WO2019022248A1

WO2019022248A1 - Information processing device, information processing method, and program

Info

Publication number: WO2019022248A1
Application number: PCT/JP2018/028332
Authority: WO
Inventors: 織田　聡; 良英秋根
Original assignee: 織田　聡; 良英秋根
Priority date: 2017-07-27
Filing date: 2018-07-27
Publication date: 2019-01-31
Also published as: JP7032072B2; JP2019028625A

Abstract

Provided is a method with which a subject measuring his/her blood sugar level can easily ascertain the relationship between the blood sugar level and the content of meals he/she has actually consumed. A blood sugar level data acquisition unit 101 acquires blood sugar level data, which is chronological information about a blood sugar level. A meal data management unit 102 acquires meal data, which is chronological information pertaining to meals consumed by the subject measuring his/her blood sugar level. On the basis of the blood sugar level data acquired by the blood sugar level data acquisition means and the meal data acquired by the meal data acquisition means, a graph generation unit 103 generates a second graph in which information indicating the content of the meals of the subject is displayed superposed on a first graph representing the chronological change in the blood sugar level of the subject.

Description

INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM

The present invention relates to an information processing apparatus, an information processing method, and a program.

Conventionally, there is CGM (Continuous Glucose Monitoring / sustained blood glucose measurement) as a method of continuously measuring sugar concentration in subcutaneous tissue interstitial fluid at regular intervals for 24 hours or more (see Non-Patent Document 1).
Further, the image stored in the storage area is acquired, the meal portion included in the acquired image is specified, and the color frequency distribution of the plurality of pixels is determined based on the value of each of the plurality of pixels included in the specified meal portion. Based on the created color frequency distribution, the number of color types included in the meal part is calculated, and based on the calculated number of color types, the meal balance numerical value is calculated, and the calculated meal balance numerical value is output There is an analysis device (see Patent Document 1).

JP 2012-212249 A

However, with the techniques described in Non-Patent Document 1 and Patent Document 1, it is not possible to grasp the relationship between the specific content of the meal consumed by the subject of the blood glucose level and the blood glucose level.

The present invention is made in view of such a situation, and an object of the present invention is to provide a method for easily grasping the relation between the contents of a meal ingested by a subject of blood glucose level and the blood glucose level.

In order to achieve the above object, an information processing apparatus according to an aspect of the present invention is:
Blood glucose level data acquisition means for acquiring blood glucose level data, which is temporal information of blood glucose level,
A meal data acquisition unit that acquires meal data that is temporally information on the meal of the subject of the blood glucose level;
A first graph showing temporal changes in blood glucose level of the subject based on the blood glucose level data acquired by the blood glucose level data acquiring unit and the meal data acquired by the meal data acquiring unit A graph generation unit that generates a second graph in which information indicating the contents of the subject's meal is displayed in a superimposed manner;
Equipped with

Further, the meal data includes at least meal image data, which is data of an image obtained by capturing the content of the meal of the subject, and information on date and time when the image is captured,
The food image data may be analyzed to further include detailed information extraction means for extracting detailed information including at least information on a used food material and a sugar mass, for the food consumed by the subject.

Activity data acquisition means for acquiring activity data, which is temporal information on the activity of the subject;
Data analysis means for analyzing the influence of the contents of the meal of the subject and the contents of the activity on the change of the blood glucose level based on the blood glucose level data, the meal data and the activity data;
Based on analysis data obtained as a result of analysis by the data analysis means, alert information is generated including at least one of notes on the diet the subject is about to ingest, and notes on the activity of the subject. An alert management unit that executes control to output the generated alert information to an information processing terminal operated by the subject;
Can further be provided.

An information processing method and program according to an aspect of the present invention are processing methods and programs corresponding to the above-described information processing apparatus according to the aspect of the present invention.

According to the present invention, it is possible to grasp the relationship between the content of a meal ingested by the subject having a blood glucose level and the blood glucose level. As a result, not only the subject of the blood glucose level but also the doctor, a registered dietitian, etc. are not satisfied with the subject of the blood glucose level based on the relationship between the content of the meal consumed by the subject of the blood glucose level and the blood glucose level. It is possible to accurately give instructions for diseases and beauty.

It is a block diagram of the information processing system containing the server which is one Embodiment of the information processing apparatus of this invention. It is a block diagram which shows the hardware constitutions of a server among the information processing systems of FIG. FIG. 5 is a functional block diagram showing an example of a functional configuration for realizing a graph generation process among the functional configurations of the server of FIG. 2 in the information processing system of FIG. 1. It is a figure which shows the specific example (blood glucose level) of the various data memorize | stored and managed by the server of FIG. It is a figure which shows the specific example (meal data) of the various data memorize | stored and managed by the server of FIG. It is a flowchart explaining the flow of the graph production | generation process which the server of FIG. 3 performs. It is an image figure which shows an example of the blood glucose level / meal graph produced | generated by the graph production | generation process which the server of FIG. 3 performs.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

FIG. 1 is a block diagram of an information processing system including a server 1 which is an embodiment of the information processing apparatus of the present invention.

The information processing system shown in FIG. 1 is configured by mutually connecting a server 1, a user terminal 2, a doctor terminal 4, and a dietitian terminal 5 via a network N such as the Internet. In addition, a blood glucose level measuring device 3 is connected to the user terminal 2.

The user U is a person who operates the user terminal 2 and is a person who continuously measures his / her blood glucose level for 24 hours using the blood glucose level measuring device 3 connected to the user terminal 2. In addition, the user U is also a person who uses the imaging function of the user terminal 2 to continuously image the contents of his own meal.
The doctor D is a person who operates the doctor terminal 4 and is a person who performs health management instruction of the user U.
The management dietitian M is a person who operates the dietitian terminal 5 and is a person who performs nutrition management instruction of the user U.

The server 1 is an information processing apparatus that executes various processes in order to manage the operation of the user terminal 2. For example, the server 1 includes temporal information on the blood sugar level of the user U (hereinafter referred to as “blood sugar level data”) and temporal information on contents of the meal of the user U (hereinafter referred to as “meal data”). Based on the above, a graph (hereinafter referred to as “blood sugar level / meal graph”) indicating the relation between the contents of each meal of the user U and the blood sugar level of the user U is generated. The meal data in the present embodiment includes at least data of an image obtained by capturing the content of each meal of the user U (hereinafter referred to as "meal image data") and information on the date and time when the image is captured. . In addition, the server 1 analyzes the meal image data included in the meal data to extract detailed information such as ingredients and nutrients contained in the imaged food, and the meal data is also included in the extracted detailed information. Manage as.
The blood sugar level / meal graph specifically displays information indicating the contents of the food data in a superimposed manner based on the blood sugar level transition graph showing the time-lapse numerical value of the user U's blood sugar level. The food consumed by U and the change in blood glucose level of user U are visualized. For this reason, at first glance at the blood glucose level / meal graph, it is possible to easily grasp the influence of the contents of the meal consumed by the user U on the blood glucose level of the user U.

The blood glucose level is the concentration of glucose (glucose) in the blood of the user U. When the user U is healthy, the fasting blood glucose level is approximately 80 to 100 mg / dL, but the blood glucose level after eating a meal shows a slightly higher value. That is, when the user U eats, carbohydrates are absorbed and become glucose into the blood. For this reason, the blood glucose level after having a meal is higher than the blood glucose level before having a meal. If the user U's fasting blood glucose level in the early morning is 126 mg / dL or more, or the blood glucose level after a meal is 200 mg / dL or more, it is said that the suspicion of diabetes is heavy.
Thus, the blood sugar level basically increases in value as the user U consumes a meal. However, depending on various factors such as the constitution of the user U, the content of the meal, the timing of the meal, and the type of behavior after eating, it is considered that the degree of increase in the blood glucose level of the user U is different.
For example, depending on the constitution of the user U who eats "Udon", "pasta", and "white rice" having the same content of carbohydrates, the blood sugar level is large only when "white rice" is ingested. It may rise. In addition, even when the user U ingests the "gyudon Nashimori" of A beef bowl storehouse and the "gyudon noodles bowl" of B beef bowl storehouse at the same timing, there is a large difference in the rise of the blood glucose level. May occur.
Further, for example, there may be a large difference in the rise of the blood glucose level between the case where the user U eats at the time of lunch and the case where he eats at the same time the same "Udon". In addition, even when the same type of "Udon" is ingested during the same time zone, there is a large difference between the increase in blood sugar level when performing exercise before eating and when not performing exercise. May occur.

That is, the doctor D and the registered dietitian M perform appropriate health guidance and nutrition guidance for the user U simply by grasping general information such as the content of nutrients such as carbohydrates contained in the user U's diet. I can not do it. That is, in order for the doctor D and the registered dietitian M to give appropriate health and nutrition guidance to the user U, various factors such as the contents of the user U's meal and the timing of the meal must be sufficiently considered. .
In this regard, the blood glucose level / meal graph generated by the server 1 of FIG. 1 "visualizes" the contents of the user U's meal and the timing of the meal. Therefore, the doctor D or the registered dietitian M can easily grasp the relationship between the contents of the meal consumed by the user U and the timing of the meal and the change in the blood glucose level simply by looking at the blood glucose level / meal graph. it can.
Thus, the doctor D or the registered dietitian M can give the user U appropriate health instruction only by asking the user U about the past activity contents of the user U while looking at the blood glucose level / meal graph. it can. Specifically, for example, from the contents of the blood sugar level and the contents of the meal graph and the result of the inquiry, it can be understood that the user U who has exercised after eating has a constitution in which the increase in blood sugar level is smaller than exercise before eating. There is. In this case, the doctor D can provide the user U with health guidance to exercise as much as possible after eating.
Also, for example, the blood sugar level tends to be greatly increased only when the user U ingests "white rice" out of "udon", "pasta" and "white rice" at first glance at the blood sugar level / meal graph. It may be possible to grasp. In this case, the registered dietitian M can provide the user U with nutrition instruction to the effect that the carbohydrates should be taken from noodles such as udon and pasta as much as possible.
Also, not only the doctor D and the dietetic dietitian M but also the user U himself / herself sees the blood glucose level / meal graph at a glance, and at what time the blood glucose level easily rises, and at which time it is difficult for the user U to Unique constitutions and trends can be easily grasped.
In addition, the specific example of a blood glucose level and a meal graph is later mentioned with reference to FIG.

The user terminal 2 is an information processing terminal operated by the user U, and includes, for example, a smartphone. Based on the operation of the user U, the user terminal 2 images the contents of the meal of the user U with a camera function provided by the user terminal 2, and transmits meal image data obtained by the imaging to the server 1 as meal data.

The blood glucose level measuring device 3 is an electronic device for the user U to continuously measure his or her blood glucose level. The blood glucose level measuring device 3 and the user terminal 2 are connected using near field communication technology such as Bluetooth (registered trademark) or wire communication such as a cable. The blood glucose level measuring device 3 continuously measures the blood glucose level of the user U for 24 hours based on the operation of the user U, and transmits the blood glucose level data as the measurement result to the user terminal 2. The blood sugar level data includes a user ID uniquely identifying the user U, a user name, a time when the blood sugar level is measured, and a specific numerical value indicating the blood sugar level. In addition, the specific example of blood glucose level data is later mentioned with reference to FIG. 4A.

The doctor terminal 4 is an information processing apparatus operated by the doctor D, and is configured of, for example, a personal computer. The doctor terminal 4 acquires the blood glucose level / meal graph transmitted from the server 1 based on the operation of the doctor D.
The dietitian terminal 5 is an information processing device operated by the dietitian M, and is configured of, for example, a personal computer. The dietitian terminal 5 acquires the blood sugar level / meal graph transmitted from the server 1 based on the operation of the managing dietitian M.

FIG. 2 is a block diagram showing the hardware configuration of the server 1 in the information processing system of FIG.

The server 1 includes a central processing unit (CPU) 11, a read only memory (ROM) 12, a random access memory (RAM) 13, a bus 14, an input / output interface 15, a touch operation input unit 16, and a display unit. A storage unit 19, a storage unit 19, a first communication unit 20, a second communication unit 21, a drive 22, and a removable medium 30 are provided.

The CPU 11 executes various processes in accordance with a program stored in the ROM 12 or a program loaded from the storage unit 19 into the RAM 13.
The RAM 13 appropriately stores information necessary for the CPU 11 to execute various processes.

The CPU 11, the ROM 12 and the RAM 13 are connected to one another via a bus 14. An input / output interface 15 is also connected to the bus 14. The touch operation input unit 16, the display unit 17, the input unit 18, the storage unit 19, the first communication unit 20, the second communication unit 21, and the drive 22 are connected to the input / output interface 15.

The touch operation input unit 16 is formed of, for example, a capacitive or resistive (pressure-sensitive) position input sensor stacked on the display unit 17, and detects coordinates of a position at which a touch operation is performed.
The display unit 17 is configured of a display such as liquid crystal and displays various images such as an image related to program preparation.
Thus, in the present embodiment, the touch operation input unit 16 and the display unit 17 constitute a touch panel.

The input unit 18 includes various hardware and the like, and inputs various information in accordance with a user's instruction operation.
The storage unit 19 is configured by a hard disk, a dynamic random access memory (DRAM), or the like, and stores various information.
For example, the first communication unit 20 executes control for performing near field wireless communication in a method according to the Bluetooth (registered trademark) standard. Specifically, for example, the blood glucose level data measured by the blood glucose level measuring device 3 is received by near field communication of a method according to the standard of Bluetooth (registered trademark).
The second communication unit 21 controls communication performed with another device (for example, the user terminal 2, the doctor terminal 4, the dietitian terminal 5) separately from the first communication unit 20 independently of the first communication unit 20. .

The drive 22 is provided as needed. The removable medium 30 made of a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory or the like is appropriately attached to the drive 22. The program read from the removable media 30 by the drive 22 is installed in the storage unit 19 as necessary.
The removable media 30 can also store various information stored in the storage unit 19 in the same manner as the storage unit 19.

Although not shown, in the information processing system of FIG. 1, the user terminal 2, the doctor terminal 4 and the dietitian terminal 5 also have basically the same hardware configuration as the hardware configuration shown in FIG. .

Next, the functional configuration of the server 1 having such a hardware configuration will be described with reference to FIG.
FIG. 3 shows an example of a functional configuration for realizing graph generation processing, graph display control processing, and alert output processing among the functional configurations of the server 1 of FIG. 2 in the information processing system of FIG. It is a functional block diagram.

The “graph generation process” refers to a series of processes until the user U's blood glucose level / meal graph is generated among the processes executed by the server 1.
The “graph display control process” causes the user terminal 2, the doctor terminal 4, and the dietitian terminal 5 to display the blood sugar level / meal graph of the user U generated in the graph generation process among the processes executed by the server 1. The process of executing control.
The “alert output process” is a series of processes for causing the user terminal 2 to output an alert at a predetermined timing based on various data serving as the basis of the blood sugar level / meal graph of the user U among the processes executed by the server 1. The process of

As shown in FIG. 3, in the CPU 11 (FIG. 2) of the server 1, when the graph generation processing is executed, the blood glucose level data acquisition unit 101, the meal data management unit 102, and the graph generation unit 103 Function.
When the graph display control process is executed, the graph display control unit 104 functions.
When the alert output process is executed, the activity data acquisition unit 105, the data analysis unit 106, and the alert management unit 107 function.
In addition, blood glucose level DB401, meal DB402, graph DB403, and activity DB404 are provided in one area | region of the memory | storage part 19 (FIG. 2).

The blood sugar level data acquisition unit 101 acquires the blood sugar level data transmitted from the user terminal 2. The timing at which the blood sugar level data acquisition unit 101 acquires blood sugar level data is not particularly limited. For example, when blood sugar level data is acquired by the user terminal 2, the blood sugar level data may be acquired in real time, every s seconds (s is an arbitrary integer value of 1 or more), every m minutes (m is 1) The blood sugar level data may be acquired at any timing such as the above arbitrary integer value) and every h hours (h is an arbitrary integer value of 1 or more). The blood glucose level data acquired by the blood glucose level data acquisition unit 101 is stored and managed in the blood glucose level DB 401. A specific example of the blood sugar level data will be described later with reference to FIG. 4A.

The meal data management unit 102 acquires the meal data transmitted from the user terminal 2, analyzes the meal image data included in the meal data, and extracts detailed information. The detailed information may include any information on the user U's meal. For example, the name of the dish, the place where the dish is provided or the name of the shop, the food used, and information on nutrition such as the amount of sugar and calories may be included. In addition, the analysis method of the data of the image by the server 1 is not specifically limited. For example, analysis of image data may be performed using artificial intelligence (AI) which has previously learned detailed information of various dishes. Further, the timing at which the meal data management unit 102 acquires meal data is not particularly limited. For example, when the contents of the meal are imaged by the user terminal 2, the meal data may be acquired in real time, or even if the meal data of d days (d is an arbitrary integer value of 1 or more) is acquired collectively Good. The detailed information on the meal extracted from the meal data by the meal data management unit 102 is stored in the meal DB 402 and managed. In addition, the specific example of the detailed information regarding the meal extracted from meal data is later mentioned with reference to FIG. 4B.

The graph generation unit 103 generates a blood glucose level / meal graph based on the blood glucose level data acquired by the blood glucose level data acquisition unit 101 and the meal data acquired by the meal data management unit 102 and for which detailed information is extracted. . Thereby, the blood glucose level / meal graph generated by the graph generation unit 103 is stored in the graph DB 403 and managed.

The graph display control unit 104 executes control to display the blood sugar level / meal graph generated by the graph generation unit 103 on the user terminal 2, the doctor terminal 4, and the dietitian terminal 5. As a result, the user U, the doctor D, and the dietetic dietitian M can easily grasp the relationship between the blood glucose level and the content of the subject's meal of the blood glucose level. In addition, the specific example of the blood glucose level / meal graph displayed on user terminal 2 grade | etc., Is later mentioned with reference to FIG.

The activity data acquisition unit 105 acquires temporal information on the activity of the user U as activity data. The activity data at least includes the past schedule of the user U. Therefore, by referring to the activity data, it becomes possible to grasp what action the user U has taken in a certain day at a certain time. The specific method for acquiring activity data is not particularly limited. For example, the schedule of the user U stored and managed by the general schedule management function of the user terminal 2 may be acquired as activity data. Alternatively, for example, information input to the user terminal 2 by the user U may be acquired as activity data. The activity data acquired by the activity data acquisition unit is stored in the activity DB 404 and managed.

The data analysis unit 106 analyzes the influence of the contents of the meal of the user U and the contents of the activity on the change of the blood glucose level, based on the blood glucose level data, the diet data, and the activity data. The analysis method of various data by the data analysis unit 106 is not particularly limited. For example, artificial intelligence (AI) may be used to analyze various data. The blood sugar level data, the meal data, and the activity data are accumulated, thereby increasing the credibility as information indicating the characteristic of the user U's constitution. That is, if you take such kind of meal at such a timing, your blood sugar level tends to rise, or if you take such kind of meal at this timing, your blood sugar level does not rise so much , The characteristics of the constitution of the user U are gradually clarified. Therefore, the result of analyzing the blood sugar level data, the meal data, and the activity data of the user U accumulated in the server 1 can be used as effective information for maintaining the health of the user U. That is, the result of analysis by the data analysis unit 106 (hereinafter referred to as “analysis data”) is used as information for supporting health guidance of the user U by the doctor D and nutrition guidance of the user U by the management dietitian M. Can.
The analysis data is also used when generating alert information to be described later, which is output from the user terminal 2.

Based on the analysis data, the alert management unit 107 generates alert information including at least notes on the meal that the user U intends to ingest, and notes on the activity of the user U. The alert management unit 107 also executes control to cause the user terminal 2 to output the generated alert information. As a result, the user U can know in advance a food material that may cause the blood sugar level to rise rapidly and an activity that may cause the blood sugar level to rise rapidly.
For example, it is assumed that the analysis data includes information that the user U's blood glucose level tends to rise sharply when eating a dish containing soymilk within a predetermined time after getting up. In this case, if soymilk is included in the meal data of the breakfast transmitted in real time at the time of the breakfast of the user U, the alert management unit 107 executes the following process. That is, the alert management unit 107 generates alert information indicating that soymilk having a tendency to rapidly increase the blood sugar level is included in the breakfast of the user U, and controls the user terminal 2 to output the alert information. Run. By this, the user U can know that soymilk, which tends to raise the blood sugar level rapidly, is included in the breakfast before eating the breakfast.
Also, for example, if the analysis data shows that the probability that the user U takes a bath between 21:00 and 22:00 is 88% and the blood sugar level of the user U drinks beer within a predetermined time after bathing It is assumed that information is included that the information tends to rise sharply. In this case, the alert management unit 107 has alert information indicating that the beer U tends to rise sharply when drinking beer within a predetermined time after bathing at around 20:30, which is likely to be immediately before the user U takes a bath. The generation and control for causing the user terminal 2 to output the alert information are executed. Thereby, the user U can know immediately before bathing that, after taking a bath, drinking beer in a predetermined time tends to rapidly raise the blood sugar level.
Thus, the analysis data not only plays a role in supporting various instruction to the user U by the doctor D and the dietitian M, but also plays a role as a material for generating alert information output from the user terminal 2 .

Next, specific examples of various data stored and managed in each of the blood sugar level DB 401, the meal DB 402, the graph DB 403, and the activity DB 404 will be described with reference to FIGS. 4A and 4B.
FIGS. 4A and 4B are diagrams showing specific examples of various data stored and managed in each of the blood sugar level DB 401, the meal DB and the meal DB 402. FIG.

FIG. 4A is a diagram showing a specific example of blood glucose level data stored and managed in the blood glucose level DB 401. In the example shown in FIG. 4A, it is assumed that the blood glucose level of the user U is continuously measured every 10 minutes for 24 hours.
As shown in FIG. 4A, the blood glucose level data includes at least a user ID uniquely identifying the user U, a user name, a date and time when the blood glucose level was measured, and a specific numerical value indicating the blood glucose level. . Specifically, for example, it is stored as blood glucose level data that the blood glucose level at “July 1, 2017 16:30” of “user U1” with user ID “01234” is “95 mg / dL”. ing. In addition, it is stored that the blood glucose level at the time of "July 1, 2017 16:40" of the user U1 is "97 mg / dL". Thus, the blood glucose level data is managed over time. The details of the blood glucose level of the user U1 at another measurement time are as shown in FIG. 4A.

FIG. 4B is a diagram showing a specific example of meal data stored and managed in the meal DB 402. As shown in FIG.
As shown in FIG. 4B, the meal DB 402 includes temporal information on the meal contents of the user U. That is, the meal data includes a user ID uniquely identifying the user U, the user name, the date and time when the user U started taking the intake, information on the place where the food was provided, the dish name, the meal image data, , Contains information on nutrition contained in the dish.
Specifically, for example, “Ochazuke”, which the user U1 ingested at “7:00” on “July 1, 2017” at “home”, has “60.0 g” of carbohydrate and “282 kcal” in calories include. In addition, “Miso ramen” consumed by user U1 at “1 2:00” on “July 1, 2017” at “○」 ken ”contains 80.0 g of sugar and 625 kcal of calories. include. The details of the other meal data are as shown in FIG. 4B.

Next, with reference to FIG. 5, graph generation processing executed by the server 1 having the functional configuration of FIG. 3 will be described.
FIG. 5 is a flowchart for explaining the flow of graph generation processing executed by the server 1 of FIG.

As shown in FIG. 5, the server 1 executes the following series of processing.
In step S1, the blood sugar level data acquisition unit 101 determines whether blood sugar level data has been transmitted from the user terminal 2.
Until blood sugar level data is transmitted from the user terminal 2, it is determined as NO in step S1, the process is returned to step S1, and the process of step S1 is repeated.
On the other hand, when blood glucose level data is transmitted from the user terminal 2, it is determined as YES in step S1, and the process proceeds to step S2.

In step S2, the meal data management unit 102 determines whether or not meal data has been transmitted from the user terminal 2.
Until meal data is transmitted from the user terminal 2, it is determined as NO in step S2, the process is returned to step S2, and the process of step S2 is repeated.
On the other hand, when meal data is transmitted from the user terminal 2, it is determined as YES in step S2, and the process proceeds to step S3.
In step S3, the meal data management unit 102 analyzes the meal image data included in the meal data to extract detailed information, and includes the detailed information in the meal data for management.
In step S4, the graph generation unit 103 uses the blood sugar level data acquired in the process of step S1 and the meal data acquired in the process of step S2 and in which the detailed information is extracted from the meal image data in the process of step S3. Based on the blood sugar level / meal graph is generated. This completes the graph generation process.

Next, with reference to FIG. 6, the specific example of the blood glucose level / meal graph produced | generated by the graph production | generation process which the server 1 of FIG. 3 performs is demonstrated.
FIG. 6 is an image diagram showing an example of a blood glucose level / meal graph generated by the graph generation process executed by the server 1 of FIG. 3.

As shown in FIG. 6, the blood glucose level / meal graph BF superimposes information F1 to F3 indicating the contents of the meal data based on the blood glucose level transition graph B showing the time-lapse numerical value of the user U's blood glucose level. It is displayed. Specifically, the blood glucose level / diet graph BF has a horizontal axis as a date and a vertical axis as a blood glucose level (unit: mg / dL) based on a blood glucose level transition graph B, the date and time when the meal was taken and Information F1 to F3 indicating contents are displayed in a superimposed manner. As a result, by looking at the blood glucose level / meal graph BF, it is possible to easily grasp the relationship between the contents of the dish actually consumed by the user U and the change in the blood glucose level of the user U.
Specifically, the blood glucose level of the user U is approximately 80 to 90 mg / dL from 0 o'clock to 7 o'clock on July 1, 2017. However, it reached about 160 mg / dL at about 8:00 immediately after taking tea pickling at home as breakfast at 7:00 on the same day, and reached about 170 mg / dL which is the peak value in the morning at 9:00. After that, the blood sugar level continues to decrease until 12 o'clock, but reaches around 170 mg / dL again at 13 o'clock immediately after consuming miso ramen at a ramen shop "○ 軒 ken" as lunch at 12 o'clock. After that, the blood sugar level continues to decrease until 18 o'clock, but at 19 o'clock immediately after taking a nape at an eels called "○ ○ ya" as dinner at 18 o'clock, 180 mg / dL which is the highest value on this day The degree has reached.
As described above, the blood glucose level / diet graph BF can be used as effective information when the doctor D or the registered dietitian M instructs the user U to perform various instructions. Specifically, for example, it can be assumed that the following health instruction is given from the doctor D to the user U:
That is, the doctor D confirms the blood sugar level / meal graph BF shown in FIG. 6, and the blood sugar level of the user U suddenly rises immediately after each of breakfast, lunch, and dinner, and peaks P1 to P3 are obtained. Understand that they are meeting each other. However, while peak P2 after lunch and peak P3 after dinner both arrive about 1 hour after the meal start, only breakfast peak P1 arrives about 2 hours after the meal start . Then, the doctor D confirms what kind of activity was performed after breakfast in the interview with the user U. On the other hand, the user U leaves his home at 8 o'clock for work after breakfast, but tells that he is commuting to work on foot for about an hour for health. Then, Doctor D checks the blood sugar level / meal graph again, and the user U's blood sugar level rapidly rises until 8:00, which is one hour after the start of breakfast, and then the inclination of the graph becomes gentle for one more hour. Confirm that peak P1 is reached by rising to time. Thereby, the doctor D estimates that the user U has a tendency to rise in blood sugar level when exercised after a meal, and performs treatment such as health guidance based on this estimation and further detailed examination. It can be taken.
As described above, from the blood sugar level / meal graph BF, the doctor D and the dietetic dietitian M can accurately give instructions for the user U for no disease and for beauty.

As mentioned above, although one Embodiment of this invention was described, this invention is not limited to the above-mentioned embodiment, A deformation | transformation in the range which can achieve the objective of this invention, improvement, etc. are included in this invention It is.

For example, in the embodiment described above, although detailed information extracted by analyzing meal image data is displayed on the blood glucose level / meal graph, only the meal image data is displayed without displaying the detailed information. May be In this case, the process of step S3 in the flowchart shown in FIG. 5 can be omitted. Even if only the meal image data is displayed on the blood sugar level / meal graph without displaying detailed information, it is possible to grasp the contents of most meals by looking at the meal image data It is.

In the above-described embodiment, the blood glucose level of the user U is continuously measured by the blood glucose level measuring device 3 every 10 minutes for 24 hours, but the timing at which the blood glucose level measuring device 3 measures the blood glucose level of the user U Is not particularly limited. The blood sugar level of the user U may be measured at any timing, such as every s seconds, every m minutes, every h hours, etc., as with the timing when the blood sugar level data acquisition unit 101 described above acquires blood sugar level data.

In the embodiment described above, the users of the blood sugar level / meal graph are the user U, the doctor D, and the management dietitian M, but these users are examples, and those in all positions have blood sugar level / meal It can be a subject of graph use. Specifically, for example, a family of user U, an exclusive trainer of a fitness club to which user U goes, etc. also uses the blood glucose level / meal graph by operating the information processing apparatus similar to the doctor terminal 4 or the dietitian terminal 5 be able to. Thereby, persons in all positions can be involved in the health of the user U.

Further, each hardware configuration shown in FIG. 2 is merely an example for achieving the object of the present invention, and is not particularly limited.

Further, the functional block diagram shown in FIG. 3 is merely an example and is not particularly limited. That is, it is sufficient if the information processing system is equipped with a function capable of executing the above-described series of processes as a whole, and what functional block is used to realize this function is not particularly limited to the example of FIG. .
Also, one functional block may be configured as a single piece of hardware or in combination with a single piece of software.

When the process of each functional block is to be executed by software, a program constituting the software is installed on a computer or the like from a network or a recording medium.
The computer may be a computer incorporated in dedicated hardware. In addition, the computer may be a computer capable of executing various functions by installing various programs, such as a general-purpose smartphone or personal computer other than a server.

A recording medium including such a program is distributed not only by a removable medium separately from the apparatus main body to provide the program to each user, but is configured not only by removable media but also by each user while being incorporated in the apparatus main body. It comprises the provided recording medium and the like.

In the present specification, in the step of describing the program to be recorded on the recording medium, the processing performed chronologically according to the order is, of course, parallel or individually not necessarily necessarily chronologically processing. It also includes the processing to be performed.
For example, in the graph generation process of FIG. 5 described above, meal data is transmitted after determination of whether blood sugar level data has been transmitted (determination in step S1 and hereinafter referred to as “first determination”). It is determined whether or not it has been received (this is the determination of step S2, hereinafter referred to as "the second determination"). However, at the time when the blood glucose level / meal graph is generated in server 1 (at the time of processing in step S4), “YES” is determined as each of the first determination and the second determination, and from meal image data It is sufficient if detailed information is extracted. Therefore, the timings of the first determination and the second determination are not particularly limited. The first determination and the second determination may be performed in parallel, respectively.

In summary, the information processing apparatus to which the present invention is applied only needs to have the following configuration, and various various embodiments can be taken.
That is, an information processing apparatus (for example, the server 1 in FIG. 1) to which the present invention is applied is
Blood glucose level data acquisition means (for example, the blood glucose level data acquisition unit 101 of FIG. 3) for acquiring blood glucose level data that is temporal information of the blood glucose level;
A meal data acquisition unit (e.g., the meal data management unit 102 in FIG. 3) for acquiring meal data that is temporal information related to the meal of the subject of the blood glucose level (e.g., the user U in FIG. 1);
A first graph showing temporal changes in blood glucose level of the subject based on the blood glucose level data acquired by the blood glucose level data acquiring unit and the meal data acquired by the meal data acquiring unit A second graph in which information indicating contents of the meal of the subject (for example, information F1 to F3 indicating contents of meal data of FIG. 6) is superimposed on (eg, blood sugar level transition graph B of FIG. 6) Graph generation means (for example, the graph generation unit 103) for generating (for example, the blood sugar level / meal graph BF in FIG. 6);
Equipped with
As a result, it is possible to generate a graph capable of grasping the relationship between the content of the meal consumed by the subject whose blood glucose level is ingested and the blood glucose level.

The meal data includes at least meal image data, which is data of an image obtained by capturing the content of the meal of the subject, and information on date and time when the image is captured,
Detailed information extraction means for extracting detailed information including at least information on used foodstuffs and sugar mass about the meal consumed by the subject by analyzing the meal image data (e.g. Part 102)
Can further be provided.
In this way, it is possible to generate a graph capable of grasping the relationship between the specific content including the detailed information of the meal consumed by the subject of the blood glucose level and the blood glucose level.

Also, an activity data acquisition unit (e.g., the activity data acquisition unit 105 in FIG. 3) that acquires activity data that is temporal information related to the activity of the subject.
Data analysis means for analyzing the influence of the contents of the meal of the subject and the contents of the activity on the change of the blood glucose level based on the blood glucose level data, the diet data, and the activity data (for example, FIG. 3) Data analysis unit 106) of
Based on analysis data obtained as a result of analysis by the data analysis means, alert information is generated including at least one of notes on the diet the subject is about to ingest, and notes on the activity of the subject. An alert management unit (for example, the alert management unit 107 in FIG. 3) that executes control to cause the information processing terminal operated by the subject to output the generated alert information;
Can further be provided.
As a result, the subject whose blood glucose level is to be measured can know in advance foods that may cause the blood glucose level to rise rapidly and activities that may cause the blood glucose level to rise rapidly.

1: Server 2: User terminal 3: Blood glucose meter 4: Doctor terminal 5: Nutritionist terminal 11: CPU
12: ROM
13: RAM
14: bus 15: input / output interface 16: touch operation input unit 17: display unit 18: input unit 19: storage unit 20: first communication unit 21: second communication unit 22: drive 30: removable media 101: blood glucose level data Acquisition unit 102: Meal data management unit 103: Graph generation unit 104: Graph display control unit 105: Activity data acquisition unit 106: Data analysis unit 107: Alert management unit 401: Blood glucose level DB
402: Meal DB
403: Graph DB
404: Activity DB
B: Blood glucose level graph BF: Blood glucose level / meal graph F1, F2, F3: Information indicating contents of meal data U: User N: Network

Claims

Blood glucose level data acquisition means for acquiring blood glucose level data, which is temporal information of blood glucose level,
A meal data acquisition unit that acquires meal data that is temporally information on the meal of the subject of the blood glucose level;
A first graph showing temporal changes in blood glucose level of the subject based on the blood glucose level data acquired by the blood glucose level data acquiring unit and the meal data acquired by the meal data acquiring unit A graph generation unit that generates a second graph in which information indicating the contents of the subject's meal is displayed in a superimposed manner;
An information processing apparatus comprising:
The meal data includes at least meal image data, which is data of an image obtained by capturing the content of the meal of the subject, and information on date and time when the image is captured,
The method according to claim 1, further comprising: detailed information extracting means for extracting detailed information including at least information on used foodstuffs and sugar amount about the meal consumed by the subject by analyzing the meal image data. Information processing equipment.
Activity data acquisition means for acquiring activity data, which is temporal information on the activity of the subject;
Data analysis means for analyzing the influence of the contents of the meal of the subject and the contents of the activity on the change of the blood glucose level based on the blood glucose level data, the meal data and the activity data;
Based on analysis data obtained as a result of analysis by the data analysis means, alert information is generated including at least one of notes on the diet the subject is about to ingest, and notes on the activity of the subject. An alert management unit that executes control to output the generated alert information to an information processing terminal operated by the subject;
The information processing apparatus according to claim 1, further comprising:
In an information processing method executed by an information processing apparatus,
A blood sugar level data acquisition step of acquiring blood sugar level data which is temporal information of the blood sugar level;
A meal data acquisition step of acquiring meal data, which is information with time of the subject's diet of the blood glucose level;
A first graph showing temporal changes in blood glucose level of the subject based on the blood glucose level data acquired in the blood glucose level data acquisition step and the meal data acquired in the meal data acquisition step A graph generating step of generating a second graph on which information indicating the contents of the subject's meal is displayed in a superimposed manner;
Information processing method including:
In a computer that controls an information processing apparatus,
A blood sugar level data acquisition step of acquiring blood sugar level data which is temporal information of the blood sugar level;
A meal data acquisition step of acquiring meal data, which is information with time of the subject's diet of the blood glucose level;
A first graph showing temporal changes in blood glucose level of the subject based on the blood glucose level data acquired in the blood glucose level data acquisition step and the meal data acquired in the meal data acquisition step A graph generating step of generating a second graph on which information indicating the contents of the subject's meal is displayed in a superimposed manner;
A program that executes control processing including