Electronic device and blood glucose data management method thereof

Abstract

An electronic device and a blood glucose data management method thereof are provided. The blood glucose data management method includes identifying first blood glucose data based on a blood glucose sensor, identifying a verification data set corresponding to the first blood glucose data, estimating whether at least a portion of the blood glucose sensor is detached from a user's body based on a comparison between a pattern corresponding to the verification data set and a reference pattern, and suspending output of the first blood glucose data if it is estimated that the detachment occurs.

Description

[0001] Cross-reference to related applications

[0002] This application claims the benefit of Korean Patent Application No. 10-2025-0026121, filed on February 27, 2025, with the Korean Intellectual Property Office, the disclosure of which is incorporated herein by reference. Technical Field

[0003] The example implementation involves an electronic device and a method for managing blood glucose data. Background Technology

[0004] A continuous glucose monitoring system (CGMS) is a device for real-time monitoring of blood glucose changes in diabetic patients. Due to its convenience, it has recently become widely used, allowing patients to measure glucose concentration in the interstitial fluid beneath the skin via a percutaneously inserted sensor, without the need for blood sampling.

[0005] While CGMS offers many advantages, one drawback is that it can potentially produce distorted or unreliable blood glucose readings if the glucose sensor attachment becomes unstable or detaches from the patient's skin. Such risks can lead to incorrect treatment decisions and may compromise patient safety.

[0006] Therefore, reliable detection of sensor detachment is crucial. However, sensor detachment often occurs without obvious physical symptoms, making it difficult to detect through simple adhesion checks alone.

[0007] Furthermore, due to the nature of continuous glucose monitoring systems (CGMS), the ability to statistically manage glucose readings is fundamentally provided and considered an important feature for users. From this perspective, how to statistically process and manage data obtained from detached sensors is a crucial consideration for improving user experience. However, discussions on this topic have not been fully developed. Summary of the Invention

[0008] On the one hand, an electronic device and a method for managing blood glucose data therewith are provided, and more specifically, a method for detecting the detachment of a blood glucose sensor based on blood glucose patterns and managing blood glucose data obtained from the detached sensor is provided.

[0009] The technical aspects of this invention are not limited to those mentioned above, and other technical aspects can be inferred from the following example embodiments.

[0010] According to one aspect, a method for managing blood glucose data in an electronic device is provided, the method comprising: identifying first blood glucose data based on a blood glucose sensor; identifying a validation dataset corresponding to the first blood glucose data; estimating whether at least a portion of the blood glucose sensor has become detached from the user's body based on a comparison between a pattern corresponding to the validation dataset and a reference pattern; and pausing the output of the user's first blood glucose data if the detachment is estimated to have occurred.

[0011] In an example embodiment of this disclosure, the blood glucose data management method may further include, prior to identifying the first blood glucose data based on a blood glucose sensor, periodically checking the blood glucose data based on a blood glucose sensor inserted percutaneously into the user's body. The first blood glucose data may be measured by the blood glucose sensor during the next measurement cycle of the periodically checked blood glucose data.

[0012] Furthermore, in an example embodiment of this disclosure, identifying a validation dataset corresponding to the first blood glucose data may include identifying at least one previous blood glucose data whose blood glucose measurement sequence is continuous with the first blood glucose data, and identifying a validation dataset comprising the first blood glucose data and at least one previous blood glucose data that are time-series aligned.

[0013] Furthermore, in an example embodiment of this disclosure, estimating whether at least a portion of the blood glucose sensor has detached may include identifying multiple time-series aligned blood glucose data included in a verification dataset, determining whether the pattern of the multiple blood glucose data corresponds to at least one of a first reference pattern and a second reference pattern included in a reference pattern, and estimating that at least a portion of the blood glucose sensor has detached if the pattern of the multiple blood glucose data corresponds to at least one of the first reference pattern and the second reference pattern.

[0014] Furthermore, in an exemplary embodiment of this disclosure, the first reference mode may include a mode in which, among two blood glucose data points having a sequential blood glucose measurement order in a plurality of blood glucose data, the subsequent blood glucose data decreases by more than a first threshold compared to the previous blood glucose data.

[0015] Furthermore, in an example embodiment of this disclosure, the first reference mode may also include a mode in which the slope between two blood glucose data points in which the blood glucose measurement order is later than the blood glucose measurement order of a previous blood glucose data is less than 0.

[0016] Furthermore, in an example embodiment of this disclosure, the second reference mode may include a mode in which at least one of the multiple blood glucose data is equal to or less than a second threshold.

[0017] Furthermore, in an example embodiment of this disclosure, estimating whether at least a portion of the blood glucose sensor is dislodged may include adjusting at least one threshold associated with a reference pattern based on the user's medical history information.

[0018] Furthermore, in an exemplary embodiment of this disclosure, adjusting at least one threshold associated with a reference pattern may include identifying medical history information indicating that a user has type 1 diabetes, and adjusting a first threshold of a first reference pattern associated with the amount of decrease in subsequent blood glucose data relative to previous blood glucose data in two consecutive blood glucose measurement sequences, such that the first threshold is increased.

[0019] Furthermore, in an example embodiment of this disclosure, adjusting at least one threshold associated with a reference pattern may include identifying medical history information indicating that a user has a history of hypoglycemic shock, and adjusting a second threshold of a second reference pattern associated with the size of at least one of a plurality of blood glucose data included in the validation dataset, such that the second threshold is reduced.

[0020] Furthermore, in an example embodiment of this disclosure, the blood glucose data management method may also include identifying a second blood glucose data that has increased compared to the first blood glucose data based on a blood glucose sensor, releasing the pause in outputting the first blood glucose data, and normally outputting the first blood glucose data to the user.

[0021] Furthermore, in an example embodiment of this disclosure, the blood glucose data management method may further include, before identifying a second blood glucose data that has increased compared to a first blood glucose data based on the blood glucose sensor, and after releasing the pause in outputting the first blood glucose data, checking a flag related to squeeze noise set for the first blood glucose data, and controlling the blood glucose sensor such that the second blood glucose data is measured earlier than the default period. Outputting the first blood glucose data to the user may include outputting a notification related to squeeze noise to the user.

[0022] Furthermore, in an example embodiment of this disclosure, the blood glucose data management method may further include determining whether the number of consecutive blood glucose data whose output has been paused corresponds to a first reference number, and if the number of consecutive blood glucose data whose output has been paused corresponds to the first reference number, disconnecting the connection with the blood glucose sensor.

[0023] Furthermore, in an example embodiment of this disclosure, the blood glucose data management method may further include: identifying a new blood glucose sensor that replaces the blood glucose sensor when the connection with the blood glucose sensor is disconnected; identifying blood glucose data based on the new blood glucose sensor; identifying estimated blood glucose data for at least a portion of continuous blood glucose data whose output has been paused by performing interpolation or extrapolation using the identified blood glucose data based on the new blood glucose sensor; and outputting the estimated blood glucose data to the user.

[0024] Furthermore, in an exemplary embodiment of this disclosure, the blood glucose data management method may also include outputting a notification to the user regarding sensor detachment.

[0025] Furthermore, in an example embodiment of this disclosure, outputting a notification to the user regarding sensor detachment may include outputting a terminal that identifies the user's caregiver and outputting a notification related to sensor detachment to the caregiver's terminal.

[0026] Furthermore, in an exemplary embodiment of this disclosure, the notification regarding sensor detachment may differ from at least a portion of the measurement notification, hypoglycemia notification, and hyperglycemia notification of the blood glucose sensor in terms of volume, vibration intensity, and notification type.

[0027] Furthermore, in an example embodiment of this disclosure, the blood glucose data management method may further include: recognizing a user's request to output a blood glucose graph; deactivating a portion of the blood glucose graph corresponding to the paused output of blood glucose data, the portion including first blood glucose data; and outputting the blood glucose graph to the user, wherein the portion corresponding to the paused output of blood glucose data is deactivated. Deactivation may include at least a portion of the following: blurring of points on the blood glucose graph, unresponsiveness to clicks, and displaying an indication that output is paused.

[0028] According to another aspect, an electronic device is provided, including a processor and a memory storing one or more instructions. The processor is configured to, by executing one or more instructions, identify first blood glucose data based on a blood glucose sensor, identify a validation dataset corresponding to the first blood glucose data, estimate whether at least a portion of the blood glucose sensor has detached from the user's body based on a comparison between a pattern corresponding to the validation dataset and a reference pattern, and, if the estimation indicates detachment has occurred, pause the output of the user's first blood glucose data.

[0029] According to another aspect, a non-transient computer-readable recording medium is provided, on which a program for performing the above-described blood glucose data management method on a computer is recorded.

[0030] Specific details of other example implementation schemes are included in the specific implementation schemes and figures.

[0031] Additional aspects of the example implementation will be set forth in part in the description below, and will be apparent in part from the description, or may be learned through practice of this disclosure. Attached Figure Description

[0032] These and / or other aspects, features, and advantages of this disclosure will become apparent and more readily understood from the following description of exemplary embodiments, taken in conjunction with the accompanying drawings, in which:

[0033] Figure 1 This is a diagram illustrating the interconnection between an electronic device for managing blood glucose data, a blood glucose sensor, a server, and a caregiver terminal according to an example implementation.

[0034] Figure 2This is a flowchart illustrating a blood glucose data management method according to an example implementation scheme;

[0035] Figure 3A This is a diagram illustrating an example of how the patterns in the validation dataset correspond to the first reference pattern;

[0036] Figure 3B This is a diagram illustrating another example of how the pattern of the validation dataset corresponds to the first reference pattern;

[0037] Figure 3C This is a diagram illustrating an example where the pattern of the validation dataset does not correspond to the first reference pattern;

[0038] Figure 4A This is a diagram illustrating an example of displaying a notification related to sensor detachment via a notification window according to an example implementation;

[0039] Figure 4B This is a diagram illustrating an example of displaying a notification related to sensor detachment via a banner, according to an example implementation.

[0040] Figure 5A This is a diagram illustrating another example of displaying a notification related to sensor detachment via a notification window according to an example implementation;

[0041] Figure 5B This is a diagram illustrating another example of a notification related to sensor detachment displayed via a banner, according to an example implementation scheme;

[0042] Figure 6A This is an example graph of a blood glucose chart based on an example implementation, where the output of blood glucose data that has been paused is deactivated;

[0043] Figure 6B This is an example diagram illustrating the user interface (UI) when blood glucose data, whose output has been paused and therefore deactivated, is clicked according to the example implementation; and

[0044] Figure 7 This is a block diagram of an electronic device based on an example implementation. Detailed Implementation

[0045] The terminology used in the example embodiments has been selected as the most general terms currently used in considering the functionality of this disclosure; however, these terms may vary depending on the intent of those skilled in the art, conventions, the emergence of new technologies, etc. Additionally, in some cases, there are terms arbitrarily chosen by the applicant, and in such cases, their meanings will be described in detail in the corresponding description. Therefore, the terms used in this disclosure should be defined based on their meaning and the entirety of this disclosure, and not merely on their names.

[0046] Throughout the specification, when a part is stated to "comprise" or "include" a component, it means that other components may also be included, and other components are not excluded unless otherwise stated.

[0047] The expression "at least one of A, B and C" can indicate the following meanings, including: only A; only B; only C; both A and B together; both A and C together; both B and C together; or all three of A, B and C together.

[0048] The term "terminal" as used in this article can be implemented as a computer or portable terminal that can access servers or other terminals via a network. Here, a computer includes, for example, a laptop, desktop computer, or laptop computer equipped with a web browser, and a portable terminal is, for example, a wireless communication device that ensures portability and mobility. It can include all kinds of handheld device-based wireless communication devices, including communication-based terminals such as IMT (International Mobile Telecommunications), CDMA (Code Division Multiple Access), W-CDMA (W-Code Division Multiple Access), LTE (Long Term Evolution), smartphones, tablet PCs, etc.

[0049] In the following, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings, enabling those skilled in the art to readily implement them. However, the present disclosure can be implemented in a variety of different forms and is not limited to the exemplary embodiments described herein.

[0050] In the following, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings.

[0051] Figure 1 This is a diagram illustrating the interconnection between an electronic device for managing blood glucose data, a blood glucose sensor, a server, and a caregiver terminal, according to an example implementation.

[0052] refer to Figure 1 The electronic device 100 can operate in conjunction with the blood glucose sensor 200, the server 300, and the caregiver terminal 400. Meanwhile, Figure 1 Only components relevant to this example implementation are shown. Therefore, those skilled in the art, in addition to those related to this example implementation, will understand that... Figure 1 In addition to the components shown, other general-purpose components may also be included.

[0053] Electronic device 100 is a device for configuring and providing various information. Electronic device 100 can provide configuration information as a webpage or application screen, or in a form that can be displayed as a webpage or application screen on a receiving terminal. According to the example embodiment, electronic device 100 may correspond to a user-carried terminal, such as a smartphone or tablet, but is not limited thereto. Electronic device 100 can be connected to blood glucose sensor 200 via wired or wireless communication methods. It can also be connected to server 300 and caregiver terminal 400 via a network.

[0054] A blood glucose sensor 200 can be percutaneously inserted into a user's body to measure the glucose concentration in the user's interstitial fluid. For example, the blood glucose sensor 200 may include a microelectrode and an enzyme layer inserted through the skin into the user's body, which can indirectly measure the glucose concentration in the interstitial fluid via the microelectrode by detecting the electron flow (i.e., current value) generated by the chemical reaction of glucose oxidase occurring in the enzyme layer as biological data. However, the blood glucose sensor is not limited to operating on this principle. Any sensor method capable of measuring the glucose concentration in the interstitial fluid can be applied to the blood glucose sensor 200 of this disclosure. When the blood glucose sensor 200 operates as described above, the blood glucose sensor 200 can be connected to the electronic device 100 via the wired or wireless communication methods described above and periodically transmit the measured biological data to the electronic device 100. According to an example embodiment, the electronic device 100 can calculate blood glucose data by processing such biological data. For example, the electronic device 100 can perform calculations based on, but is not limited to, a mapping relationship between the biological data and the blood glucose data. In the following description, detachment of at least a portion of the blood glucose sensor 200 may mean that all or part of the portion that must be percutaneously inserted into the user's body has been detached and exposed to air.

[0055] According to an exemplary embodiment, the blood glucose sensor 200 bundles multiple biometric data measurements (i.e., multiple current values) taken at short intervals and transmits them as values ​​representing larger intervals covering the short intervals to the electronic device 100. The electronic device 100 can then determine blood glucose data for the larger intervals based on the transmitted values. For example, the blood glucose sensor 200 may measure biometric data every 10 seconds and transmit the biometric data measured every 10 seconds to the electronic device 100, which is grouped at 5-minute intervals. The electronic device 100 may calculate blood glucose data for the corresponding 5-minute period based on the average of the biometric data measured every 10 seconds or various other representative values ​​determined by other methods. Of course, the method of measuring blood glucose data is not limited to those described above. For example, blood glucose data can be measured by first measuring the current value, then calculating the blood glucose data internally within the blood glucose sensor 200 itself, and subsequently transmitting it to the electronic device 100. This disclosure can cover various methods by which the electronic device 100 measures blood glucose data based on the blood glucose sensor 200, in addition to the methods described above.

[0056] Server 300 is connected to electronic device 100 via a network, enabling it to perform operations such as long-term backup of user blood glucose data collected by electronic device 100 and providing backup of historical blood glucose data to electronic device 100.

[0057] The caregiver terminal 400 is a terminal belonging to a person designated as the user's caregiver. It can correspond to a personal mobile device, such as a smartphone or tablet, but is not limited to these. The caregiver terminal 400 can be connected to the electronic device 100 and the server 300 via a network.

[0058] Below, a method for managing blood glucose data according to an example embodiment of this disclosure is described.

[0059] Figure 2 This is a flowchart illustrating a blood glucose data management method according to an example implementation.

[0060] In operation S210, electronic device 100 can identify first blood glucose data based on blood glucose sensor 200. In operation S220, electronic device 100 can identify a validation dataset corresponding to the first blood glucose data. In operation S230, electronic device 100 can estimate whether at least a portion of blood glucose sensor 200 has detached from the user's body based on a comparison between the pattern corresponding to the validation dataset and a reference pattern. In operation S240, if detachment is estimated to have occurred, electronic device 100 can pause the output of the first blood glucose data to the user. Each operation is described in detail below.

[0061] First, the electronic device 100 can identify first blood glucose data based on the blood glucose sensor 200. As described above, the blood glucose sensor 200 is percutaneously inserted into the user's body and can periodically measure the user's biometric data. An example of biometric data is the current value flowing through the microelectrode inserted percutaneously into the user's body. When measuring such biometric data, the electronic device 100 can calculate blood glucose data by processing the biometric data. For example, the electronic device 100 can perform calculations based on a mapping relationship between biometric data and blood glucose data, but is not limited thereto. According to an example embodiment, the first blood glucose data may correspond to data measured by the blood glucose sensor 200 as described above at the next check cycle of blood glucose data checked based on the biometric data periodically measured by the blood glucose sensor 200. For example, the first blood glucose data may correspond to the most recent blood glucose data based on the blood glucose data periodically measured by the blood glucose sensor 200. According to another example embodiment, the first blood glucose data may correspond to any of the periodically measured past blood glucose data. However, for convenience in the following description, the description will be based on the foregoing example embodiment, i.e., the example embodiment in which the first blood glucose data corresponds to the most recent blood glucose data. However, the following description also applies when the first blood glucose data corresponds to any past blood glucose data.

[0062] According to an example implementation, electronic device 100 can identify a validation dataset corresponding to a first blood glucose data point. The validation dataset can correspond to a set containing a number of consecutive blood glucose data points, which can identify patterns within the blood glucose data. The validation dataset corresponding to the first blood glucose data can include the time-series aligned first blood glucose data point and at least one previous blood glucose data point having a sequential blood glucose measurement order. For example, if blood glucose data is set to be measured at 5-minute intervals, the validation dataset for the first blood glucose data measured at 13:30 on January 1, 2025, can include, along with the first blood glucose data, time-series aligned blood glucose data measured at 13:25, 13:20, and 13:15 on the same day. The number of blood glucose data points included in the validation dataset can be statically or dynamically set. An example implementation for dynamically setting the number of blood glucose data points to be included in the validation dataset is described below.

[0063] According to the example implementation, the electronic device 100 can set the amount of data in the verification dataset to be inversely proportional to the magnitude of the blood glucose value indicated by the first blood glucose data. For example, when the magnitude of the blood glucose value indicated by the first blood glucose data is small, the electronic device 100 can set the amount of data included in the verification dataset to be larger. This example implementation has the advantage that when the magnitude of the blood glucose value indicated by the first blood glucose data is small, it allows for a slightly conservative and cautious approach based on more data to distinguish it from actual hypoglycemia.

[0064] According to the example implementation, in addition to multiple blood glucose data sets, the validation dataset may also include error history information, operational history information, and specification information of the blood glucose sensor 200. Based on such information, the example implementation can also be applied, where certain thresholds for each reference mode, which will be described later, are adjusted.

[0065] According to an example implementation, electronic device 100 can identify multiple blood glucose data points in a time-series arrangement included in a verification dataset. Furthermore, electronic device 100 can determine whether a pattern of the multiple blood glucose data points corresponds to at least one of a first reference pattern and a second reference pattern included in a reference pattern. If the pattern of the multiple blood glucose data points corresponds to at least one of the first reference pattern and the second reference pattern, electronic device 100 can estimate that at least a portion of the blood glucose sensor 200 has detached. The first reference pattern may relate to the relative magnitudes between the blood glucose data points, and the second reference pattern may relate to the absolute magnitudes of the blood glucose data points. First, the first reference pattern will be described.

[0066] For example, if part of the blood glucose sensor detaches, there may be no response due to insufficient glucose in the air, or current may not flow through the microelectrode because the resistance of air is much higher than that of interstitial fluid, resulting in a measurement of blood glucose data that is too low. Based on such a situation, according to an example embodiment, the first reference mode may include a mode in which, among multiple blood glucose data, subsequent blood glucose data in a sequential blood glucose measurement sequence decreases by at least a first threshold compared to previous blood glucose data. An example of the first threshold may correspond to a decrease in blood glucose that is not typically observed even in diabetic patients, such as a value of approximately 150 mg / dL, but is not limited to such values.

[0067] For example, if a portion of the blood glucose sensor detaches, it can be predicted, as previously stated, that a measurement of excessively low blood glucose data will not be followed by a subsequent measurement of rising blood glucose data. Based on this observation, according to an exemplary embodiment, the first reference mode may further include a mode in which the slope between two blood glucose data points measured in a sequence later than the previous blood glucose data is 0 or less. For example, the first reference mode may also include a mode in which blood glucose data no longer rises after a sharp drop.

[0068] The following is for reference. Figure 3A , Figure 3B and Figure 3C Describe examples in the validation dataset that correspond to the first reference pattern and examples that do not.

[0069] Figure 3A This is a diagram illustrating an example of how the pattern of the validation dataset corresponds to the first reference pattern.

[0070] refer to Figure 3A We can see that blood glucose data 311 corresponds to an example of 174 mg / dL, but the next sequence shows the first blood glucose data 312 measured at 21 mg / dL. In this case, it can be confirmed that the pattern corresponding to the validation dataset matches the first reference pattern.

[0071] Figure 3B This is a diagram showing another example of how the pattern of the validation dataset corresponds to the first reference pattern.

[0072] refer to Figure 3B Blood glucose data 321 corresponds to 166 mg / dL prior to measurement at 11 mg / dL (322). Subsequently, blood glucose data 323, 324, and 325 continue to show a pattern of no increase at 10 mg / dL, 8 mg / dL, and 8 mg / dL, and the first blood glucose data 326 is still measured at 6 mg / dL. In this case, since the blood glucose data no longer increases after a sharp drop, it can be confirmed that the pattern corresponding to the validation dataset corresponds to the first reference pattern.

[0073] Figure 3C This is a diagram illustrating an example where the pattern of the validation dataset does not correspond to the first reference pattern.

[0074] refer to Figure 3C The example where the first blood glucose level (331) has increased to 11 mg / dL compared to the previous level is roughly similar. Figure 3B However, there are slight differences. In this case, because the blood glucose data rose again after a sharp drop, it can be confirmed that the pattern corresponding to the validation dataset does not match the first reference pattern.

[0075] Next, a second reference mode will be described. According to an example implementation, the second reference mode may include a mode in which at least one of a plurality of blood glucose data is below a second threshold. Here, the second threshold may correspond to a low blood glucose value that is rarely measured even in diabetic patients, such as approximately 30 mg / dL, but is not limited to that value.

[0076] According to the example implementation, the second reference mode may also include a mode associated with the moment when at least one blood glucose data is measured below a second threshold. For example, the second reference mode may also include a mode where the moment when at least one blood glucose data is measured below the second threshold falls within a predetermined time range calculated from the moment the hypoglycemia alarm is issued to the user. When a hypoglycemia alarm is issued, the user will obviously take countermeasures, such as eating to raise blood glucose to prevent hypoglycemic shock. However, if another blood glucose data drops below the second threshold within the predetermined time range calculated from the time the hypoglycemia alarm was issued, it may be more reasonable to infer that the sensor has partially disengaged, rather than that the user's blood glucose has actually plummeted. This insight forms the basis for setting the described second reference mode. Here, the predetermined time range can be appropriately set as the time interval at which blood glucose is not expected to drop sharply after the user takes countermeasures.

[0077] Alternatively, the second reference mode may also include a mode in which a reference number of blood glucose data points are measured below the second threshold, starting with a first blood glucose data point measured below the second threshold. This could also be based on the observation that, as previously mentioned, when a hypoglycemic alarm occurs, the user will take countermeasures to raise their blood glucose. Therefore, when blood glucose remains persistently very low, it may be more reasonable to assume that the sensor has partially disengaged rather than inferring an actual hypoglycemic state. In this case, considering the measurement cycle, the reference number could be set to correspond to the time during which it is predicted the user will necessarily take countermeasures to avoid hypoglycemic shock.

[0078] According to the example implementation, electronic device 100 can adjust at least one threshold related to a reference mode based on the user's medical history information. That is, taking into account the user's medical history related to their disease, electronic device 100 can adjust, for example, a first threshold related to a first reference mode or a second threshold related to a second reference mode. Each example will now be described in detail.

[0079] For example, in patients with type 1 diabetes, the body does not produce insulin at all, resulting in greater fluctuations in blood glucose levels compared to other types of diabetes. Therefore, patients with type 1 diabetes may experience rapid drops in blood glucose. In this situation, even if blood glucose data falls significantly outside the normal range, care must be taken to avoid interpreting it as sensor detachment rather than hypoglycemia. At this point, the electronic device 100 can identify medical history information indicating that the user has type 1 diabetes. In this case, the electronic device 100 can adjust a first threshold of a first reference pattern related to the amount of decrease in subsequent blood glucose data relative to previous blood glucose data in the blood glucose measurement sequence to be increased. Through such an example implementation, sensor detachment estimation for patients with type 1 diabetes can be conservatively performed.

[0080] As another example, for patients who have experienced hypoglycemic shock, similar caution is needed to estimate sensor disengagement rather than hypoglycemia, even if the blood glucose data is slightly low. Therefore, the electronic device 100 can identify medical history information indicating a user's history of hypoglycemic shock. In this case, the electronic device 100 can adjust a second threshold of a second reference pattern, related to the size of at least one blood glucose data point among multiple blood glucose data points included in the validation dataset, to decrease. With such an example implementation, sensor disengagement estimation for patients who have experienced hypoglycemic shock can be performed conservatively. The above description regarding threshold adjustment is merely illustrative, and the scope of this disclosure is not limited to the above examples.

[0081] According to the example implementation, the electronic device 100 can also estimate the disengagement of at least a portion of the blood glucose sensor 200 based on a third reference mode. Specifically, the electronic device 100 can perform a stabilization operation after the blood glucose sensor 200 is initially inserted percutaneously into the user's body. During such a stabilization period, the current value of the biological data measured by the blood glucose sensor 200 may typically fluctuate, meaning that there can be large deviations between values ​​measured in consecutive measurement sequences. Therefore, the blood glucose data that can be determined based on these current values ​​may also fluctuate. Therefore, as at least part of the stabilization operation, the electronic device 100 may perform an operation of waiting until the current value no longer fluctuates, rather than performing a process of checking the blood glucose data based on such fluctuating current values ​​or outputting the blood glucose data. Therefore, when the electronic device 100 is performing the stabilization operation and the blood glucose sensor 200 is correctly inserted without disengagement, it is possible to predict that the current value will fluctuate.

[0082] Based on this, according to the example implementation, when it is confirmed that the electronic device 100 is performing stable operation, the electronic device 100 can compare the pattern of multiple blood glucose data included in the verification dataset with a third reference pattern corresponding to stable operation. Here, the third reference pattern can include a pattern where the average change between two consecutive blood glucose measurements is equal to or greater than a third threshold. For example, the electronic device 100 can identify multiple blood glucose data included in the verification dataset, calculate the average change between two consecutive data, and then determine whether the average value is equal to or greater than the third threshold. If the average value is equal to or greater than the third threshold, the electronic device 100 can confirm that the pattern of the multiple blood glucose data included in the verification dataset corresponds to the third reference pattern and infer that at least a portion of the blood glucose sensor is not dislodged and is correctly inserted into the user's body. Conversely, if the average value is below the third threshold, the electronic device 100 can confirm that the pattern of the multiple blood glucose data included in the verification dataset does not correspond to the third reference pattern. In this case, according to the example implementation, since no pattern of blood glucose data (which should be irregular if the blood glucose sensor 200 is properly inserted) is found to be irregular, the electronic device 100 can infer that at least a portion of the blood glucose sensor 200 has dislodged.

[0083] According to the example implementation, the electronic device 100 can estimate sensor detachment by confirming that the pattern of the verification dataset corresponding to the first blood glucose data corresponds to at least one of a first reference pattern or a second reference pattern, or by confirming that it does not correspond to a third reference pattern, and then pause the output of the first blood glucose data to the user. That is, the measured blood glucose data is output to the user essentially immediately, but the estimation that blood glucose data has been measured from a detached sensor may cause its output to the user to be paused. Here, output pause includes all actions that allow the user to view the complete blood glucose data later than the typical time for checking general blood glucose data. For example, it may allow viewing only a portion of blood glucose data up to a specific time point, prohibit viewing any blood glucose data before that time point, allow viewing only the range of blood glucose values, display the data in a faded manner on a graph so that the exact value is not discernible, use different icons to indicate that the data is presumably measured from a detached sensor, or only display the upward or downward trend of the data. Specific examples of such output pause actions, and several actions that can be linked to them, are described below.

[0084] First, when the output of the first blood glucose data is paused due to the detachment of at least a portion of the blood glucose sensor 200, the electronic device 100 can output a notification to the user related to the sensor detachment. The notification related to sensor detachment may include a message prompting the user to carefully check the sensor, as it may have become detached. (Reference) Figure 4A and Figure 4B as well as Figure 5A and Figure 5B Here are some examples of this type of notification.

[0085] Figure 4A This is a diagram illustrating an example of displaying a notification related to sensor detachment via a notification window according to an example implementation.

[0086] refer to Figure 4A Here is an example of a notification related to sensor detachment displayed via a notification window on a display device operated in conjunction with electronic device 100. The notification related to sensor detachment emphasizes the message "The sensor may have detached" by displaying it in a relatively large font size. Below, the message "Please check that the sensor is inserted correctly" can be displayed and highlighted in a relatively small font size. Figure 4A In the case of delivering a notification related to sensor detachment in the form shown, according to an exemplary embodiment, it may correspond to a situation where a user is using an application related to the blood glucose sensor 200 via electronic device 100.

[0087] Figure 4B This is a diagram illustrating an example of a notification related to sensor detachment displayed via a banner, according to an example implementation.

[0088] refer to Figure 4B An example of a notification related to sensor detachment can be seen displayed via a banner on a display device operated in conjunction with electronic device 100. For example... Figure 4B As shown, notifications related to sensor detachment provided via banners can contain only a concise message, such as "Sensor detachment needs to be checked," which is similar to... Figure 4A The notifications provided across a large area of ​​the screen on the display device are different. When using... Figure 4B When a sensor detachment notification is delivered in the form shown, according to an exemplary implementation, this may correspond to a situation where the user has not used the application associated with the blood glucose sensor 200 by the electronic device 100.

[0089] Figure 5A This is a diagram illustrating another example of displaying a notification related to sensor detachment via a notification window, according to an example implementation.

[0090] refer to Figure 5A Here is another example of a notification related to sensor detachment displayed via a notification window on a display device operated by the integrated electronic device 100. This is similar to... Figure 4A However, they differ in some aspects. Figure 5A In the case of, as with Figure 4AThe difference can also include messages informing users that they will need to perform a blood glucose self-test if they wish to check their blood glucose levels, and messages asking them to check if the sensor is functioning correctly because an abnormal sensor signal has been detected. Here, blood glucose self-tests include various methods by which users can directly measure their own blood glucose without using a blood glucose sensor 200. One example is self-monitoring using a blood glucose (SMBG) method with a lancet and a blood glucose meter, but it is not limited to this.

[0091] Figure 5B This is another example of a notification related to sensor detachment displayed via a banner, according to an example implementation.

[0092] Figure 5B Another example of a notification related to sensor detachment displayed via a banner on a display device operated in conjunction with electronic device 100 is also shown, similar to Figure 4B But in some ways different Figure 4B . Specifically, Figure 5B Corresponding to Figure 5A Examples in, and similar to Figure 5A It can include a message informing users that they must perform a self-test for blood sugar if they wish to check their blood sugar levels. When using... Figure 5B When a sensor detachment notification is delivered in the form shown, according to an exemplary implementation, this may correspond to a situation where the user has not used the application associated with the blood glucose sensor 200 by the electronic device 100.

[0093] Such notifications can also be sent to the caregiver terminal 400 configured for the user. Notifications for the caregiver terminal 400 can also be displayed via a notification window or banner on a display device operating in conjunction with the caregiver terminal 400, similar to... Figure 4A and Figure 4B as well as Figure 5A and Figure 5B In this case, the message can also be partially modified to suit the needs of the caregiver operating the caregiver terminal 400, or additional messages can be included. For example, if it is estimated that the blood glucose sensor 200 has been out of service for an extended period of time, the notification related to the sensor being out of service sent to the caregiver terminal 400 may also include a message about the estimated duration of the outage of the blood glucose sensor 200 and a message prompting the caregiver to check it.

[0094] According to an exemplary implementation, regarding at least some of the various parameters associated with the notification (such as volume, vibration intensity, and notification type), a notification about sensor detachment may differ from a measurement notification output whenever the blood glucose sensor 200 measures blood glucose, a low blood glucose notification output when low blood glucose is detected, a high blood glucose notification output when high blood glucose is detected, a rapid change notification output when blood glucose fluctuates rapidly, and an abnormality notification output when other sensor anomalies are detected. For example, the volume or vibration intensity may be relatively low compared to an emergency alarm such as a low blood glucose or rapid change notification, while the volume or vibration intensity may be relatively high compared to a routine alarm such as a measurement notification. Furthermore, regarding the notification type, a customized melody or vibration pattern can be specifically applied to a notification about sensor detachment, enabling the user to immediately recognize that the notification is related to sensor detachment.

[0095] According to the example implementation, in the presence of paused output of blood glucose data, a request to output a blood glucose graph can be identified from the user. Specifically, the request for outputting a blood glucose graph can be identified via user input through an application associated with the blood glucose sensor 200 operating on the electronic device 100. In this case, the electronic device 100 can deactivate the portion of the blood glucose graph corresponding to the blood glucose data whose output has been paused. As described above, if the output of first blood glucose data is paused, the deactivated portion may include the portion corresponding to the first blood glucose data. After such processing, the electronic device 100 can output a blood glucose graph to a display device linked to the electronic device 100, wherein the portion corresponding to the paused output of blood glucose data is deactivated. According to the example implementation, the blood glucose graph can be a graph in which the horizontal axis corresponds to the time axis, the vertical axis corresponds to the magnitude of the blood glucose value, and each point on the graph represents each blood glucose data measured at a specific time point.

[0096] Here, according to the example implementation, the deactivation process may include at least some of the following: blurring of points on the graph, non-responsiveness to clicks, and display processing related to output pause indications. For example, blurring may include processing for displaying points corresponding to output pause data in a blurred state on the graph. For example, non-responsiveness to clicks may include processing to ensure that clicking an output pause point does not display additional information, unlike regular points that display detailed blood glucose data when clicked. For example, display processing related to output pause indications may include displaying a message indicating that these points correspond to output pause data and have therefore undergone blurring or non-responsiveness processing. Furthermore, according to the example implementation, the deactivation process may include displaying blood glucose data using an icon different from other points on the graph. For example, different icons may be used to display blood glucose data assumed not to have been obtained from a detached sensor and blood glucose data assumed to have been obtained from a detached sensor on the blood glucose graph, thereby achieving a clear distinction between the two. As an additional example, the deactivation process may include processing for preventing any UI / UX feedback from being displayed, even when a click is input to the coordinates on the graph corresponding to the output pause data. When this deactivation process is applied, the electronic device 100 may display appropriate feedback when a click is made on the coordinate input on the graph corresponding to data that is not paused for output, but may not display feedback for data that is paused for output. This allows the user to recognize that a click is not possible for data that is paused for output. The deactivation process is not limited to the example above and may cover any process that allows the user to view complete blood glucose data later than the time when they would normally view normal blood glucose data to obtain data that is paused for output.

[0097] Such a blood glucose graph can also be requested via the caregiver terminal 400. In this case, the caregiver terminal 400 can obtain overall blood glucose data through a link with the server 200 or the electronic device 100, and based on this, display the blood glucose graph on a display device linked to the caregiver terminal 400. At this time, if there is blood glucose data with paused output, that part can be displayed as inactive, similar to the method described above.

[0098] refer to Figure 6A and Figure 6B Here's an example of a blood glucose graph where the output of paused blood glucose data has been deactivated.

[0099] Figure 6A This is an example graph of a blood glucose chart based on an example implementation, where the output of blood glucose data that has been paused is deactivated.

[0100] refer to Figure 6AIt can be observed that the point corresponding to value 501 (which is assumed to be the blood glucose data measured when the blood glucose sensor 200 is detached) is displayed more faintly compared to other points on the blood glucose graph. Therefore, value 501, which is assumed to be the blood glucose data measured when the blood glucose sensor 200 is detached, can be displayed on the blood glucose graph to distinguish it from other points.

[0101] Figure 6B This is an example diagram showing the UI when blood glucose data, which has been paused and therefore deactivated, is clicked according to the example implementation.

[0102] refer to Figure 6B As can be seen when the user selects the aforementioned Figure 6A An exemplary notification 502 can be displayed when the value is 501, which is assumed to be blood glucose data measured when the blood glucose sensor 200 is detached. Figure 6B As shown, clearly indicating that the value may have been measured when the sensor was detached can enhance the user experience.

[0103] The above examples describe a scenario where a user or caregiver requests information related to blood glucose in a two-dimensional blood glucose graph format. However, this is merely an example, and blood glucose-related information can be requested in formats other than graphs, such as tabular logs, distribution charts, radial charts, calendar maps, cumulative area charts, box plots, and other formats. It is not limited to the examples listed above. Electronic device 100 can provide blood glucose-related information to users or caregivers in various formats. Regardless of the format in which the blood glucose-related information is provided, various processing methods (such as deactivation processing based on the output pause described above) can be similarly applied to blood glucose data assumed to have been measured after sensor detachment, and these are also considered to be included within the scope of this disclosure.

[0104] According to the example implementation, the electronic device 100 can estimate sensor detachment by confirming that the pattern of the verification dataset corresponding to the first blood glucose data corresponds to at least one of a first reference pattern or a second reference pattern, and then check the second blood glucose data based on the blood glucose sensor 200 in the next measurement cycle. If the second blood glucose data is equal to or less than the first blood glucose data, the electronic device 100 can compare the pattern of the verification dataset corresponding to the second blood glucose data with the first and second reference patterns to re-estimate whether the sensor is detached. However, if the second blood glucose data is greater than the first blood glucose data, the electronic device 100 can confirm that the first blood glucose data was not measured while the sensor was detached. Specifically, as described above, if the blood glucose sensor 200 has actually detached, it can be assumed that the blood glucose data will not rise again. Therefore, when the second blood glucose data is larger than the first blood glucose data, it can be assumed that the blood glucose sensor 200 has not actually detached. From this perspective, the electronic device 100 can assume that the first blood glucose data was not measured while the sensor was detached, and therefore can release the pause in outputting the first blood glucose data. Therefore, the electronic device 100 can output the first blood glucose data to the user normally. That is, it can release the deactivation process applied to the blood glucose graph and display the blood glucose data the same as regular points.

[0105] According to the example implementation, a squeezing noise-related flag can be selectively set for data whose output is paused (such as first blood glucose data). For example, since applying pressure to the blood glucose sensor 200 can sometimes result in relatively low measurements, a squeezing noise-related flag can be set for data suspected of having low values ​​due to this problem. Such a squeezing noise flag can be set based on data from a pressure sensor mounted next to the blood glucose sensor 200, or for data collected during periods when squeezing occurs frequently due to throwing and turning during sleep. Alternatively, the example implementation is also possible in which a squeezing noise-related flag is set by default for all data whose output is paused.

[0106] If it is confirmed that a flag related to squeeze noise has been set for the first blood glucose data, the electronic device 100 can control the blood glucose sensor 200 to measure the second blood glucose data earlier than the default cycle. That is, if the default cycle for measuring blood glucose data is 5 minutes, the electronic device 100 can control the blood glucose sensor 200 to measure the second blood glucose data again in just 1 minute. Since the pressure applied to the blood glucose sensor 200 is usually released quickly, the second blood glucose data will be measured normally, i.e., higher than the first blood glucose data that was measured as low due to squeeze noise. In this case, the electronic device 100 can release the output pause of the first blood glucose data, but output a notification to the user including a message indicating that the first blood glucose data was assumed to be low due to squeeze noise. Alternatively, instead of the first blood glucose data, the electronic device 100 can selectively perform interpolation or extrapolation using previously measured blood glucose data and the second blood glucose data to output adjusted data to the user. For example, the electronic device 100 can estimate the accurate blood glucose value at the time of the first blood glucose data measurement by performing interpolation based on the second blood glucose data that was measured normally without squeeze noise and the most recent blood glucose data measured before the first blood glucose data measurement, instead of the first blood glucose data. For example, electronic device 100 can estimate the accurate blood glucose value at the time of measurement of the first blood glucose data by performing extrapolation using the most recent blood glucose data measured before the first blood glucose data was measured or multiple blood glucose data measured after the first blood glucose data was measured.

[0107] According to the example implementation, electronic device 100 can determine whether the number of consecutive blood glucose data whose output has been paused corresponds to a first reference number. If the number of consecutive blood glucose data whose output has been paused corresponds to the first reference number, electronic device 100 can disconnect from blood glucose sensor 200. Here, considering the measurement cycle, the first reference number can be appropriately set to reliably estimate the number of data that blood glucose sensor 200 has disconnected from. After disconnecting from blood glucose sensor 200, electronic device 100 can output a notification to the user containing a message requesting the connection of a new blood glucose sensor, since the connection with the blood glucose sensor has been disconnected.

[0108] According to an example implementation, electronic device 100 can identify a new blood glucose sensor that has replaced blood glucose sensor 200 after it has been disconnected from blood glucose sensor 200. Electronic device 100 can then obtain blood glucose data based on the new blood glucose sensor. Electronic device 100 can determine estimated blood glucose data for at least some of the blood glucose data whose output has been paused by performing interpolation or extrapolation using the blood glucose data identified based on the new blood glucose sensor. For example, electronic device 100 can determine estimated blood glucose data for blood glucose data measured at a time point between two points where its output is paused by performing interpolation using the blood glucose data identified based on the new blood glucose sensor and the most recent blood glucose data among the blood glucose data whose output is not paused. Alternatively, electronic device 100 can determine estimated blood glucose data for blood glucose data measured at a time point before the time point measured by the new blood glucose sensor where its output is paused by performing extrapolation using multiple blood glucose data identified based on the new blood glucose sensor. Electronic device 100 can output the thus determined estimated blood glucose data to a user. For example, upon receiving a request to output a blood glucose graph, electronic device 100 can display on the blood glucose graph at least some of the data whose output was paused, replacing them with the estimated blood glucose data as described above, and provide it to the user.

[0109] The various operations of the aforementioned electronic device 100 can also be configured to be performed in conjunction with the server 300. For example, the electronic device 100 can be configured to perform the role of sending data from the blood glucose sensor 200 to the server 300. In this case, the server 300 can perform the various operations described above on behalf of the electronic device 100 based on the data sent. In this case, when a user inputs a request for various information via an application operating on the electronic device 100, the server 300 can send various information determined by the operation to the electronic device 100 for output to the user.

[0110] Figure 7 A block diagram of an electronic device according to an example implementation is shown.

[0111] According to an example implementation, electronic device 100 may include memory 101 and processor 102. Figure 7 The electronic device 100 shown only depicts components relevant to this example embodiment. Therefore, those skilled in the art, in connection with this example embodiment, will understand that, in addition to… Figure 7 In addition to the components shown, other common components may be included. In the example implementation, processor 102 may be included in the controller.

[0112] Processor 102 can control the overall operation of electronic device 100 and process data and signals. Processor 102 may consist of at least one hardware unit. Furthermore, processor 102 may operate based on one or more software modules generated by executing program code stored in memory 101. Processor 102 may include memory, wherein processor 101 can execute program code stored in memory to control the overall operation of electronic device 100 and process data and signals.

[0113] The processor 102 can be configured to identify first blood glucose data based on a blood glucose sensor, identify a validation dataset corresponding to the first blood glucose data, estimate whether at least a portion of the blood glucose sensor has detached from the user's body based on a comparison between a pattern corresponding to the validation dataset and a reference pattern, and if the detachment is estimated to have occurred, pause the output of the first blood glucose data to the user.

[0114] According to the example implementation, electronic device 100 may also include a transceiver for performing wired / wireless communication. Electronic device 100 can use the transceiver to communicate with external electronic devices. The external electronic devices may be terminals or servers. Furthermore, the communication technologies used by the transceiver may include GSM (Global System for Mobile Communications), CDMA (Code Division Multiple Access), LTE (Long Term Evolution), 5G, WLAN (Wireless LAN), Wi-Fi (Wireless Fidelity), Bluetooth™, RFID (Radio Frequency Identification), IrDA (Infrared Data Communication), ZigBee, NFC (Near Field Communication), etc.

[0115] Based on the example implementation, one or more of the following effects can be expected.

[0116] According to the example implementation of this specification, the detachment of the blood glucose sensor can be detected based on the blood glucose pattern.

[0117] Furthermore, according to the example implementation of this specification, blood glucose data obtained from a detached sensor can be managed.

[0118] Furthermore, according to the example implementations in this specification, the user can be notified of the detachment of the blood glucose sensor in various ways.

[0119] The effects of this disclosure are not limited to those described above, and those skilled in the art will clearly understand from the description of the claims other effects not mentioned.

[0120] Electronic devices according to the above example embodiments may include a processor, memory for storing and executing program data, permanent memory such as a disk drive, a communication port for communicating with external devices, a user interface device such as a touch panel, keys, buttons, etc. Methods implemented as software modules or algorithms can be stored as computer-readable code or program instructions executable on a computer-readable recording medium. Here, computer-readable recording media include magnetic storage media (e.g., ROM (Read-Only Memory), RAM (Random Access Memory), floppy disks, hard disks, etc.) and optical reading media (e.g., CD-ROMs and DVDs (Digital Universal Discs)). The computer-readable recording media are distributed across a networked computer system, allowing computer-readable code to be stored and executed in a distributed manner. The medium can be read by a computer, stored in memory, and executed on a processor.

[0121] This example implementation can be represented by functional block configurations and various processing steps. These functional blocks can be implemented using various numbers of hardware and / or software configurations that perform specific functions. For example, the example implementation can employ integrated circuit configurations capable of performing various functions, such as memory, processing, logic, lookup tables, etc., by controlling one or more microprocessors or other control devices. Similar to components that can be implemented using software programming or software elements, this example implementation includes various algorithms implemented using combinations of data structures, procedures, routines, or other programming components, and can be implemented using programming or scripting languages ​​including C, C++, Java, assemblers, etc. Functional aspects can be implemented using algorithms that run on one or more processors. Additionally, this example implementation can employ conventional techniques for at least one of electronic environment setup, signal processing, and data processing. Terms such as “mechanism,” “element,” “device,” and “composition” can be used broadly and are not limited to mechanical and physical configurations. These terms can include the meaning of a series of software routines associated with processors, etc.

[0122] The above example embodiments are merely examples, and other example embodiments may be implemented within the scope of the claims described later.

Claims

1. A method for managing blood glucose data in an electronic device, the method comprising: The first blood glucose data is identified based on a blood glucose sensor. Identify the validation dataset corresponding to the first blood glucose data; Based on a comparison between the pattern corresponding to the validation dataset and the reference pattern, it is estimated whether at least a portion of the blood glucose sensor has detached from the user's body; as well as If a deviation occurs in the estimation, the output of the first blood glucose data is paused.

2. The blood glucose data management method according to claim 1, further comprising, before identifying the first blood glucose data based on the blood glucose sensor: The blood glucose sensor inserted into the user's body periodically checks blood glucose data. The first blood glucose data is measured by the blood glucose sensor during the next measurement cycle of the periodically checked blood glucose data.

3. The blood glucose data management method according to claim 1, wherein, The validation dataset corresponding to the first blood glucose data includes: Identify at least one previous blood glucose data point whose blood glucose measurement sequence is consecutive to the first blood glucose data; and Identify the validation dataset, which includes the first blood glucose data aligned to a time series and the at least one previous blood glucose data.

4. The blood glucose data management method according to claim 1, wherein, Estimating whether at least a portion of the blood glucose sensor has detached includes: Identify multiple time-series aligned blood glucose data points included in the validation dataset; Determine whether the pattern of the plurality of blood glucose data corresponds to at least one of the first reference pattern and the second reference pattern included in the reference pattern; and If the pattern of the plurality of blood glucose data corresponds to at least one of the first reference pattern and the second reference pattern, then it is estimated that at least a portion of the blood glucose sensor has detached.

5. The blood glucose data management method according to claim 4, wherein, The first reference mode includes a mode in which, among two blood glucose data points having a sequential blood glucose measurement order among the plurality of blood glucose data, the subsequent blood glucose data decreases by more than a first threshold compared to the previous blood glucose data.

6. The blood glucose data management method according to claim 5, wherein, The first reference mode further includes a mode in which the slope between two blood glucose data points whose blood glucose measurement order is later than that of the previous blood glucose data among the plurality of blood glucose data is less than 0.

7. The blood glucose data management method according to claim 4, wherein, The second reference mode includes a mode in which at least one of the plurality of blood glucose data is equal to or less than a second threshold.

8. The blood glucose data management method according to claim 1, wherein, Estimating whether at least a portion of the blood glucose sensor has detached includes: Based on the user's medical history information, adjust at least one threshold related to the reference pattern.

9. The blood glucose data management method according to claim 8, wherein, Adjusting at least one threshold associated with the reference mode includes: Identify the medical history information indicating that the user has type 1 diabetes; and In two consecutive blood glucose measurement sequences, the first threshold of the first reference mode, which is related to the amount of decrease in subsequent blood glucose data relative to previous blood glucose data, is adjusted such that the first threshold is increased.

10. The blood glucose data management method according to claim 8, wherein, Adjusting at least one threshold associated with the reference mode includes: Identify the medical history information indicating that the user has a history of hypoglycemic shock; and The second threshold of the second reference mode, which is related to the size of at least one blood glucose data among the plurality of blood glucose data included in the validation dataset, is adjusted such that the second threshold is reduced.

11. The blood glucose data management method according to claim 1, further comprising: Based on the blood glucose sensor, a second blood glucose data that has increased compared to the first blood glucose data is identified; Release the paused output of the first blood glucose data; as well as The first blood glucose data is output to the user normally.

12. The blood glucose data management method according to claim 11, further comprising, before identifying a second blood glucose data that has increased compared to the first blood glucose data based on the blood glucose sensor, and after releasing the pause in outputting the first blood glucose data: Check the squeeze noise-related flags set for the first blood glucose data; The blood glucose sensor is controlled to measure the second blood glucose data earlier than the default cycle, wherein... Outputting the first blood glucose data to the user includes: outputting a notification related to the squeezing noise to the user.

13. The blood glucose data management method according to claim 1, further comprising: Determine whether the number of consecutive blood glucose data whose output has been paused corresponds to the first reference number; as well as If the number of consecutive blood glucose data whose output has been paused corresponds to the first reference number, then disconnect the connection to the blood glucose sensor.

14. The blood glucose data management method according to claim 13 further includes: When the connection with the blood glucose sensor is disconnected, a new blood glucose sensor that replaces the blood glucose sensor is identified; Identify blood glucose data based on the new blood glucose sensor; By performing interpolation or extrapolation using the identified blood glucose data based on the new blood glucose sensor, estimated blood glucose data is identified for at least a portion of the continuous blood glucose data whose output has been paused; and The estimated blood glucose data is output to the user.

15. The blood glucose data management method according to claim 1, further comprising: Output a notification to the user regarding the sensor detachment.

16. The blood glucose data management method according to claim 15, wherein, The notification to the user regarding the sensor detachment includes: The terminal of the caregiver who identifies the user; and A notification related to sensor detachment will be output to the terminal of the user's caregiver.

17. The blood glucose data management method according to claim 15, wherein, The notification regarding sensor detachment differs from at least a portion of the measurement notification, hypoglycemia notification, and hyperglycemia notification of the blood glucose sensor in terms of volume, vibration intensity, and notification type.

18. The blood glucose data management method according to claim 1, further comprising: Recognize the user's request to output a blood glucose graph; The portion of the blood glucose graph corresponding to the paused output of blood glucose data is deactivated, including the first blood glucose data; as well as The blood glucose graph is output to the user, wherein the portion of the blood glucose data corresponding to the paused portion of the output is deactivated. The deactivation includes at least a portion of the following: blurring of points on the blood glucose graph, no response to clicks, and an indication that the output is paused.

19. A non-transient computer-readable recording medium having a program recorded thereon for performing the blood glucose data management method of any one of claims 1 to 18 on a computer.

20. An electronic device for managing blood glucose data, the electronic device comprising: processor; as well as A memory that stores one or more instructions. The processor is configured to execute one or more of the instructions to: The first blood glucose data is identified based on a blood glucose sensor. Identify the validation dataset corresponding to the first blood glucose data; Based on a comparison between the pattern corresponding to the validation dataset and the reference pattern, it is estimated whether at least a portion of the blood glucose sensor has detached from the user's body; as well as If a disconnection is estimated, the output of the user's first blood glucose data is paused.

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