Information processing device, information processing method, and information processing program

Abstract

An information processing device that comprises at least one processor. The processor: acquires measured values measured during laboratory tests and time information that indicates measurement times for the measured values; acquires monitoring values obtained by monitoring biological information that correlates with the measured values; and associates the measured values with the monitoring values for the measurement times indicated by the time information.

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus, an information processing method, and an information processing program.

Background Art

[0002] Conventionally, techniques have been disclosed for monitoring biometric information of a user wearing a wearable terminal such as a smartwatch, and utilizing the monitored biometric information for health checkups, disease prevention, health promotion, and the like. For example, Japanese Patent Application Laid-Open No. 2019-052696 describes performing a diagnosis based on vital data (e.g., pulse rate, blood pressure, body temperature, and respiratory rate) of a patient acquired by a vital band worn on the patient's arm and examination data (e.g., results of a blood test). Also, for example, Japanese Patent Application Laid-Open No. 2019-072467 describes measuring biometric information (e.g., blood glucose) of a user by a biometric information sensor worn on the subject part of the user and correcting the biometric information based on the user's dietary information (e.g., the food ingested, the ingestion amount, and the ingestion time).

[0003] Furthermore, various types of measuring devices are known for measuring blood glucose levels in users such as diabetic patients. For example, one known measuring device for measuring blood glucose levels is one that measures blood glucose levels by pricking the user's fingertip and attaching the blood obtained to a sensor (hereinafter referred to as "self-monitoring blood glucose monitor"). While self-monitoring blood glucose monitors can measure blood glucose levels more accurately, they place a significant burden on the user due to the pain of pricking and running costs, and it is difficult to measure fluctuations in blood glucose levels over time. On the other hand, there are also measuring devices that measure the glucose level of interstitial fluid, which correlates with blood glucose levels, using a sensor attached to the user's skin (hereinafter referred to as "continuous glucose monitoring devices"). Continuous glucose monitoring devices are less accurate than self-monitoring blood glucose monitors because they measure the glucose level of interstitial fluid, but they can measure fluctuations in blood glucose levels over time. For example, Japanese Patent Publication No. 2019-018005 describes a continuous glucose monitoring device that continuously measures the glucose level of interstitial fluid and, based on the glucose level, suggests an appropriate timing for the user to measure their blood glucose level using a self-monitoring blood glucose monitor. [Overview of the project] [Problems that the invention aims to solve]

[0004] Incidentally, when measuring blood glucose levels using a sample test at a specific point in time, such as with the self-monitoring blood glucose device mentioned above, the measurement results may be better or worse than usual. For example, blood glucose levels can fluctuate throughout the day depending on circumstances such as waking up, before going to bed, before meals, after meals, at rest, and during exercise. Furthermore, they may fluctuate compared to other days depending on one's physical condition, activity level, sleep duration, and diet.

[0005] It is believed that using measurement results that are better or worse than normal for health checkups, disease prevention, and health promotion will not lead to accurate judgments. Therefore, in recent years, there has been a growing demand for technology that can obtain appropriate measurement results that take the above-mentioned fluctuations into account.

[0006] This disclosure provides an information processing device, an information processing method, and an information processing program that can obtain appropriate measurement results. [Means for solving the problem]

[0007] A first aspect of the present disclosure is an information processing apparatus comprising at least one processor, the processor acquires a measurement value measured in a specimen test, along with time information indicating the time of measurement of the measurement value, acquires a monitoring value obtained by monitoring biological information correlated with the measurement value, and associates the measurement value with the monitoring value at the time of measurement indicated by the time information.

[0008] A second aspect of this disclosure is that, in the above embodiment, the processor may, after acquiring the measurement values ​​and time information, associate the acquired measurement values ​​with the monitoring values ​​at the time of measurement indicated by the time information.

[0009] A third aspect of the present disclosure is that, in the above embodiment, the processor may acquire monitoring values ​​at multiple points in time and associate the monitoring values ​​at multiple points in time with a measured value, wherein the monitoring values ​​are within a predetermined period that includes at least one of the periods before and after the measurement time indicated by the time information.

[0010] A fourth aspect of the present disclosure is that, in the third aspect described above, the processor may derive a trend in the fluctuation of the monitoring values ​​over a predetermined period including at least one of the time before and after the time of measurement indicated by time information, based on a plurality of monitoring values ​​associated with the measured values, and estimate from the trend in the fluctuation of the monitoring values ​​over a predetermined period including at least one of the time before and after the time of measurement indicated by time information, based on predetermined correlation data where the correlation between the measured values ​​and the monitoring values ​​is predetermined.

[0011] A fifth aspect of this disclosure is, in the fourth aspect described above, the measured value is a blood glucose level, and the monitoring value is at least one of the following, which correlates with the blood glucose level: glucose levels in interstitial fluid, sweat, or saliva, an electrocardiogram signal, blood pressure, and body temperature, and the processor may acquire timing information indicating whether the measurement time is fasting or postprandial, and estimate from the fluctuation trend of the monitoring value a predetermined period including at least one before and after the measurement time indicated by the time information, based on the correlation data corresponding to the timing indicated by the timing information among the correlation data corresponding to fasting and postprandial, respectively.

[0012] A sixth aspect of the present disclosure is, in the fourth or fifth aspect described above, the measured value is a blood glucose level, and the monitoring value is at least one of the following, which correlates with the blood glucose level: glucose levels in interstitial fluid, sweat, or saliva, an electrocardiogram signal, blood pressure, and body temperature, and the processor may acquire meal information indicating the contents of a meal eaten by the person from whom the measured value was taken before the measurement of the measured value, and estimate from the fluctuation trend of the monitoring value a predetermined period including at least one before and after the measurement time indicated by the time information, based on the correlation data corresponding to the contents of the meal indicated by the meal information from among a plurality of correlation data which differ for each contents of the meal.

[0013] A seventh aspect of this disclosure is that, in the fourth to sixth aspects described above, the processor may derive, as a trend of fluctuation in the monitored value, the amplitude of fluctuation in the monitored value over a predetermined period including at least one of the periods before and after the measurement time indicated by the time information.

[0014] An eighth aspect of this disclosure is that, in the fourth to seventh aspects described above, the processor may output comments corresponding to the fluctuation trend of the estimated measured values.

[0015] A ninth aspect of this disclosure is that, in the fourth to eighth aspects described above, the processor may perform a first evaluation of the measured values ​​based on the estimated fluctuation trend of the measured values.

[0016] A tenth aspect of this disclosure is that, in the ninth aspect described above, the processor may output comments corresponding to the first evaluation.

[0017] An eleventh aspect of this disclosure, in the third to ten aspects described above, may derive a trend in the fluctuation of the monitoring values ​​over a predetermined period including at least one before and after the measurement time indicated by time information, based on a plurality of monitoring values ​​associated with the measured value, and perform a first evaluation of the measured value based on the trend in the fluctuation of the monitoring value.

[0018] A twelfth aspect of this disclosure is that, in the above embodiment, the processor may perform a second evaluation of the measurement value based on the deviation between a reference value of the monitoring value at the time of measurement indicated by the time information and the monitoring value at the time of measurement indicated by the time information.

[0019] A thirteenth aspect of this disclosure is that, in the twelfth aspect described above, the processor may output comments corresponding to the second evaluation.

[0020] A fourteenth aspect of this disclosure is that, in the above-described embodiment, the processor may perform a third evaluation of the measurement time indicated by the time information based on the measured value and the associated monitoring value.

[0021] A fifteenth aspect of this disclosure is that, in the fourteenth aspect described above, the processor may output comments corresponding to the third evaluation.

[0022] A sixteenth aspect of this disclosure is that, in the above embodiment, the processor may output a monitoring value associated with the measurement value.

[0023] A 17th aspect of this disclosure is an information processing device comprising at least one processor, the processor acquiring a monitoring value obtained by monitoring biological information having a correlation with a measurement value measured in a specimen test, and recommending measurement of the measurement value when the deviation between the monitoring value and a reference value of the monitoring value is smaller than a predetermined threshold.

[0024] In the 18th aspect of the present disclosure, in the above aspect, the measured value is a blood glucose level, and the monitoring value may be at least one of a glucose value contained in interstitial fluid, sweat, or saliva, an electrocardiogram signal, blood pressure, and body temperature, which has a correlation with the blood glucose level.

[0025] The 19th aspect of the present disclosure is an information processing method, which includes acquiring a measured value measured in a specimen examination together with time information indicating the measurement time point of the measured value, acquiring a monitoring value obtained by monitoring biological information having a correlation with the measured value, and performing a process of associating the measured value with the monitoring value at the measurement time point indicated by the time information.

[0026] The 20th aspect of the present disclosure is an information processing program for causing a computer to execute a process of acquiring a measured value measured in a specimen examination together with time information indicating the measurement time point of the measured value, acquiring a monitoring value obtained by monitoring biological information having a correlation with the measured value, and associating the measured value with the monitoring value at the measurement time point indicated by the time information.

Advantages of the Invention

[0027] According to the above aspect, the information processing apparatus, information processing method, and information processing program of the present disclosure can acquire appropriate measurement results.

Brief Description of the Drawings

[0028] [Figure 1] It is a schematic configuration diagram of an information processing system. [Figure 2] It is a diagram showing an example of a blood glucose level. [Figure 3] It is a diagram showing an example of a glucose value in interstitial fluid. [Figure 4] It is a graph showing the daily variation of the glucose value in interstitial fluid. [Figure 5] It is a block diagram showing an example of the hardware configuration of an information processing apparatus. [Figure 6]This is a block diagram showing an example of the functional configuration of an information processing device. [Figure 7] This figure shows an example of correlation data between blood glucose levels and interstitial fluid glucose levels. [Figure 8] This figure shows an example of correlation data between blood glucose levels and interstitial fluid glucose levels. [Figure 9] This figure shows an example of a screen displayed on a display. [Figure 10] This figure shows an example of a screen displayed on a display. [Figure 11] This is a flowchart showing an example of the first evaluation process. [Figure 12] This figure shows an example of correlation data between postprandial blood glucose levels and interstitial fluid glucose levels. [Figure 13] This figure shows an example of correlation data between blood glucose levels and interstitial fluid glucose levels for each type of meal. [Figure 14] This diagram illustrates the reference values ​​for interstitial fluid glucose levels. [Figure 15] This is a flowchart showing an example of the second evaluation process. [Figure 16] This is a diagram to explain the third evaluation. [Figure 17] This is a flowchart showing an example of the third evaluation process. [Figure 18] This is an example of a figure output as a result of the measurement recommendation process. [Figure 19] A flowchart illustrating an example of recommended measurement procedures. [Modes for carrying out the invention]

[0029] Hereinafter, with reference to the drawings, examples of embodiments for carrying out the technology of this disclosure will be described in detail.

[0030] [First Exemplary Embodiment] Referring to Figure 1, an example of the configuration of the information processing system 1 according to this exemplary embodiment will be described. As shown in Figure 1, the information processing system 1 includes an information processing device 20, a measuring device 3, and a monitoring device 4. The information processing device 20 and the measuring device 3, and the information processing device 20 and the monitoring device 4 are each capable of communicating with each other by wired or wireless communication (e.g., Wi-Fi®, Bluetooth®, and RFID (Radio Frequency Identification)).

[0031] The measuring device 3 is a device for performing sample testing. The measuring device 3 has the function of transmitting the measured values ​​obtained in the sample testing to the information processing device 20 along with time information indicating the measurement time t of the measured values. The measuring device 3 includes a CPU (Central Processing Unit), a non-volatile storage unit realized by a storage medium such as an HDD (Hard Disk Drive), SSD (Solid State Drive), and flash memory, and memory as a temporary storage area. The measuring device 3 also includes input / output units such as a mouse, keyboard, display, and touch panel, and a network I / F (Interface) for wired or wireless communication between the information processing device 20 and an external network (not shown).

[0032] The monitoring device 4 is a device that monitors biological information correlated with measured values ​​over time. The monitoring device 4 has the function of transmitting monitoring values ​​at multiple points in time obtained through the time-series monitoring of biological information to the information processing device 20. "Time-series monitoring of biological information" means monitoring biological information at predetermined time intervals (for example, every 15 minutes) without requiring the user to give monitoring instructions each time. In addition, the monitoring device 4 may monitor biological information in addition to monitoring it over time, if instructed by the user.

[0033] The monitoring device 4 includes a processor, memory as a temporary storage area, sensors, and a network interface for wired or wireless communication with the information processing device 20 and an external network (not shown). These processor, memory, sensors, and network interface may consist of an integrated circuit (ASIC (Application Specific Integrated Circuit)) for monitoring biological information.

[0034] In this exemplary embodiment, we will describe an example in which a device for measuring blood glucose levels by blood test is used as the measuring device 3, and a device for monitoring glucose levels in interstitial fluid that correlates with blood glucose levels over time is used as the monitoring device 4. Blood is an example of a sample, blood glucose level is an example of a measured value, and glucose levels in interstitial fluid (hereinafter referred to as "interstitial fluid glucose levels") are an example of a monitored value.

[0035] As the blood glucose measuring device 3, for example, a portable self-monitoring blood glucose meter can be used, in which the user punctures their own fingertip to obtain blood, which is then applied to a sensor to measure blood glucose levels. Alternatively, a stationary blood glucose meter installed in a hospital or other testing facility can be used, in which medical professionals such as doctors, nurses, and laboratory technicians use blood drawn from the user to perform more precise blood tests than those performed by a self-monitoring blood glucose meter.

[0036] Figure 2 shows an example of blood glucose levels measured by a blood test using the measuring device 3 for a single user, along with the measurement date and time as an example of time information. Figure 2 shows that the blood glucose level measured at measurement time t1, indicated as "November 1, 2020, 6:30 AM," was 87 mg / dL, and the blood glucose level measured at measurement time t2, indicated as "November 1, 2020, 7:30 AM," was 89 mg / dL. In this case, the "measurement date and time" (i.e., the measurement time t of the measured value) refers to the time when blood was collected from the user, and does not refer to the time when the blood test by the measuring device 3 was completed, or the time when the acquisition unit 10 received the blood glucose level (details will be described later), etc.

[0037] As a monitoring device 4 for monitoring interstitial fluid glucose levels, for example, a device having a needle-shaped filament that is inserted under the user's epidermis and measures interstitial fluid glucose levels using the filament can be applied (see, for example, Japanese Patent Publication No. 2016-520379).

[0038] Figure 3 shows an example of interstitial fluid glucose levels monitored at 15-minute intervals by monitoring device 4 for a single user, along with the monitoring date and time. Figure 4 shows a graph of the daily fluctuation of interstitial fluid glucose levels monitored by monitoring device 4. Figure 4 is a graph with time on the horizontal axis and interstitial fluid glucose levels on the vertical axis. Figures 3 and 4 illustrate the time points corresponding to the blood glucose measurement times t1 and t2 shown in Figure 2. Figure 4 illustrates the timing of the user's breakfast, lunch, and dinner.

[0039] Incidentally, as shown in Figure 4, blood glucose levels are known to fluctuate throughout the day depending on the situation, such as before meals, after meals, at rest, during exercise, after waking up, and before going to bed. When measuring blood glucose levels with the measuring device 3, the blood glucose level may be better or worse than normal depending on the measurement time t. It is considered that using blood glucose levels that are better or worse than normal for health checkups, disease prevention, and health promotion will not lead to correct judgments.

[0040] Therefore, the information processing device 20 according to this exemplary embodiment evaluates whether the blood glucose level is at an appropriate value (i.e., whether it is better or worse than usual), based on the interstitial fluid glucose level at the time of blood glucose measurement t, that is, whether the blood glucose level was measured at an appropriate time. Below, an example of the configuration of the information processing device 20 according to this exemplary embodiment will be described.

[0041] First, with reference to Figure 5, an example of the hardware configuration of the information processing device 20 according to this exemplary embodiment will be described. As shown in Figure 5, the information processing device 20 includes a CPU 21, a non-volatile storage unit 22, and a memory 23 as a temporary storage area. The information processing device 20 also includes a display 24 such as a liquid crystal display, an input unit 25 such as a keyboard and mouse, and a network I / F 26 for wired or wireless communication with a measuring device 3, a monitoring device 4, and an external network (not shown). The CPU 21, storage unit 22, memory 23, display 24, input unit 25, and network I / F 26 are connected to each other via a bus 28 such as a system bus and a control bus, enabling the exchange of various types of information.

[0042] The storage unit 22 is implemented by a storage medium such as an HDD, SSD, and flash memory. The storage unit 22 stores the information processing program 27 according to this exemplary embodiment. The CPU 21 reads the information processing program 27 from the storage unit 22, expands it into the memory 23, and executes the expanded information processing program 27. The CPU 21 is an example of the processor of this disclosure. Various computers such as smartphones and personal computers can be used as the information processing device 20.

[0043] Next, with reference to Figure 6, an example of the functional configuration of the information processing device 20 according to this exemplary embodiment will be described. As shown in Figure 6, the information processing device 20 includes an acquisition unit 10, a correspondence unit 12, an evaluation unit 14, and a control unit 16. The CPU 21 executes the information processing program 27, thereby enabling the acquisition unit 10, correspondence unit 12, evaluation unit 14, and control unit 16 to function.

[0044] The acquisition unit 10 acquires blood glucose levels and time information from the measuring device 3 (see Figure 2). The acquisition unit 10 also acquires interstitial fluid glucose levels at multiple time points from the monitoring device 4 (see Figure 3). Specifically, the acquisition unit 10 acquires interstitial fluid glucose levels from the monitoring device 4 at multiple time points, including at least the time point t corresponding to the blood glucose measurement time point t indicated by the time information.

[0045] The correspondence unit 12 associates the blood glucose level acquired by the acquisition unit 10 with the interstitial fluid glucose level at measurement time t indicated by the time information. Specifically, the correspondence unit 12 associates multiple interstitial fluid glucose levels acquired by the acquisition unit 10 at multiple time points within a predetermined period T that includes at least one of the periods before and after measurement time t indicated by the time information with the blood glucose level. "Period T" may be defined, for example, as a predetermined time (e.g., 30 minutes), or as the time until interstitial fluid glucose level monitoring is performed a predetermined number of times (e.g., the time until 5 monitoring sessions are performed).

[0046] In the examples shown in Figures 2 and 3, the correspondence unit 12 associates the blood glucose level "87" at measurement time t1 indicated by the time information with five interstitial fluid glucose levels "83", "84", "85", "86", and "88" during period T1, which includes 30 minutes before and after measurement time t1. Similarly, the correspondence unit 12 associates the blood glucose level "89" at measurement time t2 indicated by the time information with five interstitial fluid glucose levels "88", "84", "86", "100", and "112" during period T2, which includes 30 minutes before and after measurement time t2.

[0047] In other words, the correspondence between blood glucose levels and interstitial fluid glucose levels by the correspondence unit 12 is performed after the acquisition of blood glucose levels and time information. After acquiring blood glucose levels, by correlating the blood glucose level with the interstitial fluid glucose level at the measurement time t in which the blood glucose level was measured, it is possible to evaluate the measured blood glucose level based on the interstitial fluid glucose level.

[0048] The evaluation unit 14 evaluates whether the blood glucose level is at an appropriate value, that is, whether the blood glucose level was measured at an appropriate time, based on the trend of fluctuations in interstitial fluid glucose levels during period T, which is associated with the blood glucose level by the correspondence unit 12. Hereinafter, this evaluation based on the trend of fluctuations in interstitial fluid glucose levels during period T will be referred to as the "first evaluation." The specific method of the first evaluation by the evaluation unit 14 will be described below.

[0049] First, the evaluation unit 14 derives the trend of fluctuation in interstitial fluid glucose levels during period T based on multiple interstitial fluid glucose levels associated with blood glucose levels. The "trend of fluctuation in interstitial fluid glucose levels" is, for example, represented by the amplitude Dx of the interstitial fluid glucose levels during period T (i.e., the difference between the maximum and minimum values ​​of multiple interstitial fluid glucose levels during period T). In the examples in Figures 2 and 3, the evaluation unit 14 derives the amplitude Dx of interstitial fluid glucose levels during period T1 as "83 to 88" and the amplitude Dx of interstitial fluid glucose levels during period T2 as "84 to 112".

[0050] Next, the evaluation unit 14 estimates the trend of fluctuations in blood glucose levels during period T from the trend of fluctuations in interstitial fluid glucose levels derived from predetermined correlation data, which shows the correlation between blood glucose levels and interstitial fluid glucose levels. The correlation data is data that has been generated in advance by performing an analysis based on the actual results of combinations of blood glucose levels and interstitial fluid glucose levels (hereinafter simply referred to as "combinations") at the same point in time, and is stored in advance in the memory unit 22, for example.

[0051] Here, with reference to Figures 7 and 8, we will explain the correlation data between blood glucose levels and interstitial fluid glucose levels. Figure 7 is a scatter plot with interstitial fluid glucose levels on the horizontal axis and blood glucose levels on the vertical axis, plotting the combined results at the same point in time. Figure 7 also shows the approximate line RL, estimated upper limit UL, and estimated lower limit LL, which are generated based on the results of each combined. These approximate line RL, estimated upper limit UL, and estimated lower limit LL represent the correlation data between blood glucose levels and interstitial fluid glucose levels.

[0052] As shown in Figure 7, the combination of interstitial fluid glucose level (X) and blood glucose level (Y) (X, Y) does not necessarily lie on the approximate straight line RL. That is, blood glucose level (Y) exhibits variability with respect to interstitial fluid glucose level (X). The estimated upper limit UL and estimated lower limit LL are defined such that the variable blood glucose level falls between the estimated upper limit UL and estimated lower limit LL (hereinafter referred to as the "estimated interval") with a predetermined probability.

[0053] For example, if the standard deviation of the approximate line RL for blood glucose levels is denoted as σ, then the approximate line RL ± σ are defined as the estimated upper limit UL and estimated lower limit LL, respectively. Assuming that the probability distribution of combinations (X, Y) follows a normal distribution, the combination (X, Y) falls within the estimation interval with a probability of 34% above and below the approximate line RL (a total of 68%). Therefore, assuming that the probability distribution of newly obtained interstitial fluid glucose values ​​and blood glucose values ​​(X, Y) also follows a normal distribution, it can be estimated that 68% of the newly obtained combinations (X, Y) fall within this estimation interval.

[0054] As illustrated in Figure 7 for each plot, it is known that the correlation between blood glucose levels and interstitial fluid glucose levels tends to be stronger (i.e., less variability) as blood glucose and interstitial fluid glucose levels are smaller, and weaker (i.e., more variability) as blood glucose and interstitial fluid glucose levels are larger. Therefore, as shown in Figure 8, it is preferable to change the slopes of the estimated upper limit UL and estimated lower limit LL so that the estimation interval widens as blood glucose and interstitial fluid glucose levels are larger.

[0055] The evaluation unit 14 estimates the trend of blood glucose fluctuations during period T by considering two factors: the fluctuation range Dx of interstitial fluid glucose levels during period T, and the variability of blood glucose levels relative to interstitial fluid glucose levels, which is determined by the estimated upper limit UL and estimated lower limit LL. The "trend of blood glucose fluctuations" is expressed, for example, by the estimated fluctuation range Dy of blood glucose levels during period T (i.e., the difference between the estimated maximum and estimated minimum values ​​of blood glucose levels during period T). For example, the estimated maximum value Ymax of blood glucose levels during period T is estimated by adding the upward variability to the maximum value Xmax of interstitial fluid glucose levels during period T. Similarly, the estimated minimum value Ymin of blood glucose levels during period T is estimated by adding the downward variability to the minimum value Xmin of interstitial fluid glucose levels during period T.

[0056] Specifically, the evaluation unit 14 derives the blood glucose level at the intersection of the minimum interstitial fluid glucose level (83) and the estimated lower limit (LL) during period T1 as the estimated minimum blood glucose level (Ymin), based on the fluctuation range of interstitial fluid glucose levels (83-88). It also derives the blood glucose level at the intersection of the maximum interstitial fluid glucose level (88) and the estimated upper limit (UL) as the estimated maximum blood glucose level (Ymax). Similarly, the evaluation unit 14 derives the blood glucose level at the intersection of the minimum interstitial fluid glucose level (84) and the estimated lower limit (LL) during period T2 as the estimated minimum blood glucose level (Ymin), based on the fluctuation range of interstitial fluid glucose levels (84-112). It also derives the blood glucose level at the intersection of the maximum interstitial fluid glucose level (112) and the estimated upper limit (UL) as the estimated maximum blood glucose level (Ymax). The following explanation assumes that the evaluation unit 14 derived an estimated fluctuation range Dy of blood glucose levels in period T1 as 80-91, and an estimated fluctuation range Dy of blood glucose levels in period T2 as 81-118.

[0057] Next, the evaluation unit 14 performs a first evaluation of the blood glucose level based on the estimated fluctuation trend of the blood glucose level. As mentioned above, blood glucose levels fluctuate throughout the day depending on the situation, such as before meals, after meals, at rest, during exercise, after waking up, and before going to bed. Therefore, if the blood glucose level is measured at a time when it happens to be low, the comment (details below) will be output using a value lower than the actual blood glucose level, reducing its reliability. To this end, the evaluation unit 14 performs a first evaluation of the blood glucose level by estimating whether the blood glucose level is stable during period T. For example, if the estimated fluctuation range Dy of the blood glucose level during period T is below a predetermined threshold, the evaluation unit 14 evaluates that the blood glucose level is stable during period T and is appropriate.

[0058] For example, suppose the threshold is "15". As described above, the estimated fluctuation range Dy of the blood glucose level during period T1, derived by the evaluation unit 14, is "11 (80-91 mg / dL)", which is below the threshold, so the evaluation unit 14 evaluates that the blood glucose level at measurement time t1 is appropriate. On the other hand, the estimated fluctuation range Dy of the blood glucose level during period T2, derived by the evaluation unit 14, is "37 (81-118 mg / dL)", which is above the threshold, so the evaluation unit 14 evaluates that the blood glucose level at measurement time t2 is inappropriate.

[0059] Furthermore, the evaluation unit 14 may perform a first evaluation of blood glucose levels based on the trend of fluctuations in interstitial fluid glucose levels. For example, if the fluctuation range Dx of interstitial fluid glucose levels during period T is greater than or equal to a predetermined threshold, the evaluation unit 14 may evaluate that blood glucose levels are unstable and inappropriate during period T. This is because if the fluctuation range Dx of interstitial fluid glucose levels during period T is too large, it can be estimated that blood glucose levels are inappropriate without even needing to estimate the trend of fluctuations in blood glucose levels.

[0060] The control unit 16 controls the output of interstitial fluid glucose values ​​associated with blood glucose levels by the correspondence unit 12. The control unit 16 also controls the output of at least one of the following: a comment corresponding to the first evaluation by the evaluation unit 14, and a comment corresponding to the estimated trend of blood glucose fluctuations by the evaluation unit 14. "Comments" are messages sent to the user regarding health checkups, disease prevention, and health promotion, and include, for example, notifications of measurement results, as well as advice and warnings based on the measurement results. "Output" can take the form of display on the display 24, voice reading, printing by a printer, or transmission of data to external devices owned by hospitals and testing facilities.

[0061] Figures 9 and 10 show examples of screens displayed on the display 24 as an example of the output format by the control unit 16. Screen D1 shown in Figure 9 relates to the interstitial fluid glucose value and blood glucose value at measurement time t1 (period T1). Screen D2 shown in Figure 10 relates to the interstitial fluid glucose value and blood glucose value at measurement time t2 (period T2). As shown in Figures 9 and 10, the control unit 16 controls the display on the screen the time information (measurement date and time) acquired by the acquisition unit 10, the blood glucose value and interstitial fluid glucose value, and the estimated fluctuation range Dy of the blood glucose value estimated by the evaluation unit 14.

[0062] As described above, the blood glucose level at measurement time t1 is evaluated by the evaluation unit 14 as an appropriate value in the first evaluation. In this case, as shown in Figure 9, the control unit 16 controls the system to display a comment indicating that the blood glucose level is appropriate, such as "※This blood glucose level is a reliable value." On the other hand, the blood glucose level at measurement time t2 is evaluated by the evaluation unit 14 as an inappropriate value in the first evaluation. In this case, as shown in Figure 10, the control unit 16 controls the system to display a comment indicating that the blood glucose level is inappropriate and to encourage retesting, such as "※This blood glucose level is unreliable. We recommend retesting."

[0063] Furthermore, it is generally known that the threshold for a normal diagnosis of diabetes using fasting blood glucose levels is 99 mg / dL or less. Since the blood glucose level at measurement time t1 is 87 mg / dL and the blood glucose level at measurement time t2 is 89 mg / dL, both diagnoses based on these blood glucose levels are normal. In this case, as shown in Figures 9 and 10, the control unit 16 performs control to display a comment indicating the result of the diagnose based on the blood glucose level obtained by the measuring device 3, such as "The diagnosis this time was normal."

[0064] On the other hand, the control unit 16 also outputs comments taking into account the estimated fluctuation range Dy of blood glucose levels estimated by the evaluation unit 14. For example, the maximum value of the estimated fluctuation range Dy of blood glucose levels in period T1 is 91, and even considering the fluctuation range, it can be judged as normal, so as shown in Figure 9, the control unit 16 displays a comment such as, "Your blood glucose is under control..." On the other hand, the maximum value of the estimated fluctuation range Dy of blood glucose levels in period T2 is 118, and considering the fluctuation range, it cannot necessarily be judged as normal, so as shown in Figure 10, the control unit 16 displays a comment such as, "Your diabetes may be worsening..."

[0065] For example, the control unit 16 may store the first evaluation from the previous test in the storage unit 22 and output a comment corresponding to the first evaluation from the previous test. For example, if the first evaluation is deemed inappropriate for both the previous test and the current test, the control unit 16 may output a comment to the user that includes advice and warnings to measure blood glucose levels at an appropriate time. In this case, the criteria for diagnosing diabetes using fasting blood glucose levels may be made stricter.

[0066] For example, if the blood glucose level is deemed inappropriate in the first evaluation, the control unit 16 may output a comment recommending further testing. For example, it may output a comment recommending postprandial blood glucose testing, glucose tolerance testing, and intestinal microbiota testing. It may also automatically reserve the necessary testing equipment for these tests, or automatically make reservations for tests at hospitals and testing facilities.

[0067] For example, if the control unit 16 is evaluated as having an inappropriate blood glucose level in the first evaluation, it may output comments including advice on exercise, sleep, and diet to improve the blood glucose level. This is because, if the first evaluation is inappropriate, even if the diabetes diagnosis based on the blood glucose level and the maximum value of the estimated fluctuation range Dy of the blood glucose level is normal, there is considered to be room for improvement. Examples of such advice include exercising after every meal, combining aerobic and resistance exercises, and getting enough sleep. Other examples include setting meal times, consuming low-GI (Glycemic Index) foods, providing recipes for diabetic patients, and suggesting the order and speed of eating. Meals for diabetic patients may also be automatically delivered.

[0068] For example, if the control unit 16 is evaluated as having an inappropriate blood glucose level in the first evaluation, it may analyze the contents of the meal the user ate before measuring their blood glucose level and output comments regarding the results of the analysis. The contents of the meal include, for example, the nutrients of the food eaten (e.g., GI value, calories, and carbohydrates), the order in which the food was eaten, and the speed at which it was eaten. The contents of the meal may be input by the user via the input unit 25, or obtained by analyzing video images obtained by taking pictures of the user eating with a camera. It may also output comments such as "Please upload images of your meal" to prompt the user to upload images of their meal. Examples of comments regarding the results of the analysis of the contents of the meal include advice such as "Eat your vegetables first" and "Eat slowly."

[0069] Next, the operation of the information processing device 20 according to this exemplary embodiment will be described with reference to Figure 11. The CPU 21 executes the information processing program 27, thereby executing the first evaluation process shown in Figure 11. The first evaluation process shown in Figure 11 is executed, for example, when the user gives an instruction to start processing via the input unit 25.

[0070] In step S10 of Figure 11, the acquisition unit 10 acquires a measured value (e.g., blood glucose level) and time information indicating the measurement time t of the measured value. In step S11, the acquisition unit 10 acquires monitoring values ​​(e.g., interstitial fluid glucose levels) at multiple time points. In step S12, the matching unit 12 associates the measured value acquired in step S10 with multiple monitoring values ​​acquired in step S11, specifically those values ​​within a predetermined period T that include at least one of the time points before and after the measurement time t indicated by the time information acquired in step S10.

[0071] In step S13, the evaluation unit 14 derives the fluctuation trend of the monitoring values ​​during period T based on a plurality of monitoring values ​​associated with the measured values ​​in step S12. In step S14, the evaluation unit 14 estimates the fluctuation trend of the measured values ​​during period T from the fluctuation trend of the monitoring values ​​during period T derived in step S13, based on correlation data in which the correlation relationship between the measured values ​​and the monitoring values ​​is predetermined. In step S15, the evaluation unit 14 performs a first evaluation of the measured values ​​based on the fluctuation trend of the measured values ​​estimated in step S14. In step S16, the control unit 16 outputs a comment corresponding to the content of the first evaluation performed in step S15, and terminates the first evaluation process.

[0072] As described above, the information processing device 20 according to the first exemplary embodiment includes at least one processor, which acquires measurement values ​​measured in a specimen test along with time information indicating the time of measurement of the measurement value, acquires monitoring values ​​obtained by monitoring biological information correlated with the measurement value, and associates the measurement value with the monitoring value at the time of measurement indicated by the time information. Therefore, it is possible to evaluate whether the measurement value is appropriate based on the monitoring value associated with the measurement value, and to obtain appropriate measurement results.

[0073] In the first exemplary embodiment described above, a form using the amplitude as a specific example of the fluctuation trend was explained, but the invention is not limited to this. For example, the slope of the approximate straight line of multiple interstitial fluid glucose values ​​during period T, as well as the variance, standard deviation, and coefficient of variation (standard deviation / arithmetic mean), may be used as the fluctuation trend.

[0074] Furthermore, it is known that the correlation between blood glucose levels and interstitial fluid glucose levels can change due to various factors. Therefore, in the first exemplary embodiment described above, the evaluation unit 14 may estimate the trend of fluctuation in blood glucose levels during period T from the trend of fluctuation in interstitial fluid glucose levels, based on multiple correlation data that differ for each of the various factors.

[0075] For example, as shown in Figure 4, blood glucose levels in diabetic users are known to rise and fall sharply during the postprandial period (Po) (so-called blood glucose spikes). Furthermore, interstitial fluid glucose levels are known to follow changes in blood glucose levels with a delay of approximately 10 minutes, and at most, the delay can be as long as the monitoring interval for interstitial fluid glucose levels plus 15 minutes (for example, 25 minutes). Therefore, during the period of blood glucose spike decline, as shown in Figure 12, there is a correlation where interstitial fluid glucose levels are higher than blood glucose levels. Diabetes is sometimes diagnosed using the degree of decline in postprandial blood glucose spikes, and in this case, it is preferable to use correlation data like that shown in Figure 12. In Figure 12, RLp is the approximation curve, ULp is the estimated upper limit, and LLp is the estimated lower limit.

[0076] Specifically, the memory unit 22 pre-stores correlation data for the fasting period Pr (see Figure 4) and correlation data for the postprandial period Po (see Figure 12). The acquisition unit 10 acquires timing information indicating whether the measurement time t at which blood glucose levels are measured is during fasting or postprandial. The evaluation unit 14 estimates the trend of blood glucose fluctuations during period T from the trend of fluctuations in interstitial fluid glucose levels, based on the correlation data corresponding to the timing indicated by the timing information, from among the correlation data corresponding to fasting and postprandial periods, respectively. The timing information may be entered by the user via the input unit 25, for example, or meal times may be set in advance and the system may make a determination based on the time information.

[0077] Furthermore, it is known that the degree to which blood glucose levels rise and fall varies depending on the content of the meal, such as the nutrients in the food eaten (e.g., glycemic index, calories, and carbohydrates), the order in which food is eaten, and the speed at which it is eaten. For example, glucose, which has a high glycemic index, causes a rapid change in blood glucose levels, while fructose, which has a low glycemic index, causes a slower change in blood glucose levels compared to glucose. As mentioned above, interstitial fluid glucose levels lag behind changes in blood glucose levels, so the variability of blood glucose levels relative to interstitial fluid glucose levels also changes between meals that cause rapid changes in blood glucose levels and meals that cause slow changes in blood glucose levels.

[0078] Therefore, it is preferable that the memory unit 22 pre-stores different correlation data for each meal content, as shown in Figure 13. The acquisition unit 10 acquires meal information indicating the content of the meal eaten by the person who measured the blood glucose level before the measurement. The evaluation unit 14 estimates the trend of blood glucose fluctuations during period T from the trend of fluctuations in interstitial fluid glucose levels, based on the correlation data corresponding to the meal content indicated by the meal information, from among multiple different correlation data for each meal content. For example, in the case of a meal content that causes a slow change in blood glucose levels, the estimated upper limit ULa and estimated lower limit LLa, which have a narrow estimation interval (i.e., small variability) in Figure 13, are used. On the other hand, in the case of a meal content that causes a rapid change in blood glucose levels, the estimated upper limit ULb and estimated lower limit LLb, which have a wide estimation interval (i.e., large variability) in Figure 13, are used. Meal information may be input by the user via the input unit 25, or it may be acquired by analyzing video images obtained by taking pictures of the user eating with a camera.

[0079] Furthermore, if the correlation data shows that the variability of blood glucose levels relative to interstitial fluid glucose levels exceeds a predetermined threshold (i.e., the variability is large), the evaluation unit 14 may make a first evaluation that the blood glucose levels within that range are inappropriate. This is because, in ranges where the correlation between blood glucose levels and interstitial fluid glucose levels is weak, the accuracy of estimating the trend of blood glucose fluctuations based on interstitial fluid glucose levels decreases.

[0080] Furthermore, while the first exemplary embodiment described above describes a form in which interstitial fluid glucose values ​​are used as biological information correlated with blood glucose levels, the system is not limited to this. Other known biological information correlated with blood glucose levels include glucose levels contained in sweat or saliva, electrocardiogram signals, blood pressure, and body temperature. When these values ​​are used instead of interstitial fluid glucose values, the evaluation unit 14 estimates the trend of blood glucose fluctuations based on the monitoring values ​​of these values ​​and correlation data in which the correlation between the monitoring values ​​and blood glucose levels is predetermined. The evaluation unit 14 may also perform the first evaluation by appropriately combining some or all of these monitoring values, including interstitial fluid glucose values. In addition, the evaluation unit 14 may also use correlation data obtained by performing big data analysis (for example, deep learning using AI (Artificial Intelligence)) based on arbitrary biological information obtained by the monitoring device 4 and blood glucose levels, in addition to these values.

[0081] [Second exemplary embodiment] In the first exemplary embodiment described above, a first evaluation was performed based on the trend of interstitial fluid glucose levels during period T, taking into account fluctuations in blood glucose levels throughout the day. On the other hand, it is known that blood glucose levels may fluctuate compared to other days depending on the physical condition, activity level, sleep duration, and diet content of that day. By taking these day-to-day fluctuations into consideration, it is possible to more accurately evaluate whether the blood glucose level is at an appropriate value (i.e., whether it is an improvement or deterioration compared to normal), that is, whether the blood glucose level was measured at the appropriate time.

[0082] Therefore, the information processing device 20 according to this exemplary embodiment evaluates whether the blood glucose level is at an appropriate value, that is, whether the blood glucose level was measured at an appropriate time, by comparing the interstitial fluid glucose level at measurement time t, when the blood glucose level was measured, with a reference value that takes into account daily fluctuations. Hereinafter, this evaluation that takes into account daily fluctuations will be referred to as the "second evaluation". Below, an example of the configuration of the information processing device 20 according to this exemplary embodiment will be described, but in this exemplary embodiment, explanations that overlap with the first exemplary embodiment will be omitted.

[0083] As described above, the acquisition unit 10 acquires blood glucose levels and time information indicating the measurement time t of those blood glucose levels from the measuring device 3. The acquisition unit 10 also acquires interstitial fluid glucose levels at multiple time points from the monitoring device 4. The correspondence unit 12 associates the blood glucose levels acquired by the acquisition unit 10 with the interstitial fluid glucose levels at measurement time t indicated by the time information.

[0084] First, the evaluation unit 14 derives the deviation between the reference value of interstitial fluid glucose at measurement time t indicated by the time information and the actual interstitial fluid glucose value at measurement time t indicated by the time information.

[0085] Here, we will explain the reference values ​​with reference to Figure 14. Figure 14 is a graph with time on the horizontal axis and interstitial fluid glucose value on the vertical axis. In Figure 14, the interstitial fluid glucose value for a given day is shown by a solid line, and the reference lines L50, L25, and L75 are shown by dashed lines. The reference lines L50, L25, and L75 are derived by analyzing the daily interstitial fluid glucose values ​​monitored for the same person, respectively. The reference line L50 represents the representative value of the daily interstitial fluid glucose value at each point in time. "Representative value" refers to, for example, the arithmetic mean, median, and mode. The reference lines L25 and L75 are defined such that the interstitial fluid glucose value falls between the reference line L25 and the reference line L75 with a probability of 25% above and below (50% in total) the reference line L50.

[0086] The evaluation unit 14 obtains a reference value for interstitial fluid glucose at measurement time t indicated by the time information, based on the reference line L50, and derives the deviation from the interstitial fluid glucose value. For example, the evaluation unit 14 derives a deviation of 0 at measurement time t1 shown in Figure 14. It also derives a deviation of 20 at measurement time t3 shown in Figure 14.

[0087] Next, the evaluation unit 14 performs a second evaluation of the blood glucose level based on the derived deviation. As mentioned above, blood glucose levels fluctuate from day to day. Therefore, if a measurement is taken on a day when the blood glucose level happens to be low, the comment will be output using a value lower than the blood glucose level on most days, reducing its validity. To address this, the evaluation unit 14 performs a second evaluation of the blood glucose level depending on whether the deviation of the interstitial fluid glucose value from the reference value at measurement time t is acceptable. For example, if the deviation of the interstitial fluid glucose value at measurement time t is below a predetermined threshold, the evaluation unit 14 evaluates that the blood glucose level at measurement time t is similar to that on other days and is therefore appropriate.

[0088] For example, suppose the threshold for deviation is "15". As described above, the deviation at measurement time t1 derived by the evaluation unit 14 is 0, which is below the threshold, so the evaluation unit 14 evaluates that the blood glucose level at measurement time t1 is appropriate. On the other hand, the deviation at measurement time t3 derived by the evaluation unit 14 is 20, which is above the threshold, so the evaluation unit 14 evaluates that the blood glucose level at measurement time t3 is inappropriate.

[0089] The control unit 16 controls the output of comments corresponding to the second evaluation by the evaluation unit 14. For example, if the second evaluation determines that the blood glucose level is inappropriate, the control unit 16 outputs a comment recommending that the test be performed again on another day, such as, "Are you feeling tired today? Let's do another test tomorrow." The control unit 16 may also output comments similar to those for the first evaluation described in the first exemplary embodiment, depending on the second evaluation.

[0090] Next, the operation of the information processing device 20 according to this exemplary embodiment will be described with reference to Figure 15. The CPU 21 executes the information processing program 27, thereby executing the second evaluation process shown in Figure 15. The second evaluation process shown in Figure 15 is executed, for example, when the user gives an instruction to start processing via the input unit 25.

[0091] In step S20 of Figure 15, the acquisition unit 10 acquires a measured value (e.g., blood glucose level) and time information indicating the measurement time t of the measured value. In step S21, the acquisition unit 10 acquires a monitoring value (e.g., interstitial fluid glucose level). In step S22, the matching unit 12 associates the measured value acquired in step S20 with the monitoring value acquired in step S21 at the measurement time t indicated by the time information acquired in step S20.

[0092] In step S23, the evaluation unit 14 performs a second evaluation of the measured value based on the deviation between the reference value of the monitoring value at measurement time t indicated by the time information acquired in step S20 and the monitoring value associated with the measured value in step S22. In step S24, the control unit 16 outputs a comment corresponding to the content of the second evaluation performed in step S23 and terminates the second evaluation process.

[0093] As described above, the information processing device 20 according to the second exemplary embodiment performs a second evaluation of the measured value based on the deviation between the reference value of the monitoring value at measurement time t indicated by the time information and the monitoring value at measurement time t indicated by the time information. Therefore, it is possible to evaluate whether the measured value is an appropriate value based on the monitoring value at measurement time t (i.e., the monitoring value associated with the measured value), and to obtain an appropriate measurement result.

[0094] In the second exemplary embodiment described above, unlike the first exemplary embodiment, the acquisition unit 10 does not necessarily have to acquire interstitial fluid glucose values ​​at multiple points in time. For example, the acquisition unit 10 may acquire only one interstitial fluid glucose value corresponding to the blood glucose measurement time t, and the evaluation unit 14 may perform a second evaluation of the blood glucose level based on that interstitial fluid glucose value. However, in order to perform the second evaluation more appropriately, it is more preferable to perform the second evaluation of the blood glucose level based on multiple interstitial fluid glucose values ​​in a period T that includes at least one of the periods before and after the blood glucose measurement time t.

[0095] Furthermore, in the second exemplary embodiment described above, the evaluation unit 14 may perform a second evaluation depending on whether the interstitial fluid glucose value at measurement time t indicated by the time information falls between the reference line L25 and the reference line L75.

[0096] Furthermore, in the second exemplary embodiment described above, the evaluation unit 14 may change the threshold for deviation according to the time and timing, such as whether it is fasting or post-meal. This is because, as shown in Figure 14, it is known that post-meal blood glucose levels have greater day-to-day variability than fasting blood glucose levels.

[0097] [Third Exemplary Embodiment] Diabetes diagnosis sometimes uses the peak blood glucose level during a postprandial blood glucose spike. For example, in the example shown in Figure 16, if the goal is to measure the peak blood glucose level during a post-breakfast blood glucose spike, it is preferable to measure the blood glucose level at the target time (tc) when the peak is reached. However, in reality, it is difficult to know in advance the target time (tc) when the blood glucose level will reach its peak, and the blood glucose measurement may deviate from the target time (tc).

[0098] Therefore, the information processing device 20 according to this exemplary embodiment evaluates whether the discrepancy between the measurement time t and the target time tc is acceptable, that is, whether the measurement time t is an appropriate time, based on the value of the interstitial fluid glucose level at the blood glucose measurement time t. Hereinafter, this evaluation will be referred to as the "third evaluation". Below, an example of the configuration of the information processing device 20 according to this exemplary embodiment will be described, but in this exemplary embodiment, explanations that overlap with the first and second exemplary embodiments will be omitted.

[0099] As an example, let's assume that the actual blood glucose level was measured at measurement time t4, relative to the target time tc shown in Figure 16. As described above, the acquisition unit 10 acquires the blood glucose level and time information indicating the measurement time t4 of the blood glucose level from the measuring device 3. The acquisition unit 10 also acquires interstitial fluid glucose values ​​from the monitoring device 4 at multiple time points, including at least the time points corresponding to measurement time t4 and the target time tc. The correspondence unit 12 associates the blood glucose level acquired by the acquisition unit 10 with the interstitial fluid glucose value at measurement time t4 indicated by the time information.

[0100] The evaluation unit 14 performs a third evaluation of the measurement time t4 indicated by the time information, based on the interstitial fluid glucose value associated with the blood glucose level. Specifically, first, the evaluation unit 14 identifies the interstitial fluid glucose value (in this case, the peak value) at the target time tc based on the interstitial fluid glucose values ​​at multiple time points acquired by the acquisition unit 10. Next, the evaluation unit 14 derives the difference between the interstitial fluid glucose value at measurement time t4 associated with the blood glucose level and the interstitial fluid glucose value at the target time tc. Next, if the derived difference is below a predetermined threshold, the evaluation unit 14 evaluates that the difference between the interstitial fluid glucose value at measurement time t4 and the interstitial fluid glucose value at the target time tc is acceptable and that measurement time t is an appropriate time.

[0101] The control unit 16 controls the output of comments corresponding to the third evaluation by the evaluation unit 14. For example, if the third evaluation determines that the measurement time t4 is inappropriate, the control unit 16 outputs a comment containing a warning such as, "Blood glucose levels could not be measured at the target time." The control unit 16 may also output comments similar to those for the first evaluation described in the first exemplary embodiment, depending on the third evaluation.

[0102] Next, the operation of the information processing device 20 according to this exemplary embodiment will be described with reference to Figure 17. The CPU 21 executes the information processing program 27, thereby executing the third evaluation process shown in Figure 17. The third evaluation process shown in Figure 17 is executed, for example, when the user issues an instruction to start processing via the input unit 25.

[0103] In step S30 of Figure 17, the acquisition unit 10 acquires a measured value (e.g., blood glucose level) and time information indicating the measurement time t of the measured value. In step S31, the acquisition unit 10 acquires a monitoring value (e.g., interstitial fluid glucose level). In step S32, the matching unit 12 associates the measured value acquired in step S30 with the monitoring value acquired in step S31 at the measurement time t indicated by the time information acquired in step S30.

[0104] In step S33, the evaluation unit 14 performs a third evaluation of the measured value based on the monitoring value associated with the measured value in step S32. In step S34, the control unit 16 outputs a comment corresponding to the content of the third evaluation performed in step S33, and terminates the third evaluation process.

[0105] As described above, the information processing device 20 according to the third exemplary embodiment performs a third evaluation of the measurement time t indicated by the time information based on the monitoring value associated with the measured value. Therefore, it is possible to evaluate whether the measurement time t of the measured value is an appropriate time based on the monitoring value associated with the measured value, and to obtain appropriate measurement results.

[0106] In the third exemplary embodiment described above, unlike the first exemplary embodiment, the acquisition unit 10 does not necessarily have to acquire interstitial fluid glucose values ​​at multiple time points. For example, it may be possible to estimate the interstitial fluid glucose value at the target time point tc in advance based on actual blood glucose levels or interstitial fluid glucose levels prior to the day the test is performed. In this case, the acquisition unit 10 acquires only one interstitial fluid glucose value corresponding to the blood glucose measurement time point t4, and the evaluation unit 14 performs the third evaluation based on that interstitial fluid glucose value and the previously estimated interstitial fluid glucose value.

[0107] Furthermore, in the third exemplary embodiment described above, the evaluation unit 14 may perform a third evaluation based on the temporal discrepancy between the target time point tc and the measurement time point t4 indicated by the time information. In this case, for example, the evaluation unit 14 derives the temporal difference between the target time point tc and the measurement time point t4, and evaluates that the measurement time point t4 is an appropriate time if the temporal difference is less than or equal to a predetermined threshold.

[0108] Furthermore, while the third exemplary embodiment described above explains an example where the target time point tc is the time when the interstitial fluid glucose value reaches its peak, the method is not limited to this. In some cases, blood glucose levels at various time points after a meal (e.g., 30 minutes, 1 hour, and 2 hours after a meal) are used to determine diabetes. In addition, blood glucose levels may be measured at the same time every day for the purpose of understanding daily fluctuations in blood glucose levels. In these cases, the target time point tc may be set as, for example, a predetermined time after a meal (e.g., 30 minutes, 1 hour, and 2 hours after a meal), or a predetermined time.

[0109] [Fourth Exemplary Embodiment] In the first to third exemplary embodiments described above, various evaluations were performed on the measured blood glucose level and the measurement time t after the blood glucose level was measured. The information processing device 20 according to this exemplary embodiment has a function to recommend the timing of blood glucose measurement before the blood glucose level is measured, by applying the technology disclosed in the first to third exemplary embodiments. Below, an example of the configuration of the information processing device 20 according to this exemplary embodiment will be described, but in this exemplary embodiment, explanations that overlap with the first to third exemplary embodiments will be omitted.

[0110] For example, by applying the technology disclosed in the second exemplary embodiment, the interstitial fluid glucose level at the current time trial (TR) in which blood glucose levels are to be measured may be compared with a reference value that takes into account daily fluctuations to determine whether or not to recommend measuring blood glucose levels. Specifically, blood glucose levels may be recommended if the deviation of the interstitial fluid glucose level at the current time trial from the reference value is acceptable.

[0111] In this case, the acquisition unit 10 acquires the interstitial fluid glucose value at the current time trial from the monitoring device 4. The evaluation unit 14 evaluates that blood glucose can be measured if the deviation between the reference value of the interstitial fluid glucose value at the current time trial and the interstitial fluid glucose value is smaller than a predetermined threshold.

[0112] If the evaluation unit 14 determines that blood glucose levels can be measured, the control unit 16 performs control to recommend measuring blood glucose levels. For example, the control unit 16 outputs a comment such as, "Currently, blood glucose levels are moving normally. Let's measure your blood glucose levels." On the other hand, if the evaluation unit 14 determines that blood glucose levels cannot be measured, the control unit 16 performs control to issue a warning. For example, the control unit 16 outputs a comment such as, "Currently, blood glucose levels are moving abnormally. We recommend measuring your blood glucose levels later, taking multiple measurements, or canceling this measurement." In addition, the control unit 16 may output a diagram like the one shown in Figure 18 so that the user can understand the relationship between the interstitial fluid glucose level and the reference value at the current time.

[0113] Next, the operation of the information processing device 20 according to this exemplary embodiment will be described with reference to Figure 19. The CPU 21 executes the information processing program 27, thereby executing the measurement recommendation process shown in Figure 19. The measurement recommendation process shown in Figure 19 is, as an example, an application of the technology disclosed in the second exemplary embodiment. The measurement recommendation process shown in Figure 19 is executed, for example, when the user gives an instruction to start the process via the input unit 25.

[0114] In step S40 of Figure 19, the acquisition unit 10 acquires the current monitoring value (e.g., interstitial fluid glucose value). In step S41, the evaluation unit 14 determines whether the deviation between the monitoring value acquired in step S40 and the current reference value of the monitoring value is less than a threshold. If step S41 is a positive determination, the process moves to step S42, where the control unit 16 performs a process to recommend measurement of the measurement value. If step S41 is a negative determination, or if step S42 is completed, this measurement recommendation process ends.

[0115] As described above, the information processing device 20 according to the fourth exemplary embodiment includes at least one processor, which acquires monitoring values ​​obtained by monitoring biological information that correlates with the measured values ​​measured in the specimen test, and recommends measuring the measured value when the deviation between the monitoring value and the reference value of the monitoring value is smaller than a predetermined threshold. Therefore, since the measured value can be measured at a point in time when it is estimated that the measured value is taking an appropriate value based on the monitoring value, an appropriate measurement result can be obtained.

[0116] In the third exemplary embodiment described above, a measurement recommendation process applying the technology disclosed in the second exemplary embodiment was explained. However, the invention is not limited to this, and the technology disclosed can also be applied to the first and third exemplary embodiments. For example, by applying the technology disclosed in the first exemplary embodiment, a decision may be made as to whether or not to recommend measuring blood glucose based on the trend of fluctuations in multiple interstitial fluid glucose values ​​over a predetermined period T, including the period prior to the current time tr in which blood glucose measurement is to be attempted. Specifically, blood glucose measurement may be recommended if the trend of fluctuations in interstitial fluid glucose values ​​over period T is acceptable.

[0117] As an example, let's explain the case where the fluctuation range is used as the trend of change in interstitial fluid glucose levels during period T. In this case, the acquisition unit 10 acquires multiple interstitial fluid glucose levels from the monitoring device 4 during a predetermined period T, including before the current time tr. The evaluation unit 14 derives the fluctuation range of the multiple interstitial fluid glucose levels during a predetermined period T, including before the current time tr, and evaluates that blood glucose levels can be measured if the fluctuation range is smaller than a predetermined threshold.

[0118] Alternatively, for example, by applying the technology disclosed in the third exemplary embodiment, it may be decided whether or not to recommend measuring blood glucose levels depending on whether the discrepancy between the current time point (TR) and the target time point (TC) is acceptable.

[0119] For example, based on past blood glucose or interstitial fluid glucose levels prior to the day of the test, it may be possible to estimate the interstitial fluid glucose level at the target time point (TC) in which the blood glucose level is to be measured. In this case, the acquisition unit 10 acquires the interstitial fluid glucose level at the current time point (TR) from the monitoring device 4. The evaluation unit 14 derives the difference between the interstitial fluid glucose level at the current time point (TR) and the interstitial fluid glucose level at the target time point (TC) estimated in advance, and evaluates that the blood glucose level can be measured if the difference is smaller than a predetermined threshold.

[0120] For example, the target time point (tc) for measuring blood glucose levels may be specified as a predetermined time after a meal (e.g., 30 minutes, 1 hour, and 2 hours after a meal), or a predetermined time. In this case, the evaluation unit 14 derives the time difference between the target time point (tc) and the current time point (tr), and evaluates that blood glucose levels can be measured if the time difference is less than or equal to a predetermined threshold.

[0121] In the above exemplary embodiments, examples were given in which interstitial fluid glucose levels were used as monitoring values ​​for biological information correlated with blood glucose levels, but the invention is not limited to this. At least one of the following can be used as monitoring values ​​for biological information correlated with blood glucose levels: glucose levels contained in sweat or saliva, electrocardiogram signals, blood pressure, and body temperature.

[0122] Furthermore, while the above exemplary embodiments describe a configuration in which the monitoring device 4 uses a device that measures interstitial fluid glucose levels by inserting a needle-shaped filament under the user's epidermis, the invention is not limited to this. For example, the monitoring device 4 may be a wearable terminal such as a wristwatch, glasses, earphones, or a ring. The wearable terminal may, for example, irradiate the user's skin with infrared light to analyze the signal emitted by glucose in the blood and derive the glucose level. Alternatively, for example, at least one of the user's electrocardiogram signal, blood pressure, and body temperature, measured by a sensor on the wearable terminal, may be used as the monitoring value. When a wearable terminal is used, the monitoring value can be measured non-invasively, thus reducing pain during puncture and running costs, and reducing the burden on the user.

[0123] A wearable device is a computer such as a smartwatch, and comprises a CPU, a non-volatile storage unit implemented by a storage medium such as an HDD, SSD, and flash memory, and memory as a temporary storage area. The wearable device also comprises an input / output unit such as buttons, a display, and a touch panel, and a network interface that performs wired or wireless communication with an information processing device 20 and an external network (not shown).

[0124] Furthermore, in each of the above exemplary embodiments, the measuring device 3, the monitoring device 4, and the information processing device 20 may be composed of a single device or multiple devices. For example, the measuring device 3 and the monitoring device 4 may be an integrated device. Alternatively, for example, a wearable terminal may be used as the monitoring device 4, and the wearable terminal may have the functions of the information processing device 20.

[0125] Furthermore, while the above exemplary embodiments used blood glucose levels as an example of measured values ​​and interstitial fluid glucose levels as an example of monitored values, the invention is not limited to these examples. For instance, blood pressure measured by a blood pressure monitor may be used as the measured value, and a blood pressure equivalent value measured by a sensor on a wearable device may be applied as the monitored value. Alternatively, for example, body temperature measured by a thermometer may be used as the measured value, and a body temperature equivalent value measured by a sensor on a wearable device may be applied as the monitored value.

[0126] Furthermore, while the above exemplary embodiments describe configurations in which the acquisition unit 10 acquires measured values, time information, and monitoring values ​​from the measuring device 3 and the monitoring device 4, the system is not limited to these configurations. For example, the measuring device 3 and the monitoring device 4 may transmit measured values, time information, and monitoring values ​​to an arbitrary aggregation server, and the acquisition unit 10 may acquire the measured values, time information, and monitoring values ​​from the aggregation server. Alternatively, for example, a user may input measured values, time information, and monitoring values ​​via the input unit 25, and the acquisition unit 10 may acquire the measured values, time information, and monitoring values ​​input by the user.

[0127] Furthermore, in each of the above exemplary embodiments, the hardware structure of the processing unit that performs various processes, such as the acquisition unit 10, the correspondence unit 12, the evaluation unit 14, and the control unit 16, can be the following types of processors. As mentioned above, these types of processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as various processing units, as well as programmable logic devices (PLDs), such as FPGAs (Field Programmable Gate Arrays), which are processors whose circuit configuration can be changed after manufacturing, and dedicated electrical circuits, such as ASICs (Application Specific Integrated Circuits), which are processors with circuit configurations specifically designed to perform specific processes.

[0128] A single processing unit may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, multiple processing units may be composed of a single processor.

[0129] Examples of configuring multiple processing units with a single processor include, firstly, a configuration where one or more CPUs and software combine to form a single processor, which then functions as multiple processing units, as exemplified by client and server computers. Secondly, a configuration using a processor that realizes the functions of the entire system, including multiple processing units, on a single IC (Integrated Circuit) chip, as exemplified by System on Chip (SoC). Thus, various processing units are configured, in terms of hardware structure, using one or more of the above-mentioned processors.

[0130] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits, which are combinations of circuit elements such as semiconductor devices.

[0131] Furthermore, while the above exemplary embodiments describe a configuration in which the information processing program 27 is pre-stored (installed) in the storage unit 22, the invention is not limited thereto. The information processing program 27 may be provided in the form of a recording medium such as a CD-ROM (Compact Disc Read Only Memory), DVD-ROM (Digital Versatile Disc Read Only Memory), or USB (Universal Serial Bus) memory. Alternatively, the information processing program 27 may be provided in the form of a download from an external device via a network. Moreover, the technology of this disclosure extends not only to the information processing program but also to storage media for non-temporarily storing the information processing program.

[0132] The technology disclosed herein can also be appropriately combined from the above-described examples. The descriptions and illustrations shown above are detailed explanations of the parts relating to the technology disclosed herein and are merely examples of the technology disclosed herein. For example, the above-described explanation of the configuration, function, operation, and effect is an explanation of an example of the configuration, function, operation, and effect of the parts relating to the technology disclosed herein. Therefore, it goes without saying that unnecessary parts may be deleted, new elements added, or replaced from the descriptions and illustrations shown above, as long as they do not deviate from the spirit of the technology disclosed herein.

[0133] The disclosure of Japanese Patent Application No. 2020-199170, filed on 30 November 2020, is incorporated herein by reference in its entirety. All documents, patent applications, and technical standards described herein are incorporated herein by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

Claims

1. Equipped with at least one processor, The aforementioned processor, The measured values ​​obtained in the specimen test are acquired along with time information indicating the time of measurement. Obtain monitoring values ​​obtained by monitoring biological information that has a correlation with the aforementioned measurement values, The measured value and the monitoring value at the time of measurement indicated by the time information are associated with each other. Obtain the monitoring values ​​at multiple points in time, Identify the monitoring value at the target time point in which the measured value is measured, A third evaluation is performed on the appropriateness of the measurement time indicated by the time information, based on a comparison of the difference between the measurement value associated with the measurement value and the monitoring value at the target time point, and a predetermined threshold. Information processing device.

2. The aforementioned processor, After acquiring the measured values ​​and time information, the acquired measured values ​​are associated with the monitoring values ​​at the time of measurement indicated by the time information. The information processing apparatus according to claim 1.

3. The aforementioned processor, Obtain the monitoring values ​​at multiple points in time, Among the monitoring values ​​at the aforementioned multiple time points, a plurality of monitoring values ​​within a predetermined period that includes at least one of the time points before and after the measurement time point indicated by the time information are associated with the measured value. The information processing apparatus according to claim 1 or 2.

4. The aforementioned processor, Based on the measured values ​​and the plurality of monitoring values ​​associated with them, the trend of change in the monitoring values ​​during the period is derived. Based on predetermined correlation data, the correlation between the measured value and the monitoring value is used to estimate the trend of change in the measured value during the period from the trend of change in the monitoring value. The information processing apparatus according to claim 3.

5. The measurement mentioned above is blood glucose level. The aforementioned monitoring value is at least one of the following, which correlates with blood glucose levels: glucose levels in interstitial fluid, sweat, or saliva, electrocardiogram signals, blood pressure, and body temperature. The aforementioned processor, The timing information indicating whether the measurement was taken on an empty stomach or after a meal is obtained. Based on the correlation data corresponding to the timing indicated by the timing information, among the correlation data corresponding to fasting and post-meal states, the trend of change in the measured value during the period is estimated from the trend of change in the monitoring value. The information processing apparatus according to claim 4.

6. The measurement mentioned above is blood glucose level. The aforementioned monitoring value is at least one of the following, which correlates with blood glucose levels: glucose levels in interstitial fluid, sweat, or saliva, electrocardiogram signals, blood pressure, and body temperature. The aforementioned processor, The person who measured the measurement obtains meal information indicating the contents of the meal they ate before the measurement was taken. Based on the correlation data corresponding to the meal content indicated by the meal information, from among the multiple correlation data that differ for each meal content, the trend of change in the measured value during the period is estimated from the trend of change in the monitoring value. The information processing apparatus according to claim 4 or 5.

7. The aforementioned processor, As the trend of fluctuation in the aforementioned monitoring value, the amplitude of the fluctuation in the aforementioned monitoring value during the aforementioned period is derived. The information processing apparatus according to any one of claims 4 to 6.

8. The aforementioned processor, Output comments corresponding to the fluctuation trend of the estimated measured values. The information processing apparatus according to any one of claims 4 to 7.

9. The aforementioned processor, Based on a comparison of the estimated fluctuation trend of the measured values ​​with a predetermined threshold, a first evaluation of the appropriateness of the measured values ​​is performed. The information processing apparatus according to any one of claims 4 to 8.

10. The aforementioned processor, Output comments corresponding to the first evaluation. The information processing apparatus according to claim 9.

11. The aforementioned processor, Based on the measured values ​​and the plurality of monitoring values ​​associated with them, the trend of change in the monitoring values ​​during the period is derived. Based on a comparison of the fluctuation trend of the monitoring value and a predetermined threshold, a first evaluation is performed regarding the appropriateness of the measured value. An information processing apparatus according to any one of claims 3 to 10.

12. The aforementioned processor, A second evaluation of the appropriateness of the measured value is performed based on a comparison between the deviation between the reference value of the monitoring value at the measurement time indicated by the time information and the monitoring value at the measurement time indicated by the time information, and a predetermined threshold. An information processing apparatus according to any one of claims 1 to 11.

13. The aforementioned processor, Output comments corresponding to the second evaluation described above. The information processing apparatus according to claim 12.

14. The aforementioned processor, Output comments corresponding to the third evaluation mentioned above. The information processing apparatus according to claim 1.

15. The aforementioned processor, Output the monitoring value corresponding to the measured value. An information processing apparatus according to any one of claims 1 to 14.

16. The processor is If the aforementioned deviation is smaller than the aforementioned threshold, measurement of the measurement value is recommended. The information processing apparatus according to claim 12.

17. The measurement mentioned above is blood glucose level. The aforementioned monitoring value is at least one of the following, which correlates with blood glucose levels: glucose levels in interstitial fluid, sweat, or saliva, electrocardiogram signals, blood pressure, and body temperature. An information processing apparatus according to any one of claims 1 to 16.

18. The measured values ​​obtained in the specimen test are acquired along with time information indicating the time of measurement. Obtain monitoring values ​​obtained by monitoring biological information that has a correlation with the aforementioned measurement values, The measured value and the monitoring value at the time of measurement indicated by the time information are associated with each other. Obtain the monitoring values ​​at multiple points in time, Identify the monitoring value at the target time point in which the measured value is measured, A third evaluation is performed on the appropriateness of the measurement time indicated by the time information, based on a comparison of the difference between the measurement value associated with the measurement value and the monitoring value at the target time point, and a predetermined threshold. An information processing method in which a computer performs the processing.

19. The measured values ​​obtained in the specimen test are acquired along with time information indicating the time of measurement. Obtain monitoring values ​​obtained by monitoring biological information that has a correlation with the aforementioned measurement values, The measured value and the monitoring value at the time of measurement indicated by the time information are associated with each other. Obtain the monitoring values ​​at multiple points in time, Identify the monitoring value at the target time point in which the measured value is measured, A third evaluation is performed on the appropriateness of the measurement time indicated by the time information, based on a comparison of the difference between the measurement value associated with the measurement value and the monitoring value at the target time point, and a predetermined threshold. An information processing program that causes a computer to perform a task.

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