JP7032072B2 - Information processing equipment, information processing methods, and programs - Google Patents

Description

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

Conventionally, CGM (Continuous Glucose Monitoring) has existed as a method for continuously measuring the sugar concentration in the 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 based on the value of each of the plurality of pixels included in the specified meal portion. Is created, the number of color types included in the meal part is calculated based on the created color frequency distribution, the meal balance value is calculated based on the calculated number of color types, and the calculated meal balance value is output. An analyzer exists (see Patent Document 1).

Japanese Unexamined Patent Publication No. 2012-21249

Diabetes network (http://www.dm-net.co.jp/calendar/2013/020112.php)

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 ingested by the blood glucose subject and the blood glucose level.

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

In order to achieve the above object, the information processing apparatus according to one aspect of the present invention is
A blood glucose data acquisition means for acquiring blood glucose level data, which is information on the blood glucose level over time, and
A meal data acquisition means for acquiring meal data which is information on the meal of the blood glucose subject over time, and a meal data acquisition means.
A first graph showing changes over time in the blood glucose level of the subject based on the blood glucose level data acquired by the blood glucose level data acquisition means and the dietary data acquired by the dietary data acquisition means. A graph generation means for generating a second graph in which information indicating the contents of the meal of the person to be measured is superposedly displayed.
To prepare for.

Further, the meal data includes at least meal image data, which is image data obtained by capturing the contents of the meal of the person to be measured, and information on the date and time when the image was captured.
By analyzing the meal image data, it is possible to further provide a detailed information extraction means for extracting detailed information including at least information on the ingredients used and the sugar mass for the meal ingested by the subject.

An activity data acquisition means for acquiring activity data which is information on the activity of the person to be measured over time, and
A data analysis means for analyzing the influence of the dietary content and activity content of the subject on the change in blood glucose level based on the blood glucose level data, the dietary data, and the activity data.
Based on the analysis data that is the result of the analysis by the data analysis means, alert information including at least one of the precautions regarding the meal that the subject intends to ingest and the precautions regarding the activity of the subject is generated. Then, an alert management means for executing control to output the generated alert information to the information processing terminal operated by the person to be measured, and
Can be further prepared.

The information processing method and program according to one aspect of the present invention are the processing methods and programs corresponding to the above-mentioned information processing apparatus according to one aspect of the present invention.

According to the present invention, it is possible to grasp the relationship between the content of the meal ingested by the blood glucose subject and the blood glucose level. As a result, not only the blood glucose subject, but also doctors, registered dietitians, etc., have not yet been measured by the blood glucose subject based on the relationship between the content of the meal ingested by the blood glucose subject and the blood glucose level. It is possible to accurately give instructions for illness and beauty.

It is a block diagram of the information processing system including the server which is one Embodiment of the information processing apparatus of this invention. It is a block diagram which shows the hardware configuration of a server in the information processing system of FIG. It is a functional block diagram which shows an example of the functional configuration for realizing the graph generation processing among the functional configurations of the server of FIG. 2 in the information processing system of FIG. It is a figure which shows the specific example of various data stored and managed in the server of FIG. It is a flowchart explaining the flow of the graph generation process executed by the server of FIG. It is an image diagram which shows an example of the blood glucose level / meal graph generated by the graph generation process executed by the server of FIG.

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

FIG. 1 is a configuration 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 connecting a server 1, a user terminal 2, a doctor terminal 4, and a nutritionist terminal 5 to each other via a network N such as the Internet. Further, a blood glucose meter 3 is connected to the user terminal 2.

The user U is a person who operates the user terminal 2 and continuously measures his / her own blood glucose level for 24 hours by using the blood glucose level measuring device 3 connected to the user terminal 2. The user U is also a person who continuously images the contents of the meal of each meal by using the image pickup function of the user terminal 2.
The doctor D is a person who operates the doctor terminal 4 and gives health management guidance to the user U.
The registered dietitian M is a person who operates the dietitian terminal 5 and is a person who gives nutritional management guidance to the user U.

The server 1 is an information processing device that executes various processes in order to manage the operation of the user terminal 2. The server 1 has, for example, information on the blood glucose level of the user U over time (hereinafter referred to as “blood glucose level data”) and information on the contents of the meal of the user U over time (hereinafter referred to as “meal data”). Based on the above, a graph (hereinafter referred to as "blood glucose level / meal graph") showing the relationship between the content of each meal of the user U and the blood glucose level of the user U is generated. The meal data in the present embodiment includes at least image data (hereinafter referred to as "meal image data") in which the content of each meal of the user U is captured, and information on the date and time when the image was 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 dish, and the extracted detailed information is also meal data. Manage as.
Specifically, the blood glucose level / meal graph is based on the blood glucose level transition graph showing the time-dependent numerical value of the blood glucose level of the user U, and the information showing the contents of the meal data is superimposed and displayed. The food consumed by U and the change in blood glucose level of user U are visualized. Therefore, by looking at the blood glucose level / meal graph, it is possible to easily grasp the influence of the content of the meal ingested 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 about 80 to 100 mg / dL, but the blood glucose level after eating shows a slightly high value. That is, when the user U eats, carbohydrates are absorbed and become glucose, which appears in the blood. Therefore, the blood glucose level after eating is higher than the blood glucose level before eating. If the fasting blood glucose level of User U is 126 mg / dL or higher, or the postprandial blood glucose level is 200 mg / dL or higher, it is said that there is a strong suspicion of diabetes.
As described above, the blood glucose level is basically increased by the user U ingesting a meal. However, it is said that the degree of increase in the blood glucose level of the user U varies 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 the meal.
For example, even if "udon", "pasta", and "polished rice" have the same carbohydrate content, the blood glucose level is high only when "polished rice" is ingested, depending on the constitution of the user U who eats these. May rise. In addition, even when the user U ingests "Gyudon Namimori" of A beef bowl shop and "Gyudon Namimori" of B beef bowl shop at the same timing, there is a big difference in the increase in blood glucose level. May occur.
Further, for example, there may be a large difference in the increase in blood glucose level between the case where the user U eats the same "udon" at lunch and the case where the user U eats it at dinner. In addition, even if the same type of "udon" is ingested at the same time, there is a large difference in the increase in blood glucose level between the case of exercising before eating and the case of not exercising. May occur.

That is, the doctor D and the registered dietitian M provide accurate health guidance and nutritional guidance to the user U simply by grasping general information such as the content of nutrients such as carbohydrates contained in the diet of the user U. Can't. That is, in order for the doctor D and the registered dietitian M to provide appropriate health guidance and nutritional guidance to the user U, various factors such as the content of the meal of the user U and the timing of the meal must be fully considered. ..
Regarding this point, in the blood glucose level / meal graph generated by the server 1 of FIG. 1, the contents of the meal of the user U and the timing of the meal are "visualized". Therefore, the doctor D and the registered dietitian M can easily grasp the relationship between the content of the meal ingested by the user U and the timing of the meal and the change in the blood glucose level just by looking at the blood glucose level / meal graph. can.
As a result, the doctor D and the registered dietitian M can give accurate health guidance to the user U simply by asking the user U about the past activity contents of the user U while looking at the blood glucose level / meal graph. can. Specifically, for example, when the user U can understand from the contents of the blood glucose level / meal graph and the result of the medical examination that the user U has a constitution in which the increase in the blood glucose level is smaller when exercising after the meal than when exercising before the meal. There is. In this case, the doctor D can give the user U health guidance to the effect that he / she should exercise after eating as much as possible.
Also, for example, just by looking at the blood glucose level / meal graph, the blood glucose level tends to rise significantly only when the user U ingests "white rice" out of "udon", "pasta", and "white rice". It may be possible to grasp. In this case, the registered dietitian M can give nutritional guidance to the user U that carbohydrates should be ingested from noodles such as udon and pasta as much as possible.
In addition, not only doctor D and registered dietitian M, but also user U himself can see when the blood glucose level is likely to rise and when it is difficult for the user U to rise just by looking at the blood glucose level / meal graph. You can easily grasp the peculiar constitution and tendency.
A specific example of the blood glucose level / meal graph will be described later with reference to FIG.

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

The blood glucose meter 3 is an electronic device for the user U to continuously measure his / her own blood glucose level. The blood glucose meter 3 and the user terminal 2 are connected by using a short-range wireless communication technology such as Bluetooth (registered trademark) or a wire such as a cable. The blood glucose meter 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 glucose level data includes a user ID that uniquely identifies the user U, a user name, a time when the blood glucose level is measured, and a specific numerical value indicating the blood glucose level. A specific example of blood glucose level data will be described later with reference to FIG.

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

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

The server 1 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a bus 14, an input / output interface 15, a touch operation input unit 16, and a display unit. It includes 17, an input unit 18, a storage unit 19, a first communication unit 20, a second communication unit 21, a drive 22, and a removable media 30.

The CPU 11 executes various processes according to the program recorded in the ROM 12 or the program loaded from the storage unit 19 into the RAM 13.
Information and the like necessary for the CPU 11 to execute various processes are also appropriately stored in the RAM 13.

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

The touch operation input unit 16 is composed of, for example, a capacitance type or resistance film type (pressure sensitive type) position input sensor laminated on the display unit 17, and detects the coordinates of the position where the touch operation is performed.
The display unit 17 is composed of a display such as a liquid crystal display, and displays various images such as an image related to program production.
As described above, in the present embodiment, the touch panel is composed of the touch operation input unit 16 and the display unit 17.

The input unit 18 is composed of various hardware and the like, and inputs various information according to a user's instruction operation.
The storage unit 19 is composed of a hard disk, a DRAM (Dynamic Random Access Memory), or the like, and stores various information.
The first communication unit 20 executes control for short-range wireless communication, for example, by a method according to the standard of Bluetooth (registered trademark). Specifically, for example, the blood glucose level data measured by the blood glucose level measuring device 3 is received by short-range wireless communication in a method according to the standard of Bluetooth (registered trademark).
The second communication unit 21 controls communication with other devices (for example, a user terminal 2, a doctor terminal 4, a dietitian terminal 5) via the Internet or the like, separately from the first communication unit 20. ..

The drive 22 is provided as needed. A removable medium 30 made of a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is appropriately mounted on the drive 22. The program read from the removable media 30 by the drive 22 is installed in the storage unit 19 as needed.
Further, 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, among the information processing systems of FIG. 1, the user terminal 2, the doctor terminal 4, and the nutritionist 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 a graph generation process, a graph display control process, and an alert output process among the functional configurations of the server 1 of FIG. 2 in the information processing system of FIG. 1. It is a functional block diagram.

The “graph generation process” refers to a series of processes executed by the server 1 up to the generation of the blood glucose level / meal graph of the user U.
The "graph display control process" is to display the blood glucose level / meal graph of the user U generated by the graph generation process on the user terminal 2, the doctor terminal 4, and the dietitian terminal 5 among the processes executed by the server 1. The process of executing control.
The "alert output process" is a series of processes executed by the server 1 until the user terminal 2 outputs an alert at a predetermined timing based on various data that are the basis of the blood glucose level / meal graph of the user U. Refers to the processing of.

As shown in FIG. 3, in the CPU 11 (FIG. 2) of the server 1, when the graph generation process is executed, the blood glucose level data acquisition unit 101, the meal data management unit 102, and the graph generation unit 103 Function.
Further, when the graph display control process is executed, the graph display control unit 104 functions.
Further, 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.
A blood glucose level DB 401, a meal DB 402, a graph DB 403, and an activity DB 404 are provided in one area of the storage unit 19 (FIG. 2).

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

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 regarding User U's diet. For example, the name of the dish, the name of the place or store where the dish was provided, the ingredients used, information on nutrition such as sugar mass and calories may be included. The method for analyzing image data by the server 1 is not particularly limited. For example, image data may be analyzed using artificial intelligence (AI) in which detailed information of various dishes is learned in advance. Further, the timing at which the meal data management unit 102 acquires the meal data is not particularly limited. For example, the meal data may be acquired in real time when the contents of the meal are imaged by the user terminal 2, or the meal data for d days (d is an arbitrary integer value of 1 or more) may be collectively acquired. good. Detailed information about the meal extracted from the meal data by the meal data management unit 102 is stored and managed in the meal DB 402. A specific example of detailed information on the meal extracted from the meal data will be described later with reference to FIG.

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 from which detailed information is extracted. .. As a result, the blood glucose level / meal graph generated by the graph generation unit 103 is stored and managed in the graph DB 403.

The graph display control unit 104 executes control to display the blood glucose 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 registered dietitian M can easily grasp the relationship between the dietary content of the blood glucose subject and the blood glucose level. A specific example of the blood glucose level / meal graph displayed on the user terminal 2 or the like will be described later with reference to FIG.

The activity data acquisition unit 105 acquires information over time regarding the activity of the user U as activity data. The activity data includes at least the user U's past schedule. Therefore, by referring to the activity data, it is possible to grasp what kind of action the user U has taken at a certain time on a certain day. 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 provided in the user terminal 2 may be acquired as activity data. Further, for example, the 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 and managed in the activity DB 404.

The data analysis unit 106 analyzes the influence of the user U's dietary content and activity content on the change in blood glucose level based on the blood glucose level data, the dietary data, and the activity data. The method for analyzing various data by the data analysis unit 106 is not particularly limited. For example, various data may be analyzed using artificial intelligence (AI). By accumulating blood glucose level data, meal data, and activity data, the credibility of the information indicating the characteristics of the constitution of the user U becomes high. That is, if you eat these kinds of meals at these timings, your blood sugar level tends to rise, or if you eat these kinds of meals at these timings, your blood sugar levels do not rise so much. , The characteristics of the constitution of the user U are gradually clarified. Therefore, the result of analyzing the blood glucose level data, the meal data, and the activity data of the user U stored in the server 1 can be used as effective information for maintaining the health of the user U. That is, the result of the analysis by the data analysis unit 106 (hereinafter referred to as "analysis data") is used as information for supporting the health guidance of the user U by the doctor D and the nutritional guidance of the user U by the registered dietitian M. Can be done.
The analysis data is also used when generating alert information, which will 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 regarding the meal that the user U intends to ingest and notes regarding the activity of the user U. Further, the alert management unit 107 executes control to output the generated alert information to the user terminal 2. As a result, the user U can know in advance the foodstuffs that may cause the blood glucose level to rise sharply and the activities that may cause the blood glucose level to rise sharply.
For example, suppose that the analysis data contains information that the blood glucose level of the user U tends to rise sharply when a dish containing soymilk is eaten within a predetermined time after waking up. In this case, if soymilk is included in the meal data of the breakfast transmitted in real time at the time of breakfast of the user U, the alert management unit 107 executes the following processing. That is, the alert management unit 107 controls to generate alert information indicating that the breakfast of the user U contains soymilk that tends to raise the blood glucose level sharply, and to output the alert information to the user terminal 2. Execute. As a result, the user U can know that soymilk, which tends to raise the blood sugar level sharply, is contained in the breakfast before eating the breakfast.
Further, for example, if the analysis data shows that the user U has an 88% probability of taking a bath between 21:00 and 22:00 and that the blood glucose level of the user U drinks beer within a predetermined time after taking a bath. Suppose that it contains information that it tends to rise sharply. In this case, the alert management unit 107 indicates that the alert information tends to rise sharply if the user U drinks beer within a predetermined time after bathing around 20:30, which is likely to be just before bathing. The generation and the control to output the alert information to the user terminal 2 are executed. As a result, the user U can know immediately before taking a bath that the blood glucose level tends to rise sharply when the beer is drunk within a predetermined time after taking a bath.
In this way, the analysis data not only plays a role of supporting various guidances to the user U by the doctor D and the registered dietitian M, but also plays a role as a material for generating alert information output from the user terminal 2. ..

Next, with reference to FIG. 4, specific examples of various data stored and managed in the blood glucose level DB 401, the meal DB and 402, the graph DB 403, and the activity DB 404 will be described.
FIG. 4 is a diagram showing specific examples of various data stored and managed in the blood glucose level DB 401 and the meal DB and 402 respectively.

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 a user ID that uniquely identifies 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. At least included. Specifically, for example, it is stored as blood glucose level data that the blood glucose level of "User U1" whose user ID is "01234" at "16:30 on July 1, 2017" is "95 mg / dL". ing. Further, it is remembered that the blood glucose level of the user U1 at "16:40 on July 1, 2017" is "97 mg / dL". In this way, blood glucose level data is managed over time. The details of the blood glucose level of the user U1 at other measurement times are as shown in FIG. 4 (A).

FIG. 4B is a diagram showing a specific example of meal data stored and managed in the meal DB 402.
As shown in FIG. 4B, the meal DB 402 contains time-dependent information regarding the meal content of the user U. That is, the meal data includes a user ID that uniquely identifies the user U, a user name, information on the date and time when the user U started ingestion, information on the place where the food was served, the food name, and meal image data. Contains information about the nutrition contained in the dish.
Specifically, for example, the "Ochazuke" that the user U1 ingested at "home" at "7:00" on "July 1, 2017" has "60.0 g" of sugar and "282 kcal" of calories. include. In addition, the "miso ramen" that user U1 ingested at "○○ eken" at "12:00" on "July 1, 2017" has "80.0 g" of sugar and "625 kcal" of calories. include. The details of other meal data are as shown in FIG. 4 (B).

Next, with reference to FIG. 5, the graph generation process executed by the server 1 having the functional configuration of FIG. 3 will be described.
FIG. 5 is a flowchart illustrating a 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 processes.
In step S1, the blood glucose level data acquisition unit 101 determines whether or not the blood glucose level data has been transmitted from the user terminal 2.
Until the blood glucose level data is transmitted from the user terminal 2, it is determined to be NO in step S1, the process is returned to step S1, and the process of step S1 is repeated.
On the other hand, when the blood glucose level data is transmitted from the user terminal 2, it is determined to be YES in step S1, and the process proceeds to step S2.

In step S2, the meal data management unit 102 determines whether or not the meal data has been transmitted from the user terminal 2.
Until the meal data is transmitted from the user terminal 2, it is determined to be NO in step S2, the process is returned to step S2, and the process of step S2 is repeated.
On the other hand, when the meal data is transmitted from the user terminal 2, it is determined to be YES in step S2, and the process proceeds to step S3.
In step S3, the meal data management unit 102 extracts detailed information by analyzing the meal image data included in the meal data, and manages the detailed information by including it in the meal data.
In step S4, the graph generation unit 103 combines the blood glucose level data acquired in the process of step S1 and the meal data acquired in the process of step S2 and whose detailed information is extracted from the meal image data in the process of step S3. Based on this, a blood glucose level / meal graph is generated. This ends the graph generation process.

Next, with reference to FIG. 6, a specific example of the blood glucose level / meal graph generated by the graph generation process executed by the server 1 of FIG. 3 will be described.
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.

As shown in FIG. 6, the blood glucose level / meal graph BF superimposes information F1 to F3 indicating the contents of meal data on the basis of the blood glucose level transition graph B showing the time-dependent numerical value of the blood glucose level of the user U. It is displayed. Specifically, the blood glucose level / meal graph BF is based on the blood glucose level transition graph B in which the horizontal axis is the date and time and the vertical axis is the blood glucose level (unit: mg / dL). Information F1 to F3 indicating the contents are displayed in a superimposed manner. Thereby, at a glance of the blood glucose level / meal graph BF, the relationship between the content of the food actually ingested by the user U and the change in the blood glucose level of the user U can be easily grasped.
Specifically, the blood glucose level of the user U has been changing at about 80 to 90 mg / dL from 0:00 to 7:00 on July 1, 2017. However, it reached about 160 mg / dL at 8 o'clock immediately after ingesting Ochazuke for breakfast at 7 o'clock on the same day, and reached the peak value of 170 mg / dL in the morning at 9 o'clock. After that, the blood glucose level continued to drop until 12 o'clock, but reached about 170 mg / dL again at 13:00 immediately after ingesting miso ramen at a ramen shop called "○○ ken" for lunch at 12 o'clock. After that, the blood glucose level continued to fall until 18:00, but at 19:00 immediately after ingesting eel at a eel shop called "○○ ya" at 18:00, the highest value of the day was 180 mg / dL. Has reached the degree.
As described above, the blood glucose level / meal graph BF can be used as effective information when various instructions are given to the user U by the doctor D and the registered dietitian M. Specifically, for example, it can be assumed that the following health guidance is given from the doctor D to the user U.
That is, by checking the blood glucose level / meal graph BF shown in FIG. 6, the doctor D rapidly increases the blood glucose level of the user U immediately after each of breakfast, lunch, and dinner, and peaks P1 to P3. Know that you are welcoming each. However, while the peak P2 after lunch and the peak P3 after dinner both arrive about 1 hour after the start of the meal, only the peak P1 of breakfast arrives about 2 hours after the start of the meal. .. Therefore, 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 to go to work after breakfast, but tells him that he is commuting to work for about an hour on foot for the sake of his health. Then, Doctor D checks the blood glucose level / meal graph again, and the blood glucose level of User U rises sharply until 8 o'clock, which is 1 hour after the start of breakfast, and then the slope of the graph becomes gentle for another 1 hour, but 9 Confirm that the peak P1 is reached by rising until time. As a result, the doctor D presumes that the user U has a constitution in which the blood glucose level tends to rise when exercising after eating, and takes measures such as health guidance based on this presumption and further detailed examination. Can be taken.
In this way, from the blood glucose level / meal graph BF, the doctor D and the registered dietitian M can accurately give instructions for pre-illness and beauty in the user U.

Although one embodiment of the present invention has been described above, the present invention is not limited to the above-described embodiment, and modifications, improvements, etc. within the range in which the object of the present invention can be achieved are included in the present invention. Is.

For example, in the above-described embodiment, the blood glucose level / meal graph displays the detailed information extracted by analyzing the meal image data, but the detailed information is not displayed and only the meal image data is displayed. You may. In this case, the process of step S3 in the flowchart shown in FIG. 5 can be omitted. Even if the detailed information is not displayed and only the meal image data is displayed on the blood glucose level / meal graph, it is possible to grasp the contents of most meals by looking at the meal image data. Is.

Further, in the above-described embodiment, the blood glucose level of the user U is continuously measured every 10 minutes for 24 hours by the blood glucose meter 3, but the timing at which the blood glucose meter 3 measures the blood glucose level of the user U. Is not particularly limited. Similar to the timing at which the blood glucose level data acquisition unit 101 acquires the blood glucose level data, the blood glucose level of the user U may be measured at any timing such as every s seconds, every m minutes, and every h hours.

Further, in the above-described embodiment, the user U, the doctor D, and the registered dietitian M are the users of the blood glucose level / meal graph, but these user subjects are examples, and a person in every position has a blood glucose level / meal. It can be the main user of the graph. Specifically, for example, the family of user U and the exclusive trainer of the fitness club to which user U attends also use the blood glucose level / meal graph by operating the same information processing device as the doctor terminal 4 and the dietitian terminal 5. be able to. This allows anyone in any position to be involved in the health of 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 suffices if the information processing system is provided with a function capable of executing the above-mentioned series of processes as a whole, and what kind of functional block is used to realize this function is not particularly limited to the example of FIG. ..
Further, one functional block may be configured by a single hardware or a combination of a single software.

When the processing of each functional block is executed by software, the programs constituting the software are installed in a computer or the like from a network or a recording medium.
The computer may be a computer embedded in dedicated hardware. Further, the computer may be a computer capable of executing various functions by installing various programs, for example, a general-purpose smartphone or a personal computer in addition to a server.

The recording medium containing such a program is not only composed of removable media, which is distributed separately from the main body of the device to provide the program to each user, but also is preliminarily incorporated in the main body of the device to each user. It is composed of the provided recording media and the like.

In this specification, the steps for describing a program to be recorded on a recording medium are not only processed in chronological order but also in parallel or individually, even if they are not necessarily processed in chronological order. It also includes the processing to be executed.
For example, in the graph generation process of FIG. 5 described above, meal data is transmitted after determination of whether or not blood glucose level data has been transmitted (determination in step S1, hereinafter referred to as “first determination”). It is determined whether or not the data has been received (determination in step S2, hereinafter referred to as "second determination"). However, at the time when the blood glucose level / meal graph is generated on the server 1 (the processing time in step S4), the determination of "YES" is made for each of the first determination and the second determination, and the meal image data is used. It suffices if detailed information is extracted. Therefore, the timings of the first determination and the second determination are not particularly limited. Further, 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 may have the following configurations, and various embodiments can be taken.
That is, the information processing apparatus to which the present invention is applied (for example, the server 1 in FIG. 1) is
A blood glucose level data acquisition means (for example, blood glucose level data acquisition unit 101 in FIG. 3) for acquiring blood glucose level data which is information on the blood glucose level over time, and
A meal data acquisition means (for example, the meal data management unit 102 in FIG. 3) for acquiring meal data which is information on the meal of the person whose blood glucose level is to be measured (for example, the user U in FIG. 1) over time.
A first graph showing a change over time in the blood glucose level of the subject based on the blood glucose level data acquired by the blood glucose level data acquisition means and the dietary data acquired by the dietary data acquisition means. (For example, the blood glucose level transition graph B in FIG. 6) is superposed with information indicating the contents of the meal of the subject (for example, information F1 to F3 showing the contents of the meal data in FIG. 6). (For example, a graph generation means (for example, graph generation unit 103) for generating (for example, blood glucose level / meal graph BF in FIG. 6) and
To prepare for.
This makes it possible to generate a graph capable of grasping the relationship between the content of the meal ingested by the blood glucose subject and the blood glucose level.

The meal data includes at least meal image data, which is image data obtained by capturing the contents of the meal of the person to be measured, and information on the date and time when the image was captured.
Detailed information extraction means (for example, meal data management in FIG. 3) for extracting detailed information including at least information on the ingredients used and the amount of sugar for the meal ingested by the subject by analyzing the meal image data. Part 102)
Can be further prepared.
As a result, it is possible to generate a graph capable of grasping the relationship between the specific content including the detailed information of the meal ingested by the blood glucose subject and the blood glucose level.

Further, an activity data acquisition means (for example, the activity data acquisition unit 105 in FIG. 3) for acquiring activity data which is information on the activity of the person to be measured over time, and
Based on the blood glucose level data, the dietary data, and the activity data, a data analysis means for analyzing the influence of the dietary content and activity content of the subject on the change in blood glucose level (for example, FIG. 3). Data analysis unit 106) and
Based on the analysis data that is the result of the analysis by the data analysis means, alert information including at least one of the precautions regarding the meal that the subject intends to ingest and the precautions regarding the activity of the subject is generated. An alert management means (for example, the alert management unit 107 in FIG. 3) that executes control to output the generated alert information to the information processing terminal operated by the person to be measured.
Can be further prepared.
As a result, the person to be measured for the blood glucose level can know in advance the foodstuffs that may cause the blood glucose level to rise sharply and the activities that may cause the blood glucose level to rise sharply.

1: Server 2: User terminal 3: Blood glucose meter 4: Doctor terminal 5: Dietitian 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 the contents of meal data U: User N: Network

Claims (6)

A blood glucose data acquisition means for acquiring blood glucose level data, which is information on the blood glucose level of the subject over time, and
A meal data acquisition means for acquiring meal data, which is information on the meal of the subject over time, and
An activity data acquisition means for acquiring activity data which is information over time regarding a plurality of activities including meal intake of the person to be measured, and an activity data acquisition means.
Based on the blood glucose level data, the dietary data, and the activity data, as an analysis of the influence of a predetermined relationship between the dietary content and the activity content of the subject on the change in blood glucose level. A data analysis means for at least analyzing a combination of a predetermined activity and a predetermined diet that raises the blood glucose level for the person to be measured .
Based on the activity data and the analysis data that is the result of the analysis by the data analysis means, alert information including the notes regarding the combination of the predetermined activity and the predetermined meal is generated as the notes regarding the predetermined relationship. An alert management means for executing control to output the generated alert information to the information processing terminal operated by the subject at a predetermined timing before the time when the predetermined activity is predicted to be performed.
Information processing device equipped with. The meal data includes information on at least one of the place where the food was served and the name of the store.
The information processing apparatus according to claim 1. A first graph showing changes over time in the blood glucose level of the subject based on the blood glucose level data acquired by the blood glucose level data acquisition means and the dietary data acquired by the dietary data acquisition means. A graph generation means for generating a second graph in which information indicating the contents of the meal of the person to be measured is superimposed and displayed.
The information processing apparatus according to claim 1 or 2, further comprising. The meal data includes at least meal image data, which is image data obtained by capturing the contents of the meal of the person to be measured, and information on the date and time when the image was captured.
Claims 1 to 3 further include a detailed information extraction means for extracting detailed information including at least information on the ingredients used and the sugar mass of the meal ingested by the subject by analyzing the meal image data. The information processing apparatus according to any one of the above. In the information processing method executed by the information processing device
A blood glucose data acquisition step for acquiring blood glucose level data, which is information on the blood glucose level of the subject over time, and
A meal data acquisition step for acquiring meal data, which is information on the meal of the subject over time, and
The activity data acquisition step for acquiring activity data which is information over time regarding a plurality of activities including the food intake of the person to be measured, and the activity data acquisition step.
Based on the blood glucose level data, the dietary data, and the activity data, as an analysis of the influence of a predetermined relationship between the dietary content and the activity content of the subject on the change in blood glucose level. A data analysis means for at least analyzing a combination of a predetermined activity and a predetermined diet that raises the blood glucose level for the person to be measured .
Based on the activity data and the analysis data that is the result of the analysis by the data analysis means, alert information including the notes regarding the combination of the predetermined activity and the predetermined meal is generated as the notes regarding the predetermined relationship. An alert management step that executes control to output the generated alert information to the information processing terminal operated by the subject at a predetermined timing before the time when the predetermined activity is predicted to be performed.
Information processing methods including. For computers that control information processing equipment
A blood glucose data acquisition step for acquiring blood glucose level data, which is information on the blood glucose level of the subject over time, and
A meal data acquisition step for acquiring meal data, which is information on the meal of the subject over time, and
The activity data acquisition step for acquiring activity data which is information over time regarding a plurality of activities including the food intake of the person to be measured, and the activity data acquisition step.
Based on the blood glucose level data, the dietary data, and the activity data, as an analysis of the influence of a predetermined relationship between the dietary content and the activity content of the subject on the change in blood glucose level. A data analysis means for at least analyzing a combination of a predetermined activity and a predetermined diet that raises the blood glucose level for the person to be measured .
Based on the activity data and the analysis data that is the result of the analysis by the data analysis means, alert information including the notes regarding the combination of the predetermined activity and the predetermined meal is generated as the notes regarding the predetermined relationship. An alert management step that executes control to output the generated alert information to the information processing terminal operated by the subject at a predetermined timing before the time when the predetermined activity is predicted to be performed.
A program that executes control processing including.

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