JP2023076792A - Information processing system, server, information processing method and program - Google Patents

Abstract

To provide an information processing system or the like for generating meal related information including any of at least meal timing information, meal frequency information, intake estimate value information, meal period information and meal period tendency information of a user based on blood glucose level information acquired from a measuring device.SOLUTION: An information processing system for receiving measured data from a measuring device worn by a user at a prescribed period via a network and generating biometric data and meal related information from the measured data, includes: a biometric data generation unit for executing prescribed calculations on the measured data and generating the biometric data including at least blood glucose level information; and a meal related information generation unit for generating meal related information including any of at least meal timing information, meal frequency information, intake estimate value information, meal period information and meal period tendency information of the user based on the blood glucose level information.SELECTED DRAWING: Figure 1

Description

The present disclosure generates meal-related information including at least one of meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information for the user, based on blood glucose level information acquired from a measuring device. The present invention relates to an information processing system, a server, an information processing method, and a program.

Conventionally, blood sugar levels have been measured by an invasive measurement method in which blood is collected from the user. However, since blood sampling is involved, it is a burden on the user to measure the blood sugar level on a daily basis and grasp the health condition. It was big.

Therefore, methods for measuring blood sugar levels in a non-invasive manner are being investigated. For example, Patent Literature 1 and Patent Literature 2 disclose a method of calculating a blood sugar level based on pulse wave information measured from a user.

Japanese Patent No. 6851664 Japanese Patent No. 6544751

However, simply measuring the blood sugar level is not sufficient for the benefit that the user can obtain. Further study is required on how to use it.

Therefore, in the present disclosure, meal-related information including at least one of meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information of the user is obtained based on the blood glucose level information acquired from the measuring device. An information processing system, a server, an information processing method, and a program to be generated will be described.

An information processing system according to one aspect of the present disclosure is an information processing system that receives measurement data from a measurement device worn by a user via a network at predetermined intervals, and generates biological data and meal-related information from the measurement data. a biometric data generation unit that performs a predetermined calculation on the measurement data to generate the biometric data including at least blood sugar level information; a meal-related information generating unit that generates meal-related information including any of information, intake estimated value information, meal period information, and meal period trend information.

According to the present disclosure, based on blood glucose level information generated based on measurement data, meal-related information including at least any of meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information of the user is provided. Information can be generated, and user convenience is improved.

1 is a block configuration diagram showing an information processing system according to an embodiment of the present disclosure; FIG. 2 is a diagram showing a hardware configuration of a management server 100 in FIG. 1; FIG. 3 is a block diagram illustrating functions of a storage unit 120 and a control unit 130 of FIG. 2; FIG. 4 is a schematic diagram showing an example of tag information associated with the measurement data of FIG. 3; FIG. 2 is a flowchart showing an example of processing of the information processing system 1 of FIG. 1;

The contents of the embodiments of the present invention are listed and explained. A system according to an embodiment of the present invention has the following configuration.

[Item 1]
An information processing system that receives measured data from a measuring device worn by a user via a network at predetermined intervals and generates biological data and meal-related information from the measured data,
a biometric data generation unit that performs a predetermined calculation on the measurement data to generate the biometric data that includes at least blood sugar level information;
a meal-related information generating unit that generates meal-related information including at least one of meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information of the user based on the blood sugar level information;
An information processing system comprising:
[Item 2]
When the meal-related information includes at least the user's meal timing information and meal frequency information,
The meal-related information generating unit detects peak value information from blood sugar level transition information based on the blood sugar level information, and generates at least one of the meal timing information and meal frequency information based on the peak value information.
The information processing system according to item 1, characterized by:
[Item 3]
When the meal-related information includes the user's meal timing information,
The meal timing information is time information indicating a time preceding a predetermined time from the time indicated by the time information included in the peak value information.
The information processing system according to item 2, characterized by:
[Item 4]
When the meal-related information includes meal frequency information,
The meal frequency information is information indicating the number of times the peak value information is detected.
The information processing system according to either item 2 or item 3, characterized by:
[Item 5]
The meal-related information generation unit generates notification information regarding changes in at least one of meal timing and meal frequency based on at least one of meal timing information and meal frequency information.
The information processing system according to any one of items 2 to 4, characterized by:
[Item 6]
When the meal-related information further includes intake estimate information,
The estimated intake value information is an estimated intake range of at least one of GI value, sugar content, and calorie value in the meal determined by the peak value information.
The information processing system according to any one of items 2 to 5, characterized by:
[Item 7]
When the meal-related information includes meal timing information and meal period information,
The meal period information is a period during which eating behavior information is determined based on the biometric data including at least movement information within a meal detection period set based on the meal timing information.
The information processing system according to any one of items 2 to 6, characterized by:
[Item 8]
When the meal-related information includes meal period trend information,
The meal period trend information is determined by comparing the meal period information and a reference meal period.
The information processing system according to item 7, characterized by:
[Item 9]
The meal-related information generation unit generates notification information regarding a change in the meal period based on the meal period trend information.
The information processing system according to item 8, characterized by:
[Item 10]
The meal-related information generation unit generates the meal-related information based on blood sugar level trend information that is associated with user information and indicates information about a user's blood sugar level trend.
The information processing system according to any one of items 1 to 9, characterized by:
[Item 11]
A server that receives measured data from a measuring device worn by a user via a network at predetermined intervals and generates biological data and meal-related information from the measured data,
a biometric data generation unit that performs a predetermined calculation on the measurement data to generate the biometric data that includes at least blood sugar level information;
a meal-related information generating unit that generates meal-related information including at least one of meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information of the user based on the blood sugar level information;
A server characterized by comprising:
[Item 12]
An information processing method for receiving measured data from a measuring device worn by a user via a network at a predetermined cycle and generating biological data and meal-related information from the measured data,
a step of performing a predetermined calculation on the measured data by a biological data generation unit to generate the biological data including at least blood glucose level information;
a step of generating meal-related information including at least one of meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information of the user by the meal-related information generation unit based on the blood sugar level information; and,
An information processing method comprising:
[Item 13]
A program for executing, on a computer, an information processing method for receiving measurement data from a measurement device worn by a user via a network at predetermined intervals and generating biometric data and meal-related information from the measurement data, comprising:
The information processing method includes:
a step of performing a predetermined calculation on the measured data by a biological data generation unit to generate the biological data including at least blood glucose level information;
a step of generating meal-related information including at least one of meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information of the user by the meal-related information generation unit based on the blood sugar level information; and,
An information processing method comprising:

Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. It should be noted that the embodiments described below do not unduly limit the content of the present disclosure described in the claims. Also, not all the components shown in the embodiments are essential components of the present disclosure. Also, the features shown in each embodiment can be applied to other embodiments as long as they are not mutually contradictory.

<Configuration>
FIG. 1 is a block configuration diagram showing an information processing system 1 according to an embodiment of the present disclosure. In this information processing system 1, for example, the management server 100 receives user measurement data from the measurement device 300 via the network NW at predetermined periodic timings, and performs predetermined calculations on the measurement data. generates biological data, and based on the biological data, generates meal-related information including at least one of the user's meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information. .

The information processing system 1 has a management server 100, a user terminal device 200, a measuring device 300, and a network NW. The management server 100 and the user terminal device 200 are connected via a network NW. The network NW includes the Internet, an intranet, a blockchain network, a wireless LAN (Local Area Network), a WAN (Wide Area Network), BLE (Bluetooth Low Energy), and the like.

The management server 100 is, for example, a device that receives user measurement data from the measurement device 300 via a network at predetermined periodic timing via the user terminal device 200 and performs calculation from the measurement data to biometric data. There is, for example, a server device that provides various Web services.

The user terminal device 200 is an information processing device such as a personal computer, a tablet terminal, a smart phone, a smart watch, a mobile phone, a PHS, a PDA, etc. owned by a user. It is used to display a waveform graph or the like, or to display meal-related information including at least the user's meal timing information (details will be described later) generated based on biometric data. User information such as user identification number, date of birth, gender, height, weight, stride length, etc. is registered in advance in the user terminal device 200, and user information including age calculated from the date of birth is measured data. to the management server 100 via the network NW.

Also, the user terminal device 200 may be configured such that the user inputs the state of data acquisition by the measuring device 300 using a touch panel or the like. The user terminal device 200 can input the "data acquisition state" as tag information, for example, "running" when running. In this case, the user terminal device 200 associates the measurement data received from the measurement device 300 with predetermined periodic timing with the tag information and transmits the measurement data to the management server 100 via the network NW.

The measuring device 300 is a device that measures a user's biological data, and is a so-called wearable device that the user wears on his or her body such as a wrist or arm. This measurement device 300 is a device for measuring, for example, the user's electrocardiogram, pulse wave, skin temperature (body temperature), acceleration, and angular velocity data at predetermined periodic timings by a known method. The predetermined cycle may be set in advance or may be arbitrarily set by the user. More specifically, for example, a time period in units of seconds may be set, or the same may be set depending on the frequency.

As a specific example of the configuration of the measurement device 300, two electrodes may be brought into contact with the skin, and an electrocardiogram may be obtained as electrocardiogram data from changes in the detected potential difference over time. The waveform may be data acquired by galvanic skin response. In addition, the skin is irradiated with light from LEDs that emit green, red, and infrared light, and the change in intensity of the light received by the photodiode over time changes the volume of blood vessels caused by the user's heartbeat, generating a pulse wave. It may be configured with a device that acquires pulse waveform data, and the pulse waveform that can be detected by this method is a photoelectric volume pulse waveform. Alternatively, the apparatus may be configured by a device that acquires the user's skin temperature as data from a temperature sensor that is brought into contact with the user's skin. Further, it may be composed of a three-axis acceleration sensor that detects the deformation state of each of the orthogonal XYZ axes, acquires the user's motion as acceleration data, and for example, the measuring device 300 is worn on the user's wrist, arm, or the like. In this case, the measurement device 300 acquires acceleration data as acceleration obtained by synthesizing the swing of the wrist or arm and the movement of the whole body. Further, it may be composed of a gyro sensor (angular velocity sensor) that detects rotational angular velocities in each of the orthogonal XYZ axes. If so, the measurement device 300 acquires angular velocity data as an angular velocity obtained by synthesizing the rotation of the wrist, arm, etc. and the movement of the whole body.

Between the user terminal device 200 and the measuring device 300, Bluetooth (registered trademark), Near Field radio Communication (NFC), Afero (registered trademark), Zigbee (registered trademark), Z-Wave (registered trademark) ), or a wireless LAN or the like. A wired connection may be used instead of such a wireless connection. In addition, the user terminal device 200 and the measurement device 300 may be integrated equipment, for example, the measurement device 300 may be equipped with a SIM to have a communication function, or a management server using BLE (Bluetooth Low Energy). 100 may be configured to be directly communicable.

One or a plurality of user terminal devices 200 are connected to the network NW for the number of users using the measuring device 300 . One or a plurality of measuring devices 300 are connected to the same number of user terminal devices 200 used by one user. When one user uses multiple measuring devices 300 , multiple measuring devices 300 are connected to one user terminal device 200 .

<Management Server 100>
FIG. 2 is a diagram showing the hardware configuration of the management server 100. As shown in FIG. FIG. 3 is a block diagram illustrating functions of the storage unit 120 and the control unit 130. As shown in FIG. Note that the illustrated configuration is an example, and other configurations may be employed.

The management server 100 includes a communication unit 110 , a storage unit 120 , a control unit 130 and an input/output unit 140 . These functional units are realized by executing a predetermined program for the management server 100. FIG.

The communication unit 110 is a communication interface for communicating with the user terminal device 200, and communication is performed according to a communication protocol such as TCP/IP (Transmission Control Protocol/Internet Protocol).

The storage unit 120 stores programs, input data, and the like for executing various control processes and functions in the control unit 130, and is composed of RAM (Random Access Memory), ROM (Read Only Memory), and the like. be. Further, as shown in FIG. 3, the storage unit 120 includes a measurement data DB 121 that stores data measured by the measurement device 300 in association with user information, and a biometric data that is calculated and generated from the measurement data in association with the user information. and meal-related information including at least one of the user's meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information generated based on the biological data DB 122 as user information. and a user information DB 124 for storing user information including a user identification number. The user information may include account information generated by the data management unit 131, and the user information DB 124 may store the account information in association with other user information. Furthermore, the storage unit 120 temporarily stores data communicated with the user terminal device 200 . Note that the data structure of the DB is not limited to this, and part of the DB described above may be stored in the user terminal device 200 or the measurement device 300 .

The control unit 130 controls the overall operation of the management server 100, and is composed of a CPU (Central Processing Unit) and the like. Further, as shown in FIG. 3, the control unit 130 includes functional units such as a data management unit 131, a biological data generation unit 132, a meal-related information generation unit 133, and a data output unit .

Data management unit 131 generates account information for each user who uses measuring device 300 . This account information generation is performed when the user using the measuring device 300 registers the account information with the user terminal device 200 . Therefore, the data management unit 131 controls access to various DBs in the storage unit 120 for each account of the user terminal device 200 and other terminal devices of the user. The data management unit 131 handles various data such as measurement data, biometric data, and meal-related information including at least one of the user's meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information. stored in a DB associated with the user information. Also, at this time, the data management unit 131 can store the measurement data in association with predetermined tag information.

FIG. 4 is a schematic diagram showing an example of tag information associated with the measurement data of FIG. Data D1 shown in FIG. 4 is measurement data of the measurement device 300 . The tag T1 is tag information associated with the data D1. For example, time information when the measuring device 300 measured the data D1 or time information when the data D1 was transmitted from the measuring device 300 to the user terminal device 200 is time-series. stored as data. Alternatively, both the measured time information and the transmitted time information may be associated. For example, in the first line of the tag T1 shown in FIG. 4, "20180620120746144" is stored, which indicates June 20, 2018 12:07:46:144 milliseconds. Such time information can be obtained from communication logs. This makes it possible to ascertain which time period the measurement data belongs to.

The association between measurement data and biometric data based on such tag information is not limited to time information. Physical information and behavior information indicating the user's physical condition and behavioral condition can be entered freely and stored as tag information. (For example, in response to the question "How are you feeling now?", select one of "1: good, 2: normal, 3: bad", etc.) , the selected answer may be stored. Alternatively, when the user takes a predetermined action (for example, sitting, standing, walking, running, sleeping, driving, resting, etc.), the user records measurement data or biometric data as tag information (for example, option format or free description). Furthermore, instead of or in combination with the recording by the user, for example, measurement data and biological data (for example, walking speed information, stride length information, movement information of the wearing part, posture information, position information of the center of gravity, heartbeat information, etc. ) based on the tag information (e.g., sitting, standing, lying down, walking, running, sleeping, waking up, going to bed, driving, resting, etc.) by a known method. behavior information). At this time, for example, the learning model may be estimated based on the teacher measurement data, and the learning model may be personalized by performing additional learning based on the results recorded by the user. As a result, when biometric data is generated by the control unit 150, by associating the tag information with the biometric data, it becomes possible to generate biometric data with higher accuracy, and the biometric data itself is also used as action information. becomes possible.

Further, for example, the data management unit 131 can manage data based on tag information, such as rearranging (sorting) the data D1 in chronological order of the tags T1, and extracting only predetermined physical information and behavior information.

The biometric data generation unit 132 performs a predetermined operation on the measurement data stored in the measurement data DB 121 to generate biometric data. This biological data may be any information as long as it can be calculated from the measurement data. For example, the user's blood sugar level information, blood pressure information, heartbeat information, Electrocardiogram information, respiratory rate, body temperature information, step count information, stride information, center of gravity position information, posture information, stress information, exercise amount information, exercise load information, movement distance information, movement speed information, activity amount information, hands or legs, etc. , which is data such as motion information of the attachment site, and is calculated from measurement data by a known method. Biometric data generated by the calculation is stored in the biometric data DB 122 .

Further, by a known learning device, for example, measured data, biological data generated based on the measured data (such as heartbeat information and blood pressure information) and positive biological data (such as heartbeat information based on known medical equipment) , blood pressure information, etc.), and a learning model is created in advance based on the teacher data associated by the correspondence relationship (for example, information indicating the degree and range of error may be included), and the biometric data generation unit 132 Alternatively, determination using the learning model may be used as the above-described predetermined calculation (analysis) to generate biometric data.

The meal-related information generation unit 133 generates at least the meal timing information of the user, for example, based on the blood sugar level information generated from the measurement data received at predetermined periodic timing by the measuring device 300 that the user wears on a daily basis. , meal frequency information, intake estimated value information, meal period information, and meal period trend information.

Here, in the conventional measuring device 300 and related applications, it is assumed that the user inputs (further manages separately with another application) when leaving meal-related information about meals. generates and manages various biological data such as blood pressure based on measurement data obtained from the measuring device 300 worn on a daily basis. is generated from measured or biometric data, eliminating the need for user input.

Therefore, in the present embodiment, the blood sugar level rises significantly after a meal, and a peak value that turns from an increase to a decrease appears after a predetermined time (for example, about 1 hour) after the meal, and meal-related information is generated. The unit 133 detects and generates peak value information from the blood sugar level transition information based on the blood sugar level information, and generates meal-related information including meal timing, number of meals, etc. based on the peak value information. The peak value information may be, for example, blood sugar level information and time information at the maximum value when the difference value between the maximum value and the minimum value of blood sugar level information within a predetermined period exceeds a predetermined reference value. In addition, the condition for detecting the peak value may be that the blood sugar level information exceeds a predetermined reference value (for example, any numerical value within the range of 120 to 160 mg/dl). In addition to this condition, in order to eliminate noise, the blood glucose level information exceeds the predetermined reference value and after a predetermined period of time (after about 1 to 3 hours and at least 1 hour), the reference value is re-established. may be less than In addition, in the case of a person with high blood sugar level, such as a diabetic, there is a risk of erroneous determination based on only the reference value. And the magnitude of the relative difference value with respect to the average value information such as the average value of the sleep period calculated based on the behavior information and the average value of the predetermined period before meals exceeds a predetermined reference value (30 to 50 mg / dl, etc.) Alternatively, the condition may be that the gradient from the minimum value to the maximum value of the blood sugar level information for a predetermined period (time information of each value is also considered) exceeds a predetermined reference value. Alternatively, peak value information may be generated by determining a peak value using a learning model that is learned based on teacher data in which a peak value is supervised for information indicating changes in blood sugar levels. The meal frequency information is calculated based on the peak value information, and may be information indicating, for example, the number of times the peak value information is detected. The meal timing information is calculated based on the time information included in the peak value information, and is, for example, time information indicating a time that is a predetermined time (for example, one hour before) before the time indicated by the time information included in the peak value information. may be used as the meal timing information. Also, depending on whether the user is a "normal person", "a person who is prone to blood sugar spikes", or "a person who may have diabetes (including potential diabetes)", the tendency of the blood sugar level transition information is large. In view of the differences, it may be associated with the user information as blood sugar level trend information indicating information about the user's blood sugar level trend, such as who the user is, and the above-mentioned predetermined The reference value for the period and the difference value may be set to different values (for example, the reference value for "a person who may have diabetes" may be set higher). The blood sugar level trend information may be set, for example, by a user's input operation (selection operation) on an application, or may be set based on the average value or maximum value for each predetermined period (for example, daily unit) of blood sugar level information. It may be set, for example, if the average value is more than a predetermined blood sugar level, it is set as "a person who may have diabetes (including potential diabetes)", and the average value is lower than the predetermined blood sugar level, but the maximum value is If the blood sugar level is higher than a predetermined level, it may be set as "a person who is prone to blood sugar level spikes", and other than that may be set as a "normal person", but the present invention is not limited to these.

In this way, it is possible to generate meal-related information regarding the number of meals and meal timing based on the peak information generated from the user's blood sugar level transition information. In addition, the meal-related information generating unit 133 determines the number of meals (including snacks) based on at least one of the meal timing information and meal frequency information when the maximum blood sugar level information is higher than the reference blood sugar level information. ), prompting people to eat meals (especially snacks) when the time interval in multiple meal timing information is larger than a predetermined value, or changing the meal timing and number of meals by calling attention to the necessity of these items. Notification information (in particular, alert information, advice information, etc.) related to eating may be generated as meal-related information, and these may be presented to the user on the application. The generation of notification information here includes determining which notification is to be the meal-related information. , and so on.

In addition, it is known that the higher the GI (glycemic index) value, the sugar content, and the calorie value, the greater the increase in blood sugar level. , the meal-related information generation unit 133 estimates how much GI value, carbohydrate amount, and calorie value may be ingested in the meal determined by the peak information. However, the estimated intake range may be generated as estimated intake value information included in the meal-related information. Furthermore, since the above-described rising tendency differs depending on the blood sugar level trend and user characteristics (especially height, weight, age, etc.), for example, each blood sugar level trend information and user information (especially height information, weight information, age information, etc.) The accuracy of estimation may be improved by storing the correspondence relationship between each value and the rate of increase in blood sugar level for each predetermined range of .

In addition, although it is theoretically possible to estimate action information such as "eating" from hand action information and posture information when the measuring device 300 is attached to the hand, it is possible to estimate all action information during the day. A considerable amount of machine learning is required to pinpoint and accurately judge from among. Therefore, the meal-related information generation unit 133 sets a meal detection period (for example, one hour before or after the time information indicated by the meal timing information) based on the meal timing information described above, and calculates at least the motion information within the meal detection period. Action information (eating action information) indicating "meal" is determined based on the above. As a result, for example, it is possible to improve the determination accuracy when determining action information indicating "meal" by using a learning model. Furthermore, the meal-related information generation unit 133 may generate meal-period information indicating the period during which the user has been eating as the meal-related information based on the period information in which the action information indicating "meal" was determined. Then, for example, by presenting one or more pieces of meal period information to the user on the application, it becomes possible to objectively grasp the tendency of one's own meal period. is compared with the reference meal period, and meal period trend information (e.g., "fast eating" if the meal period is shorter than the first reference meal period, and if the meal period is longer than the first reference meal period "just right", "late eating" if the meal period is longer than the second reference meal period longer than the first reference meal period, etc.), and notification information about changes in the meal period corresponding to the meal period trend information (For example, alert information such as "Be careful not to eat too quickly" or advice information such as "Be careful not to eat too quickly") may be generated as meal-related information, and these may be sent to the user on the application. By adopting the configuration shown, it may be possible to grasp the tendency of one's own meal time in more detail.

The data output unit 134 outputs the biometric data and various types of meal-related information described above to the user terminal device 200 . In the user terminal device 200, the output data may be displayed on the screen via a dedicated application, for example, so that the user can easily check it.

The input/output unit 140 is an information input device such as a keyboard and a mouse, and an output device such as a display.

<Process flow>
The flow of processing of the information processing method executed by the information processing system 1 will be described with reference to FIG. FIG. 5 is a flow chart showing an example of processing of the information processing system 1 of FIG.

As the process of step S101, the data management unit 131 generates account information for each user who uses the measuring device 300, and acquires predetermined user information from the user terminal device 200 or the like. The registered user information is stored in the user information DB 124 by the data management unit 131 . The processing of step S101 may be performed as preprocessing for the user to use the measuring device 300, or may be performed when the user uses the measuring device 300 for the first time.

As the process of step S102, when the user uses the measuring device 300, the measured data is transmitted from the measuring device 300 to the management server 100 via the user terminal device 200 and received via the communication unit 110 at predetermined intervals. The data management unit 131 stores the measurement data in the measurement data DB 121 of the storage unit 120 in association with the user information.

As the process of step S103, the biometric data generation unit 132 reads the measurement data, and generates biometric data by a predetermined calculation or the like. The generated biometric data is stored in the biometric data DB 122 by the data management unit 131 .

As the process of step S104, the meal-related information generation unit 133 reads the biometric data, and at least any of the user's meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information is obtained by predetermined calculation or the like. Meal-related information is generated including At least the user's meal timing information generated is stored in the meal-related information DB 123 by the data management unit 131 .

As the process of step S105, the data output unit 134 reads biological data and/or meal-related information including at least one of the user's meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information. and output to the user terminal device 200 .

<effect>
As described above, the information processing system according to the present embodiment uses at least the user's meal timing information, meal frequency information, and intake estimation from the blood sugar level information generated based on the measurement data via the meal-related information generation unit 133. Meal-related information including any of value information, meal period information, and meal period trend information is generated. Thereby, the user can grasp at least the user's meal timing information, for example, and the user's convenience is improved.

Although the disclosed embodiments have been described above, they can be implemented in various other forms, and can be implemented with various omissions, substitutions, and modifications. These embodiments, modifications, omissions, substitutions and changes are included within the technical scope of the claims and their equivalents.

1 Information Processing System 100 Management Server 200 User Terminal Device 300 Measuring Device NW Network

Claims (13)

An information processing system that receives measured data from a measuring device worn by a user via a network at predetermined intervals and generates biological data and meal-related information from the measured data,
a biometric data generation unit that performs a predetermined calculation on the measurement data to generate the biometric data that includes at least blood sugar level information;
a meal-related information generating unit that generates meal-related information including at least one of meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information of the user based on the blood sugar level information;
An information processing system comprising: When the meal-related information includes at least the user's meal timing information and meal frequency information,
The meal-related information generating unit detects peak value information from blood sugar level transition information based on the blood sugar level information, and generates at least one of the meal timing information and meal frequency information based on the peak value information.
The information processing system according to claim 1, characterized by: When the meal-related information includes the user's meal timing information,
The meal timing information is time information indicating a time preceding a predetermined time from the time indicated by the time information included in the peak value information.
3. The information processing system according to claim 2, characterized by: When the meal-related information includes meal frequency information,
The meal frequency information is information indicating the number of times the peak value information is detected.
4. The information processing system according to claim 2 or 3, characterized in that: The meal-related information generation unit generates notification information regarding changes in at least one of meal timing and meal frequency based on at least one of meal timing information and meal frequency information.
5. The information processing system according to any one of claims 2 to 4, characterized in that: When the meal-related information further includes intake estimate information,
The estimated intake value information is an estimated intake range of at least one of GI value, sugar content, and calorie value in the meal determined by the peak value information.
6. The information processing system according to any one of claims 2 to 5, characterized in that: When the meal-related information includes meal timing information and meal period information,
The meal period information is a period during which eating behavior information is determined based on the biometric data including at least movement information within a meal detection period set based on the meal timing information.
7. The information processing system according to any one of claims 2 to 6, characterized in that: When the meal-related information includes meal period trend information,
The meal period trend information is determined by comparing the meal period information and a reference meal period.
8. The information processing system according to claim 7, characterized by: The meal-related information generation unit generates notification information regarding a change in the meal period based on the meal period trend information.
9. The information processing system according to claim 8, characterized by: The meal-related information generation unit generates the meal-related information based on blood sugar level trend information that is associated with user information and indicates information about a user's blood sugar level trend.
10. The information processing system according to any one of claims 1 to 9, characterized by: A server that receives measured data from a measuring device worn by a user via a network at predetermined intervals and generates biological data and meal-related information from the measured data,
a biometric data generation unit that performs a predetermined calculation on the measurement data to generate the biometric data that includes at least blood sugar level information;
a meal-related information generating unit that generates meal-related information including at least one of meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information of the user based on the blood sugar level information;
A server characterized by comprising: An information processing method for receiving measured data from a measuring device worn by a user via a network at a predetermined cycle and generating biological data and meal-related information from the measured data,
a step of performing a predetermined calculation on the measured data by a biological data generation unit to generate the biological data including at least blood glucose level information;
a step of generating meal-related information including at least one of meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information of the user by the meal-related information generation unit based on the blood sugar level information; and,
An information processing method comprising: A program for executing, on a computer, an information processing method for receiving measurement data from a measurement device worn by a user via a network at predetermined intervals and generating biometric data and meal-related information from the measurement data, comprising:
The information processing method includes:
a step of performing a predetermined calculation on the measured data by a biological data generation unit to generate the biological data including at least blood glucose level information;
a step of generating meal-related information including at least one of meal timing information, meal frequency information, intake estimated value information, meal period information, and meal period trend information of the user by the meal-related information generation unit based on the blood sugar level information; and,
An information processing method comprising:

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