring systems generally have high and low glucose warning mechanisms, which can send out warning signals when glucose is too low or too high. At the same time, clinical physicians can use the high and low glucose warning mechanisms to design more personalized treatment plans.

[0005] However, the existing technology does not provide users with analysis of the reasons for exercise and guidance information or suggestions based on the CGMS dynamic curve. It only gives some simple suggestions based on the level of glucose in the curve (such as whether to see a doctor for educational guidance). Doctors or diabetes educators need to spend 30-60 minutes interpreting the dynamic curve during exercise to output risk level assessment and auxiliary decision-making suggestions. Summary of the invention

[0006] The present invention is completed in view of the above-mentioned state of the prior art, and its purpose is to provide a glucose monitoring system for glucose concentration before and after exercise. It is a glucose monitoring system for detecting the glucose concentration of the subject to be tested and providing guidance information. It can analyze the fluctuation characteristics according to the glucose dynamic curve and help the subject to be tested and the doctor to read the report quickly and accurately, and provide suggestions or guidance information related to exercise behavior.

[0007] To this end, the present invention discloses a glucose monitoring system for glucose concentration before and after exercise, which is a glucose monitoring system for detecting the glucose concentration of a subject to be measured and providing guidance information, and is characterized in that it includes a sensor module, a communication module and a processing module, the sensor module is configured to detect glucose data of the subject to be measured, the glucose data including the glucose concentration of the subject to be measured that changes with time before and after exercise; the communication module is configured to receive the glucose data and send it to the processing module; the processing module is configured to determine the fluctuation type of glucose concentration based on the glucose data, the fluctuation type reflects the changing trend of the glucose concentration between before and after exercise, and generates guidance information or suggestions related to exercise behavior according to the fluctuation type.

[0008] In this case, the sensing module can continuously monitor the time-varying glucose concentration of the object to be tested before and after exercise in real time and generate data to send to the communication module, which is more convenient and faster than manual collection of glucose concentration; in addition, the communication module can send the real-time glucose data of the object to be tested to the processing module to generate real-time and continuous dynamic glucose data with a short sampling cycle to improve data accuracy; in addition, the processing module can receive and determine the fluctuation type of the glucose concentration of the object to be tested based on the received glucose data, and then generate guidance information or suggestions related to the exercise behavior based on the fluctuation type, and provide it to the object to be tested or the doctor in a timely manner, thereby reducing the time spent on traditional manual collection of glucose concentration and seeking doctor's advice.

[0009] According to the glucose monitoring system provided by the present invention, optionally, the glucose monitoring system further comprises an input module, and the input module is used to input the exercise time when the subject to be tested starts exercising. In this case, the glucose monitoring system can determine the exercise time of the subject to be tested so as to provide more accurate guidance information or suggestions to the subject to be tested or the doctor according to the glucose dynamic curve.

[0010] The glucose data includes the glucose concentrations of multiple detection points and the detection times that match the multiple detection points. If the movement time recorded by the subject to be tested is located at the midpoint of the detection times corresponding to two adjacent detection points, any one of the two adjacent detection points is used as the movement detection point. If the movement time recorded by the subject to be tested is not between the two adjacent detection points or is not located at the midpoint of the detection times corresponding to the two adjacent detection points, the detection point closest to the movement time recorded by the subject to be tested is used as the movement detection point. In this case, the glucose monitoring system can more accurately grasp the glucose data of the subject to be tested to determine the corresponding fluctuation characteristics.

[0011] According to the glucose monitoring system provided by the present invention, optionally, the time before exercise is the detection time corresponding to the exercise detection point, and the time after exercise is 3 hours to 5 hours after the time before exercise. In this case, the glucose monitoring system can determine the fluctuation type according to the change of the glucose concentration of the subject to be tested to provide the subject to be tested or the doctor with corresponding guidance information or suggestions.

[0012] According to the glucose monitoring system provided by the present invention, optionally, the processing module obtains the glucose concentration, the first glucose fluctuation amplitude and the second glucose fluctuation amplitude of the motion detection point based on the glucose data, and obtains the fluctuation type based on the glucose concentration of the motion detection point, the first glucose fluctuation amplitude and the second glucose fluctuation amplitude, wherein the first glucose fluctuation amplitude is the difference between the maximum glucose concentration among the detection points between the time before the exercise and the time after the exercise and the glucose concentration of the motion detection point, and the second glucose fluctuation amplitude is the difference between the glucose concentration of the motion detection point and the minimum glucose concentration among the detection points between the time before the exercise and the time after the exercise.

[0013] In this case, the glucose monitoring system can determine the corresponding fluctuation type based on the obtained glucose concentration, the first glucose fluctuation amplitude and the second glucose fluctuation amplitude at the motion detection point of the object to be tested, compared with the glucose concentration and fluctuation type algorithm configured in the processing module.

[0014] According to the glucose monitoring system provided by the present invention, optionally, the fluctuation types include rising, falling, rising first and then falling, falling first and then rising, normal fluctuation and not high before exercise, and normal fluctuation and slightly high before exercise. In this case, the glucose monitoring system can determine whether the subject to be tested belongs to the fluctuation type of rising, falling, rising first and then falling, falling first and then rising, normal fluctuation and not high before exercise, and normal fluctuation and slightly high before exercise according to the acquired glucose data, and provide corresponding guidance information or suggestions to the subject to be tested or the doctor according to the determined fluctuation type.

[0015] According to the glucose monitoring system provided by the present invention, optionally, the guidance information or suggestions related to exercise behavior include at least one of suggestions for exercise intensity, suggestions for exercise time, and suggestions for exercise method.

[0016] In this case, the glucose monitoring system can provide the subject under test or the doctor with at least one of recommendations on exercise intensity, exercise time, and exercise method based on the determined fluctuation type. Such recommendations can improve the quality of life of the subject under test and reduce the time spent by the subject under test seeking a doctor and the doctor providing evaluation recommendations.

[0017] According to the glucose monitoring system provided by the present invention, optionally, the processing module performs noise reduction processing on the glucose data. In this case, the glucose monitoring system can eliminate variables that may exist in the glucose data and affect the determination of the fluctuation type to obtain a more accurate fluctuation type.

[0018] According to the glucose monitoring system provided by the present invention, optionally, the processing module obtains a glucose concentration curve based on the glucose data and smoothes the glucose concentration curve. In this case, the glucose monitoring system can display a smoother glucose dynamic curve for the subject to be tested or the doctor, which can improve the user experience.

[0019] According to the glucose monitoring system provided by the present invention, optionally, the glucose monitoring system further comprises a display module, wherein the display module is configured to display at least one of guidance information, a glucose concentration curve and a fluctuation type, wherein the guidance information comprises the cause of the fluctuation type and guidance information or suggestions related to the exercise behavior. In this case, the subject to be tested or the doctor can observe the glucose data of the subject to be tested in real time, and can obtain the corresponding fluctuation type and guidance information or suggestions without the need for analysis and evaluation by the doctor.

[0020] According to the glucose monitoring system provided by the present invention, optionally, the glucose monitoring system further comprises a storage module, and the storage module is configured to store the glucose data. In this case, the glucose monitoring system can store glucose data of more days or exercise moments, and can compare glucose data of multiple days or multiple exercise moments to provide more reference information to the subject to be tested or the doctor.

[0021] According to the glucose monitoring system provided by the present invention, optionally, the sensor module is used to obtain the glucose concentration in the interstitial fluid, and the sensor module obtains the glucose concentration at a preset frequency. In this case, the interstitial fluid glucose concentration that can be measured by the glucose monitoring system has a good correlation with the venous glucose concentration and the finger glucose concentration, and can be used as an auxiliary glucose monitoring means to improve the measurement accuracy.

[0022] According to the glucose monitoring system provided by the present invention, optionally, the input module, the processing module and the display module are integrated into a mobile terminal device, and the mobile terminal device has a software program, and the software program is configured to input exercise time through the input module, obtain fluctuation type and guidance information through the processing module, and display guidance information through the display module. In this case, the subject to be tested can monitor its own glucose concentration in real time through such a convenient way as the mobile terminal device, and can obtain corresponding guidance suggestions to improve the quality of life.

[0023] According to the glucose monitoring system provided by the present invention, optionally, the processing module classifies the fluctuation type of glucose concentration based on classification conditions related to glucose concentration, the classification conditions including a first classification condition, a second classification condition, a third classification condition, and a fourth classification condition, the first classification condition being that the first glucose fluctuation amplitude is not less than a first preset value; the second classification condition being that the second glucose fluctuation amplitude is not less than a second preset value; the third classification condition being that the first peak value of the glucose data appears within a preset time after the exercise time; and the fourth classification condition being that the glucose concentration corresponding to the exercise detection point is not less than a third preset value.

[0024] In this case, the glucose monitoring system can more quickly obtain the fluctuation type corresponding to the glucose concentration of the subject under test at a certain exercise time according to the classified conditions in the processing module and provide corresponding guidance information or suggestions in a timely manner.

[0025] According to the glucose monitoring system provided by the present invention, optionally, the second preset value is equal to the first preset value, and the third preset value is greater than the second preset value. In this case, the glucose monitoring system can more quickly obtain the fluctuation type corresponding to the glucose concentration of the subject to be tested at a certain exercise time according to the classified conditions in the processing module and provide corresponding guidance information or suggestions in a timely manner.

[0026] According to the glucose monitoring system provided by the present invention, optionally, the first preset value is 1.5 to 2.0 mmol / L, the second preset value is 1.5 to 2.0 mmol / L, and the third preset value is not less than 7.0 mmol / L. In this case, the glucose concentration curve measured by the glucose monitoring system can more accurately classify the fluctuation type.

[0027] According to the glucose monitoring system provided by the present invention, optionally, the preset time is 10 minutes to 1 hour. In this case, the glucose monitoring system can accurately monitor the glucose concentration at the time of exercise.

[0028] According to the glucose monitoring system provided by the present invention, optionally, the sensor module detects the glucose concentration of the interstitial fluid of the subject to be tested by means of a sensor component that can react with glucose. In this case, the glucose monitoring system can obtain the required glucose data of the subject to be tested from the sensor module and can analyze and process the data, and then provide corresponding guidance information to the subject to be tested or the doctor.

[0029] According to the glucose monitoring system provided by the present invention, optionally, the communication module transmits the glucose data to the processing module wirelessly or by wire. In this case, transmitting the glucose data to the processing module by wireless means can be more convenient for the subject to be tested and can form a good user experience, and transmitting the glucose data to the processing module by wire can improve the integrity and stability of the data.

[0030] According to the glucose monitoring system provided by the present invention, optionally, the wireless method includes at least one of Bluetooth, Wi-Fi, 3G / 4G / 5G, NFC, UWB and Zig-Bee. In this case, transmitting the glucose data to the processing module by wireless means can be more convenient for the subject to be tested and can form a good user experience, and the glucose concentration of the subject to be tested can be observed remotely, which is convenient for doctors to provide professional guidance information or suggestions and medical care.

[0031] According to the present invention, a glucose monitoring system for glucose concentration before and after exercise can be provided. The system is used to detect the glucose concentration of the subject to be tested and provide guidance information or suggestions. The system can analyze the fluctuation characteristics according to the glucose dynamic curve and help the subject to be tested and the doctor to read the report quickly and accurately, and provide guidance information or suggestions or guidance information related to exercise behavior. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 is a schematic diagram of an application scenario of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention;

[0033] Figure 2 is a structural block diagram of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention;

[0034] Figure 3a A glucose concentration curve diagram of an embodiment of the present invention, wherein the fluctuation type of the glucose concentration of the glucose monitoring system before and after exercise is an increase;

[0035] Figure 3b A glucose concentration curve diagram of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention, wherein the fluctuation type is a decrease;

[0036] Figure 3c A glucose concentration curve diagram of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention, wherein the fluctuation type is first rising and then falling;

[0037] Figure 3dA glucose concentration curve diagram of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention, wherein the fluctuation type is first decreasing and then increasing;

[0038] Figure 3e-1 A glucose concentration curve diagram of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention, in which the fluctuation type is small and the glucose concentration is not high before exercise;

[0039] Figure 3e-2 A glucose concentration curve diagram of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention, wherein the fluctuation type is small and the glucose concentration is high before exercise;

[0040] Figure 4a It is a schematic diagram of an interface for real-time monitoring of glucose concentration before and after exercise by a mobile terminal device of a glucose monitoring system according to an embodiment of the present invention;

[0041] Figure 4b is a schematic diagram of an interface of a mobile terminal device for motion analysis of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention;

[0042] Figure 4c is a schematic diagram of an interface of guidance information of a mobile terminal device of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention;

[0043] Figure 4d It is a schematic diagram of an interface of a motion record of a mobile terminal device of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention;

[0044] Figure 4e It is a schematic diagram of an interface for recording glucose concentration of a mobile terminal device of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] It should be noted that the terms "first", "second", "third" and "fourth" in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices. In the following description, the same symbols are given to the same components, and repeated descriptions are omitted. In addition, the drawings are only schematic diagrams, and the ratio of the sizes of the components to each other or the shapes of the components may be different from the actual ones.

[0047] The glucose monitoring system for glucose concentration before and after exercise provided by the present invention is a glucose monitoring system for detecting the glucose concentration of a subject to be tested and providing guidance information, which can analyze the fluctuation characteristics according to the glucose dynamic curve and help the subject to be tested and the doctor to read the report quickly and accurately, and provide guidance information or suggestions or guidance information related to exercise behavior. The following is a detailed description in conjunction with the accompanying drawings.

[0048] The present invention discloses a glucose monitoring system for glucose concentration before and after exercise. In some examples, the glucose monitoring system for glucose concentration before and after exercise may also be referred to as a glucose concentration monitoring system or a glucose monitoring system.

[0049] Figure 1 is a schematic diagram of an application scenario of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention, Figure 2 It is a block diagram of the structure of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention.

[0050] like Figure 1 , 2 As shown, the present invention discloses a glucose monitoring system 1 for glucose concentration before and after exercise, which is a glucose monitoring system 1 for detecting the glucose concentration of a subject 2 to be measured and providing guidance information, and may include a sensor module 11, a communication module 12 and a processing module 134. The sensor module 11 may be configured to detect glucose data of the subject 2 to be measured, and the glucose data may include the glucose concentration of the subject 2 to be measured that changes with time before and after exercise; the communication module 12 may be configured to receive the glucose data and send it to the processing module 134; the processing module 134 may be configured to determine the fluctuation type of the glucose concentration based on the glucose data, and the fluctuation type reflects the changing trend of the glucose concentration between before and after exercise, and may generate guidance information or suggestions related to exercise behavior according to the fluctuation type.

[0051] In this case, the sensing module 11 can continuously monitor the glucose concentration of the object to be tested 2 before and after exercise over time in real time and generate data to send to the communication module 12, which is more convenient and faster than manually collecting glucose concentration; in addition, the communication module 12 can send the real-time glucose data of the object to be tested 2 to the processing module 134 to generate real-time and continuous dynamic glucose data with a short sampling cycle to improve data accuracy; in addition, the processing module 134 can receive and determine the fluctuation type of the glucose concentration of the object to be tested 2 based on the received glucose data, and then generate guidance information or suggestions related to the exercise behavior based on the fluctuation type, and provide it to the object to be tested 2 or the doctor in a timely manner, thereby reducing the time spent on traditional manual collection of glucose concentration and seeking doctor's advice.

[0052] In some examples, the glucose data may include the glucose concentrations of multiple detection points and the detection times that match the multiple detection points. If the motion time recorded by the subject 2 to be tested is located at the midpoint of the detection times corresponding to two adjacent detection points, any one of the two adjacent detection points is used as the motion detection point. If the motion time recorded by the subject 2 to be tested is not between the two adjacent detection points or is not located at the midpoint of the detection times corresponding to the two adjacent detection points, the detection point closest to the motion time recorded by the subject 2 to be tested is used as the motion detection point. In this case, the glucose monitoring system 1 can more accurately grasp the glucose data of the subject 2 to be tested to determine the corresponding fluctuation characteristics.

[0053] In some examples, such as Figure 2 As shown, the glucose monitoring system 1 may include a sensor module 11 , in which case the glucose monitoring system 1 is capable of collecting glucose concentration information.

[0054] In some examples, the sensor module 11 may be an implantable or semi-implantable glucose detection sensor. Preferably, the sensor module 11 may be an implantable glucose detection sensor. In this case, the implantable or semi-implantable sensor can alleviate the physiological pain caused by the traditional blood collection method of the subject 2 to be tested, and has the advantages of short collection cycle, more sampling data, and continuous sampling. In other examples, the sensor module 11 may also be a non-implantable sensor. In this case, the sampled patient needs to collect blood regularly, and the data accuracy is high.

[0055] In some examples, the sensor module 11 can be used to obtain the glucose concentration in the interstitial fluid. In other words, the sensor module 11 can be a subcutaneous implantable sensor. In this case, since the glucose concentration of the interstitial fluid is equal to or strictly corresponds to the plasma glucose under steady-state conditions, and the change rate of the glucose concentration of the blood is ahead of that of the interstitial fluid in a short period of time after the intake of high-sugar food or the injection of glucose, it can accurately reflect the glucose concentration of the object to be measured, that is, the glucose concentration of the interstitial fluid that can be measured by the glucose monitoring system 1 has a good correlation with the venous glucose concentration and the finger glucose concentration, and can be used as an auxiliary glucose monitoring means to improve the measurement accuracy.

[0056] In some examples, the sensor module 11 may acquire the glucose concentration at a preset frequency (or a preset acquisition frequency). In this case, multiple glucose concentrations can be obtained, thereby forming a nearly continuous glucose concentration curve.

[0057] In some examples, the sensor module 11 can be adjusted at a preset frequency. For example, when the glucose concentration of the object 2 to be measured changes by a small amplitude, the sensor module 11 can obtain the glucose concentration at a lower preset frequency. When the glucose concentration of the object 2 to be measured changes by a large amplitude, the sensor module 11 can obtain the glucose concentration at a higher preset frequency. In this case, the preset frequency of the sensor module 11 can be adjusted according to actual conditions.

[0058] In some examples, the sensor module 11 can also be used to obtain glucose data in other body fluids of the subject 2, for example, glucose concentration in urine.

[0059] In other examples, the sensor module 11 can detect the glucose concentration of the interstitial fluid of the subject 2 through a sensor component that can react with glucose. In this case, the glucose monitoring system 1 can obtain the required glucose data of the subject 2 from the sensor module 11 and can analyze and process it, and then provide corresponding guidance information to the subject 2 or the doctor.

[0060] In some examples, the sensor module 11 may be composed of a bioactive substance and microelectrodes. In this case, the bioactive substance can react with glucose and form an electrical signal on the microelectrodes through chemical signals to generate data.

[0061] In some examples, the sensor module 11 may be disposed near the upper arm of the subject 2 to be measured, thereby reducing the impact of the sensor module 11 on the daily life behavior of the subject 2 to be measured.

[0062] In some examples, preferably, the communication module 12 may be a wireless communication device, and the communication mode of the wireless communication device may be at least one of Bluetooth, Wi-Fi, 3G / 4G / 5G, NFC, UWB and Zig-Bee. In other examples, the communication module 12 may be a wired communication device, in which case, interference such as radiation and noise can be prevented to improve the stability and effectiveness of data transmission.

[0063] In some examples, the sensor module 11 and the communication module 12 can be integrated into one and can be implanted or semi-implanted into the body of the subject 2. In this case, after the sensor module 11 detects the glucose data of the subject 2, it can be directly sent to the communication module 12, so as to achieve instant detection, which is fast and convenient, and reduces the trouble of the subject 2 to carry the communication module 12 in real time.

[0064] In some examples, the communication module 12 can transmit the glucose data to the processing module 134 wirelessly or by wire. In this case, transmitting the glucose data to the processing module 134 by wireless can be more convenient for the subject 2 to be tested and can form a good user experience, and transmitting the glucose data to the processing module 134 by wire can improve the integrity and stability of the data.

[0065] In some examples, preferably, the communication module 12 can wirelessly transmit the glucose data to the processing module 134. In this case, the glucose monitoring system 1 can bring a better user experience to the subject 2 or other users.

[0066] In some examples, the wireless method may include at least one of Bluetooth, Wi-Fi, 3G / 4G / 5G, NFC, UWB, and Zig-Bee. In this case, wirelessly transmitting the glucose data to the processing module 134 can be more convenient for the subject 2 to be tested and can form a good user experience, and the glucose concentration of the subject 2 to be tested can be observed remotely, which is convenient for doctors to provide professional guidance and medical care.

[0067] In some examples, the communication module 12 can perform data transmission in a Bluetooth manner. In this case, the processing module 134 can obtain the monitoring data of the sensor module 11 within a limited range.

[0068] In some examples, such as Figure 2 As shown, the glucose monitoring system 1 may further include a display module 131, which may be configured to display at least one of the guidance information, the glucose concentration curve, and the fluctuation type. The display module 131 may also be integrated in a mobile terminal device, in other words, the display module may be a display interface of the mobile terminal device.

[0069] For example, Figures 4a to 4e It is a schematic diagram showing a real-time monitoring interface of a mobile terminal device of a glucose monitoring system for glucose concentration before and after exercise involved in an embodiment of the present invention, a schematic diagram of an interface for exercise analysis, a schematic diagram of an interface for guidance information, a schematic diagram of an interface for exercise recording, and a schematic diagram of an interface for glucose concentration recording.

[0070] In some examples, the guidance information includes the cause of the fluctuation type and guidance information or suggestions related to the exercise behavior. In this case, the subject 2 or the doctor can observe the glucose data of the subject 2 in real time and obtain the corresponding fluctuation type and guidance suggestions without the doctor's analysis and evaluation.

[0071] In some examples, such as Figure 2 As shown, the glucose monitoring system 1 may further include an input module 132, which may be used to input the exercise time when the subject 2 starts exercising. In this case, the glucose monitoring system 1 can determine the exercise time of the subject 2 to provide more accurate guidance information or suggestions to the subject 2 or the doctor based on the glucose dynamic curve.

[0072] In some examples, preferably, the recording module 132 can be integrated with the processing module 134. In this case, the information of the recorded movement of the object 2 to be measured can be received by the processing module 134 in real time and used for processing and analysis.

[0073] In some examples, the input module 132 can automatically identify the exercise time according to the glucose concentration. In this case, the operation steps of the subject 2 can be reduced, thereby improving the convenience of the glucose monitoring system 1.

[0074] In some examples, the recording module 132 may also record at least one of the time, type, and amount of exercise.

[0075] For example, Figure 4b , 4e As shown, the subject 2 can enter its exercise-related information, such as clock-in time, exercise type, etc., in the mobile terminal device of the glucose monitoring system 1 through the entry module.

[0076] In some examples, the glucose monitoring system 1 may further include a storage module 133 configured to store glucose data. In this case, the glucose monitoring system 1 can store glucose data of more days or exercise moments, and can compare glucose data of multiple days or multiple exercise moments to provide more reference information to the subject 2 or the doctor.

[0077] In some examples, the storage module 133 may be provided in the sensor module 11. In this case, the glucose data acquired by the sensor module 11 can be temporarily stored in the storage module 133. In some examples, the storage module 133 may be provided in the processing module 134. In this case, the glucose data from the sensor module 11 is collected and stored in the storage module 133 for a long time. In other words, the storage module 133 may include a first storage module (not shown) and a second storage module (not shown), the first storage module is integrated in the sensor module 11, and the second storage module is integrated in the mobile terminal device 13, the first storage module can be used to temporarily store the glucose data, and the glucose data of the first storage module is transmitted to the second storage module when the communication module 12 is working normally.

[0078] In some examples, the storage module 133 may overwrite the old glucose data with the new glucose data, and the detection time of the new glucose data and the old glucose data may differ by more than 14 days. In this case, the storage space of the storage module 133 can be fully utilized.

[0079] In some examples, preferably, the processing module 134 is located in a mobile terminal device 13 (described later), such as a personal mobile phone, a laptop, a computer, a custom processor, etc. In this case, the subject 2 or an observer such as a doctor can quickly and easily obtain the glucose data of the subject 2.

[0080] In some examples, the processing module 134 may also be a cloud processing device. In this case, the processing module 134 may monitor the glucose concentration of each object 2 at the same time.

[0081] In some examples, the input device of the mobile terminal device 13 can be used to input the exercise time information. In other words, the input module 132 can be the input device of the mobile terminal device 13. In this case, the exercise time information of the subject 2 can be input by voice input, touch screen input or keyboard input. In this case, the input information can be processed and analyzed by the processing module 134 quickly and conveniently, and the corresponding guidance information can be generated according to the glucose data and fed back to the subject 2 or the doctor.

[0082] In some examples, as described above, the storage module 133 and the processing module 134 can be integrated into the same mobile terminal device 13. In this case, the processing module 134 and the storage module 133 can coordinately process the glucose data of the subject 2 to generate multiple data types and store multiple days of data.

[0083] In some examples, the display module 131 and the processing module 134 can be integrated in the same mobile terminal device 13. In this case, the processing module 134 can display the glucose concentration of the subject 2 to the subject 2 or the doctor in real time after processing the data and can control the display module 131 to display the corresponding guidance information or suggestions in time.

[0084] In some examples, the input module 132, the processing module 134 and the display module 131 can be integrated into the mobile terminal device 13, and the mobile terminal device 13 has a software program, and the software program is configured to input the exercise time through the input module 132, obtain the fluctuation type and guidance information through the processing module 134, and display the guidance information through the display module 131. In this case, the subject 2 can monitor its own glucose concentration in real time through the mobile terminal device 13, and can obtain corresponding guidance suggestions to improve the quality of life.

[0085] In some examples, the input module 132, the processing module 134 and the display module 131 may not be integrated with the mobile terminal device 13, that is, the input module 132, the processing module 134 and the display module 131 may be separately provided. In this case, the functions of the input module 132, the processing module 134 and the display module 131 can be implemented in different locations respectively.

[0086] In some examples, the exercise time recorded by the subject 2 can also be outside two adjacent detection points, and the detection point closest to the exercise time is used as the exercise time detection point. In this case, the glucose monitoring system 1 can more accurately grasp the glucose data of the subject 2 to determine the corresponding fluctuation characteristics.

[0087] In some examples, the time before exercise can be the detection time corresponding to the exercise detection point, and the time after exercise can be 3 to 5 hours after the time before exercise. In this case, the glucose monitoring system 1 can determine the fluctuation type according to the change in the glucose concentration of the subject 2 to provide the subject 2 or the doctor with corresponding guidance information or suggestions or information.

[0088] In some examples, the time before exercise is the detection time corresponding to the exercise detection point, and the time after exercise is 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 7 hours, 8 hours, etc. after the time before exercise. In this case, the glucose monitoring system 1 can determine the fluctuation type according to the change of the glucose concentration of the subject 2 to provide the subject 2 or the doctor with corresponding guidance information or suggestions or information.

[0089] In some examples, processing module 134 may obtain the glucose concentration, the first glucose fluctuation amplitude, and the second glucose fluctuation amplitude at the motion detection point based on the glucose data, and obtain the fluctuation type based on the glucose concentration, the first glucose fluctuation amplitude, and the second glucose fluctuation amplitude at the motion detection point.

[0090] In some examples, the first glucose fluctuation amplitude may be a difference between a maximum glucose concentration among detection points between a time before exercise and a time after exercise and a glucose concentration at the exercise detection point.

[0091] In some examples, the second glucose fluctuation amplitude may be a difference between a glucose concentration at the exercise detection point and a minimum glucose concentration among detection points between a time before the exercise and a time after the exercise.

[0092] In this case, the glucose monitoring system 1 can determine the corresponding fluctuation type based on the obtained glucose concentration, the first glucose fluctuation amplitude and the second glucose fluctuation amplitude at the motion detection point of the object 2 to be tested, and the glucose concentration and fluctuation type algorithm configured in the processing module 134.

[0093] Figure 3a A glucose concentration curve diagram of an embodiment of the present invention, wherein the fluctuation type of the glucose concentration of the glucose monitoring system before and after exercise is an increase; Figure 3b A glucose concentration curve diagram of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention, wherein the fluctuation type is a decrease; Figure 3c A glucose concentration curve diagram of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention, wherein the fluctuation type is first rising and then falling; Figure 3d A glucose concentration curve diagram of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention, wherein the fluctuation type is first decreasing and then increasing; Figure 3e-1 A glucose concentration curve diagram of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention, in which the fluctuation type is small and the glucose concentration is not high before exercise; Figure 3e-2 This is a glucose concentration curve diagram of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention, in which the fluctuation type is small and the glucose concentration is higher before exercise.

[0094] In other examples, the processing module 134 may also be based on the glucose concentration at the motion detection point, the first glucose fluctuation amplitude, and the second glucose fluctuation amplitude, and may obtain the fluctuation type in other mathematical ways or algorithms based on the glucose concentration at the motion detection point, the first glucose fluctuation amplitude, and the second glucose fluctuation amplitude. In this case, the glucose monitoring system 1 may compare the obtained glucose concentration at the motion detection point of the subject 2, the first glucose fluctuation amplitude, and the second glucose fluctuation amplitude with the glucose concentration and fluctuation type algorithm configured in the processing module 134 to determine the corresponding fluctuation type.

[0095] In some examples, the fluctuation type may include rising, falling, rising first and then falling, falling first and then rising, normal fluctuation and not high before exercise, and normal fluctuation and slightly high before exercise. In this case, the glucose monitoring system 1 can determine whether the subject 2 at the moment of exercise belongs to the fluctuation type of rising, falling, rising first and then falling, falling first and then rising, normal fluctuation and not high before exercise, and normal fluctuation and slightly high before exercise according to the acquired glucose data, and provide corresponding guidance information or suggestions to the subject 2 or the doctor according to the determined fluctuation type.

[0096] In some examples, the guidance information or suggestions can be provided based on the number of days and fluctuation types monitored by the glucose monitoring system 1, but not limited to one type of guidance information or suggestions. For example, the number of days monitored by the glucose monitoring system 1 can be set to 15 consecutive days, or longer or shorter days. In this case, based on the corresponding motion information, fluctuation type, and number of days, the glucose monitoring system 1 can provide guidance information or suggestions adapted to the glucose concentration of the subject 2 to help improve their quality of life.

[0097] Figure 4a It is a schematic diagram of an interface for real-time monitoring of glucose concentration before and after exercise by a mobile terminal device of a glucose monitoring system according to an embodiment of the present invention; Figure 4b is a schematic diagram of an interface of a mobile terminal device for motion analysis of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention; Figure 4c It is a schematic diagram of an interface of guidance information of a mobile terminal device of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention.

[0098] In some examples, one fluctuation type may correspond to multiple coaching suggestions according to the number of monitoring days of the glucose monitoring system 1 .

[0099] like Figure 4a , 4band 4c. In some examples, guidance suggestions may include guidance suggestions for different types of exercise of the same exercise intensity and the number of check-ins. For example, guidance suggestions may include guidance suggestions for walking, brisk walking, housework, and ball games. Specifically, the first check-in is a low-intensity walk, and the corresponding guidance information or suggestions may be: low intensity, 1 kg of body weight consumes 2.625 kcal of energy in 1 hour, and a 12-minute walk is equivalent to 1,000 steps of energy; walking helps absorb food, promotes gastrointestinal motility, and normalizes bowel movements; the second check-in is a low-intensity walk, and the corresponding guidance information or suggestions may be: low intensity, 1 kg of body weight consumes 2.625 kcal of energy in 1 hour, and a 12-minute walk is equivalent to 1,000 steps of energy; exercise 3-5 times a week, 0.5-1 hour each time It can increase insulin sensitivity by 30%; the first punch-in is a moderate-intensity brisk walking exercise, and the corresponding guidance information or suggestions may be: moderate intensity, 1 kg of body weight consumes 4.2 kcal of energy in 1 hour, and 8 minutes of brisk walking is equivalent to the energy of 1000 steps. The knee and ankle joints are under greater pressure due to brisk walking, so you can use knee pads and ankle pads to protect them; the second punch-in is a moderate-intensity brisk walking exercise, and the corresponding guidance information or suggestions may be: moderate intensity, 1 kg of body weight consumes 4.2 kcal of energy in 1 hour, and 8 minutes of brisk walking is equivalent to the energy of 1000 steps. Pay attention to your walking posture when walking briskly, keep your chest and head up, lift your hips, and tighten your abdomen. Never bend over or hunch your back.

[0100] In some examples, the guidance suggestions may include monitoring days, for example, the guidance suggestions may indicate that today is the 1st day of using glucose monitoring system 1, the guidance suggestions may indicate that today is the 2nd day of using glucose monitoring system 1, the guidance suggestions may indicate that today is the 14th day of using glucose monitoring system 1, etc.

[0101] In some examples, as described above, guidance suggestions may include reasons for fluctuation types. Specifically, if the fluctuation type is increased, there may be multiple reasons, such as: 1. Did you exercise after a meal? Generally, the calories of a meal are much greater than the calories consumed by exercise. The overall performance of post-meal exercise glucose may still be increased, but the increase is smaller; 2. People often have both hypoglycemic factors and hyperglycemic factors. The hypoglycemic factor is strong, and glucose shows a decrease, and vice versa. If glucose increases after exercise, it is generally because the intensity, time, and energy consumption of exercise are small, which cannot offset the hyperglycemic factors such as food; 3. If you exercise during the process of post-meal glucose rise, the effect of exercise is to consume energy and reduce the hyperglycemic range of food. If you eat less and exercise more, glucose will decrease, and if you eat more and exercise less, glucose will increase. If the fluctuation type is a decrease, there may be a variety of reasons, such as: 1. Exercise is a good blood sugar lowering weight. Generally, exercise works faster than blood sugar lowering drugs. When glucose is high or rising, exercise often reduces glucose; 2. During exercise, glycogen in the muscles is consumed, and glucose in the blood is absorbed by the muscles, so glucose will decrease rapidly and significantly; 3. The blood sugar lowering effect of exercise lasts up to 8 hours. Even if glucose has many small fluctuations due to the effects of various blood sugar raising and lowering weights at every moment, the overall glucose tends to decrease. In this case, the subject 2 to be tested can preliminarily infer the reason for the corresponding fluctuation type.

[0102] In some examples, the causes of the fluctuation types in each guidance suggestion may be different from each other. In this case, the subject 2 to be tested can fully understand the multiple causes of the corresponding fluctuation types.

[0103] Figure 4d It is a schematic diagram of an interface of a motion record of a mobile terminal device of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention; Figure 4e It is a schematic diagram of an interface for recording glucose concentration of a mobile terminal device of a glucose monitoring system for glucose concentration before and after exercise according to an embodiment of the present invention.

[0104] In some examples, the guidance information or suggestions related to exercise behavior may also include at least one of suggestions for exercise intensity, suggestions for exercise time, and suggestions for exercise method.

[0105] In this case, the glucose monitoring system 1 can provide the subject 2 or the doctor with at least one of suggestions on exercise intensity, exercise time, and exercise method based on the determined fluctuation type. Such suggestions can improve the quality of life of the subject 2 and reduce the time spent by the subject 2 seeking a doctor and the doctor providing evaluation suggestions.

[0106] In some examples, the guidance suggestions may be as follows (without limitation):

[0107] Daily exercise: walking; Guidance information or suggestions: low intensity, 2.625 kcal of energy is consumed per kilogram of body weight in 1 hour, and 12 minutes of walking is equivalent to the energy of 1,000 steps; if you walk less than 4,000 steps a day, your physical activity is relatively low.

[0108] Daily exercise: brisk walking; Guidance information or suggestions: medium intensity, 4.2 kcal of energy is consumed per kilogram of body weight in 1 hour, and 8 minutes of brisk walking is equivalent to the energy of walking 1,000 steps; those with better body shape can choose to walk at a moderate speed, 100 to 120 steps per minute.

[0109] Daily exercise: running; Guidance information or suggestions: high intensity, 8.4 kcal of energy is consumed per kilogram of body weight in 1 hour, and running for 4 minutes is equivalent to the energy of walking 1,000 steps; it is more appropriate to exercise until you are no longer out of breath, have no chest tightness, sweat slightly but not heavily, and your legs are not sore.

[0110] Household activities: cooking; Guidance information or suggestions: low intensity, 2.625 kcal of energy is consumed per kilogram of body weight in 1 hour, and cooking for 12 minutes is equivalent to the energy of walking 1,000 steps; develop a cooking habit and enjoy the process of cooking.

[0111] Household activities: cleaning the house; Guidance information or suggestions: medium intensity, 3.675 kcal of energy is consumed per kilogram of body weight in 1 hour, and 9 minutes of cleaning the house is equivalent to the energy of walking 1,000 steps; although cleaning the house is not an activity with high intensity, it is repeated frequently and is also a good exercise for muscles.

[0112] Fitness exercise: Yoga; Guidance information or suggestions: Low intensity, 2.625 kcal of energy is consumed per kilogram of body weight in 1 hour, and 12 minutes of yoga is equivalent to the energy of walking 1,000 steps; it is best to practice yoga on an empty stomach, not after a full meal.

[0113] Fitness exercise: aerobics; Guidance information or suggestions: medium intensity, 3.675 kcal of energy is consumed per kilogram of body weight in 1 hour, and 9 minutes of aerobics is equivalent to the energy of walking 1,000 steps; doing aerobics is both leisure and entertainment, and physical exercise.

[0114] Ball sports: table tennis; Guidance information or suggestions: medium intensity, 4.2 kcal of energy is consumed per kilogram of body weight in 1 hour, and playing table tennis for 8 minutes is equivalent to the energy of walking 1,000 steps; table tennis can train people's reaction speed.

[0115] Ball sports: basketball; Guidance information or suggestions: High intensity, 6.3 kcal of energy is consumed per kilogram of body weight in 1 hour, and playing basketball for 5 minutes is equivalent to the energy of walking 1,000 steps; playing basketball regularly can cultivate people's sense of teamwork.

[0116] In some examples, the processing module 134 may perform noise reduction processing on the glucose data. In this case, the glucose monitoring system 1 can eliminate variables that may exist in the glucose data and affect the determination of the fluctuation type to obtain a more accurate fluctuation type.

[0117] In some examples, the processing module 134 can obtain a glucose concentration curve based on the glucose data and smooth the glucose concentration curve. In this case, the glucose monitoring system 1 can display a smoother glucose dynamic curve for the subject 2 or the doctor, which can facilitate the doctor to interpret the glucose dynamic curve and classify it, so that more accurate guidance and suggestions can be given, which can improve the user experience.

[0118] In some examples, the processing module 134 can classify the fluctuation type of glucose concentration based on classification conditions related to glucose concentration, the classification conditions including a first classification condition, a second classification condition, a third classification condition, and a fourth classification condition, the first classification condition being that the first glucose fluctuation amplitude is not less than a first preset value; the second classification condition being that the second glucose fluctuation amplitude is not less than a second preset value; the third classification condition being that the first peak of the glucose data appears within a preset time after the exercise time; and the fourth classification condition being that the glucose concentration corresponding to the exercise detection point is not less than a third preset value.

[0119] In this case, the glucose monitoring system 1 can more quickly obtain the fluctuation type corresponding to the glucose concentration of the subject 2 at a certain exercise time according to the classified conditions in the processing module 134 and the fluctuation characteristics of the glucose data curve and provide corresponding guidance suggestions in a timely manner.

[0120] In some examples, the second preset value may be greater than the first preset value, and the third preset value may be greater than the second preset value. In this case, the glucose monitoring system 1 may be optimized in terms of the algorithm and may more quickly obtain the fluctuation type corresponding to the glucose concentration of the subject 2 at a certain exercise time according to the classified conditions in the processing module 134 and provide corresponding guidance suggestions in a timely manner.

[0121] In some examples, the first preset value may be 1.5 to 2.0 mmol / L, for example, the first preset value may be 1.5 mmol / L, 1.6 mmol / L, 1.7 mmol / L, 1.8 mmol / L, 1.9 mmol / L, or 2.0 mmol / L, etc. Preferably, the first preset value may be 1.7 mmol / L or 1.8 mmol / L. In this case, it is possible to determine whether the glucose fluctuation before and after exercise is large.

[0122] In some examples, the second preset value may be 1.5 to 2.0 mmol / L, for example, the second preset value may be 1.5 mmol / L, 1.6 mmol / L, 1.7 mmol / L, 1.8 mmol / L, 1.9 mmol / L, or 2.0 mmol / L, etc. Preferably, the second preset value may be 1.7 mmol / L or 1.8 mmol / L. In this case, it is possible to determine whether the glucose fluctuation before and after exercise is large.

[0123] In some examples, the third preset value may be no less than 7.0mmol / L. For example, the third preset value may be 7.0mmol / L, 7.2mmol / L, 7.4mmol / L, 7.6mmol / L, 7.8mmol / L, 8.0mmol / L, 8.2mmol / L, 8.4mmol / L, 8.8mmol / L, 9.0mmol / L or 10.0mmol / L, etc. Preferably, the third preset value may be 7.0mmol / L, 7.2mmol / L, or 7.4mmol / L. In this case, it is possible to determine whether the glucose before exercise is high. Thus, the glucose concentration curve measured by the glucose monitoring system 1 can more accurately classify the fluctuation type.

[0124] In some examples, the preset time may be 10 minutes to 1 hour. For example, the preset time may be 0.5h, 0.6h, 0.7h, 0.8h, 0.9h, 1.0h. Preferably, the preset time may be 0.8h, 0.9h, 1.0h. In this case, the glucose monitoring system 1 can determine whether the glucose concentration first decreases and then increases or first increases and then decreases, and can thus accurately monitor the glucose concentration during exercise.

[0125] In some examples, the preset time can be set to a larger or smaller range of 0.5 to 2 hours. In this case, the glucose monitoring system 1 can accurately monitor the glucose concentration at the time of exercise. For example, according to the above-mentioned first classification condition, the second classification condition, the third classification condition, and the fourth classification condition, the following fluctuation types can be obtained (the units of the data described in the following algorithm are all mmol / L used for glucose concentration unless otherwise specified):

[0126] In some examples, such as Figure 3aAs shown: The analysis period of the glucose concentration curve with the fluctuation type of rising is the exercise time point - 4 hours after exercise. The fluctuation characteristics of the glucose concentration curve with the fluctuation type of rising are 1. The peak rises as a whole (partially can fall); 2. The highest value of the peak is not lower than the glucose value at the beginning of exercise (uncertain value) + the first preset value; 3. The lowest value of the trough is not lower than the glucose value at the beginning of exercise (uncertain value) - the first preset value. The formula algorithm of the glucose concentration curve with the fluctuation type of rising is 1. The highest value of the peak - the glucose value during exercise (uncertain value) >= the first preset value; 2. The glucose value during exercise (uncertain value) - the lowest value of the trough < the second preset value.

[0127] In some examples, such as Figure 3b As shown: The analysis period of the glucose concentration curve with fluctuation type as decrease is the exercise time point - 4 hours after exercise. The fluctuation characteristics of the glucose concentration curve with fluctuation type as decrease are 1. The peak decreases as a whole (partially may increase); 2. The highest value of the peak is lower than the glucose value at the beginning of exercise (uncertain value) + the first preset value; 3. The lowest value of the trough is lower than the glucose value at the beginning of exercise (uncertain value) - the first preset value. The formula algorithm of the glucose concentration curve with fluctuation type as decrease is 1. The highest value of the peak - the glucose value during exercise (uncertain value) < the first preset value; 2. The glucose value during exercise (uncertain value) - the lowest value of the trough > = the second preset value.

[0128] In some examples, such as Figure 3c As shown: The analysis period of the glucose concentration curve with the fluctuation type of first rising and then falling is the exercise time point - 4 hours after exercise. The fluctuation characteristics of the glucose concentration curve with the fluctuation type of first rising and then falling are 1. The fluctuation mainly appears first, followed by the fluctuation mainly falling; 2. The highest value of the peak is not lower than the glucose value at the beginning of exercise (uncertain value) + the first preset value; 3. The lowest value of the trough is not higher than the glucose value at the beginning of exercise (uncertain value) - the first preset value; 4. The start time of the first peak with the main rising is within 0.5 hours from the exercise time. The formula algorithm of the glucose concentration curve with the fluctuation type of first rising and then falling is 1. The highest value of the peak - the glucose value during exercise (uncertain value) >= the first preset value; 2. The glucose value during exercise (uncertain value) - the lowest value of the trough >= the second preset value.

[0129] In some examples, such as Figure 3dAs shown: The analysis period of the glucose concentration curve with the fluctuation type of first falling and then rising is the exercise time point - 4 hours after exercise. The fluctuation characteristics of the glucose concentration curve with the fluctuation type of first falling and then rising are 1. The fluctuation mainly appears first, followed by the fluctuation mainly rising; 2. The highest value of the peak is not lower than the glucose value at the beginning of exercise (uncertain value) + the first preset value; 3. The trough is not higher than the glucose value at the beginning of exercise (uncertain value) - the first preset value; 4. The start time of the first peak mainly falling is within 0.5 hours from the exercise time. The formula algorithm of the glucose concentration curve with the fluctuation type of first falling and then rising is 1. Glucose value during exercise (uncertain value) - the lowest value of the trough >= the first preset value; 2. The highest value of the peak - glucose value during exercise (uncertain value) >= the second preset value.

[0130] In some examples, such as Figure 3e-1 As shown: The analysis period of the glucose concentration curve with a fluctuation type of small fluctuation and not high before exercise is the exercise time point - 4 hours after exercise. The fluctuation characteristics of the glucose concentration curve with a fluctuation type of small fluctuation and not high before exercise are 1. The peak part rises and the part falls alternately; 2. The peak is lower than (glucose value at the beginning of exercise + the first preset value) (uncertain value); 3. The trough is higher than (glucose value at the beginning of exercise - the first preset value) (uncertain value); 4. Glucose is lower than the third preset value at the beginning of exercise. The formula algorithm of the glucose concentration curve with a fluctuation type of small fluctuation and not high before exercise is 1. The highest value of the peak - glucose value during exercise (uncertain value) < the first preset value; 2. Glucose value during exercise (uncertain value) - the lowest value of the trough < the second preset value; 3. Glucose before exercise < the third preset value.

[0131] In some examples, such as Figure 3e-2 As shown: The analysis period of the glucose concentration curve with a fluctuation type of small fluctuation and a high level before exercise is the exercise time point - 4 hours after exercise. The fluctuation characteristics of the glucose concentration curve with a fluctuation type of small fluctuation and a high level before exercise are 1. The peak part rises and the part falls alternately; 2. The peak is lower than (glucose value during exercise + the first preset value) (uncertain value); 3. The trough is higher than (glucose value during exercise - the first preset value) (uncertain value); 4. Glucose is not lower than the third preset value when starting exercise. The formula algorithm of the glucose concentration curve with a fluctuation type of small fluctuation and a high level before exercise is 1. The highest value of the peak - glucose value during exercise (uncertain value) < the first preset value; 2. Glucose value during exercise (uncertain value) - the lowest value of the trough < the second preset value; 3. Glucose before exercise >= the third preset value.

[0132] In addition, other types: the analysis period is the exercise time point - 4 hours after exercise, and the judgment logic or fluctuation characteristics do not meet the above 5 types, then the evaluation result of the fluctuation trend is irregular fluctuation of glucose after exercise (this type needs iterative logic and further classification).

[0133] Although the present invention is specifically described above in conjunction with the accompanying drawings and examples, it is to be understood that the above description does not limit the present invention in any form. Those skilled in the art can deform and change the present invention as needed without departing from the essential spirit and scope of the present invention, and these deformations and changes all fall within the scope of the present invention.

Claims

1. A processing module for glucose concentration before and after exercise, used to detect the glucose concentration of a subject to be tested and provide guidance information, characterized in that: The processing module is configured to determine the fluctuation type of the glucose concentration curve between before and after exercise based on glucose data including the glucose concentration of the subject to be tested that changes over time between before and after exercise, the fluctuation type reflecting the changing trend of the glucose concentration between before and after exercise, and generate guidance information or suggestions related to exercise behavior based on the fluctuation type.

2. The processing module according to claim 1, characterized in that Based on the glucose data, the glucose concentration, the first glucose fluctuation amplitude and the second glucose fluctuation amplitude at the time before the exercise are obtained; and based on the glucose concentration, the first glucose fluctuation amplitude and the second glucose fluctuation amplitude at the time before the exercise, the fluctuation type is obtained, wherein the first glucose fluctuation amplitude is the difference between the maximum glucose concentration among the detection points between the time before the exercise and the time after the exercise and the glucose concentration at the time before the exercise, and the second glucose fluctuation amplitude is the difference between the glucose concentration at the time before the exercise and the minimum glucose concentration among the detection points between the time before the exercise and the time after the exercise.

3. The processing module according to claim 2, characterized in that: The glucose concentration curve is classified into fluctuation types based on classification conditions related to glucose concentration, the classification conditions including a first classification condition, a second classification condition, a third classification condition, and a fourth classification condition, the first classification condition being that the first glucose fluctuation amplitude is not less than a first preset value, the second classification condition being that the second glucose fluctuation amplitude is not less than a second preset value, the third classification condition being that the first peak of the glucose data appears within a preset time after the exercise time, and the fourth classification condition being that the glucose concentration before the exercise time is not less than a third preset value.

4. The processing module according to any one of claims 1 to 3, characterized in that: The time before exercise is the detection time corresponding to the exercise detection point, and the glucose data includes glucose concentrations of multiple detection points and detection times matching the multiple detection points. If the exercise time recorded by the object to be measured is at the midpoint of the detection time corresponding to two adjacent detection points, any one of the two adjacent detection points is used as the motion detection point. If the exercise time recorded by the object to be measured is not between two adjacent detection points or is not at the midpoint of the detection time corresponding to two adjacent detection points, the detection point closest to the exercise time recorded by the object to be measured is used as the motion detection point.

5. The processing module according to claim 1, characterized in that: The post-exercise time is 3 to 5 hours after the pre-exercise time.

6. The processing module according to claim 1, characterized in that: The fluctuation types include rising, falling, rising first and then falling, falling first and then rising, not high before normal fluctuation movement, and relatively high before normal fluctuation movement.

7. The processing module according to claim 1, characterized in that: The guidance information or suggestions related to the exercise behavior include at least one of suggestions on exercise intensity, suggestions on exercise time, and suggestions on exercise methods.

8. The processing module according to claim 1, characterized in that: The guidance information or suggestions related to the exercise behavior include the reasons for the fluctuation type and / or the number of monitoring days.

9. A mobile terminal device, characterized in that: An input module, a processing module as described in any one of claims 1 to 8, and a display module are integrated; the input module is used to input the exercise time when the object to be tested starts exercising; the processing module is used to obtain the fluctuation type and guidance information; the display module is used to display at least one of the guidance information, the glucose concentration curve and the fluctuation type.

10. A glucose monitoring system for glucose concentration before and after exercise, used to detect the glucose concentration of a subject to be tested and provide guidance information, characterized in that: The glucose monitoring system comprises a sensing module, a communication module and a processing module according to any one of claims 1 to 8; the sensing module is configured to detect glucose data of the subject to be tested; and the communication module is configured to receive the glucose data and send it to the processing module.

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