JP2023038142A - Information system, server, information processing method and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information processing system, etc. according to the present embodiment, generating determination support information for supporting determination of a health status relating to diabetes mellitus based on at least any one of minimum blood glucose level information or average blood glucose level information, or standard deviation blood glucose level information acquired from blood glucose level information generated based on measured data.

SOLUTION: An information processing system according to the present embodiment includes a biometric data generation unit executing prescribed calculations on measured data and generating biometric data including blood glucose level information, and a determination support information generation unit generating determination support information for supporting determination of a health status relating to diabetes mellitus based on the blood glucose level information. The determination support information generation unit generates determination support information based on a result of comparing at least one of minimum blood glucose level information and average blood glucose level information, and standard deviation blood glucose level information, with corresponding reference blood glucose level information to each other.

SELECTED DRAWING: Figure 1

COPYRIGHT: (C)2023,JPO&INPIT

Description

The present disclosure relates to an information processing system, a server, an information processing method, and a program that generate determination support information that supports determination of a health condition related to diabetes based on blood sugar level information acquired from a measuring device.

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, an information processing system, a server, an information processing method, and a program that generate determination support information that supports determination of a health condition related to diabetes based on blood sugar level information acquired from a measuring device 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 determination support information from the measurement data. a biometric data generation unit that performs a predetermined operation on the measurement data to generate the biometric data including at least blood sugar level information; and a determination of a health condition related to diabetes based on the blood sugar level information. and a determination support information generation unit that generates determination support information to support, the determination support information generation unit is the lowest blood sugar level information that is the lowest blood sugar level information in a predetermined period, or the lowest blood sugar level information in a predetermined period Average blood sugar level information that is the average value of predetermined blood sugar level information acquired, or a value obtained by subtracting twice the standard deviation of the blood sugar level information acquired during the predetermined period from the average blood sugar level information At least one of the standard deviation blood sugar level information and the corresponding reference blood sugar level information are compared with each other to generate determination support information.

According to the present disclosure, based on at least one of minimum blood sugar level information or average blood sugar level information obtained from blood sugar level information generated based on measurement data, or standard deviation blood sugar level information, It becomes possible to generate determination support information that supports determination of the health condition, thereby improving convenience for the user.

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 measurement data from a measurement device worn by a user via a network at predetermined intervals and generates biological data and determination support information from the measurement 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 determination support information generation unit that generates determination support information that supports determination of a health condition related to diabetes based on the blood sugar level information;
The determination support information generation unit includes minimum blood sugar level information that is the lowest blood sugar level information in a predetermined period, or average blood sugar level information that is an average value of predetermined blood sugar level information acquired in a predetermined period, Alternatively, at least one of the standard deviation blood sugar level information, which is a value obtained by subtracting twice the standard deviation of the blood sugar level information obtained in the predetermined period from the average blood sugar level information, and the corresponding reference blood sugar level information generating decision support information based on the results of comparing with each other,
An information processing system characterized by:
[Item 2]
At least one of the minimum blood sugar level information, the average blood sugar level information, and the standard deviation blood sugar level information is provided with a plurality of the corresponding reference blood sugar level information in stages.
The information processing system according to item 1, characterized by:
[Item 3]
The average blood sugar level information is an average value of blood sugar level information in the waking period estimated based on the associated behavior information,
The information processing system according to any one of items 1 and 2, characterized by:
[Item 4]
The average blood sugar level information is an average value of blood sugar level information whose associated behavior information is at least one of waking up, eating, going to bed, and sleeping.
The information processing system according to any one of items 1 and 2, characterized by:
[Item 5]
The average blood sugar level information is an average value of blood sugar level information obtained by removing high frequency components from the blood sugar level fluctuation information indicating the transition of the generated blood sugar level information,
The information processing system according to any one of items 1 and 2, characterized by:
[Item 6]
wherein the average blood sugar level information is an average value of blood sugar level information excluding blood sugar level information whose associated behavior information is meal;
The information processing system according to any one of items 1 and 2, characterized by:
[Item 7]
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 determination support 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 determination support information generation unit that generates determination support information that supports determination of a health condition related to diabetes based on the blood sugar level information;
The determination support information generation unit includes minimum blood sugar level information that is the lowest blood sugar level information in a predetermined period, or average blood sugar level information that is an average value of predetermined blood sugar level information acquired in a predetermined period, Alternatively, at least one of the standard deviation blood sugar level information, which is a value obtained by subtracting twice the standard deviation of the blood sugar level information obtained in the predetermined period from the average blood sugar level information, and the corresponding reference blood sugar level information generating decision support information based on the results of comparing with each other,
A server characterized by:
[Item 8]
An information processing method for receiving measurement data from a measurement device worn by a user via a network at a predetermined cycle and generating biological data and determination support information from the measurement 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;
generating, by a determination support information generation unit, determination support information that supports determination of a health condition related to diabetes based on the blood glucose level information;
The determination support information generation unit includes minimum blood sugar level information that is the lowest blood sugar level information in a predetermined period, or average blood sugar level information that is an average value of predetermined blood sugar level information acquired in a predetermined period, Alternatively, at least one of the standard deviation blood sugar level information, which is a value obtained by subtracting twice the standard deviation of the blood sugar level information obtained in the predetermined period from the average blood sugar level information, and the corresponding reference blood sugar level information generating decision support information based on the results of comparing with each other,
An information processing method characterized by:
[Item 9]
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 determination support information from the measurement data,
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;
generating, by a determination support information generation unit, determination support information that supports determination of a health condition related to diabetes based on the blood glucose level information;
The determination support information generation unit includes minimum blood sugar level information that is the lowest blood sugar level information in a predetermined period, or average blood sugar level information that is an average value of predetermined blood sugar level information acquired in a predetermined period, Alternatively, at least one of the standard deviation blood sugar level information, which is a value obtained by subtracting twice the standard deviation of the blood sugar level information obtained in the predetermined period from the average blood sugar level information, and the corresponding reference blood sugar level information generating decision support information based on the results of comparing with each other,
A program characterized by

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. is a system that generates biometric data in and generates determination support information based on the biometric data.

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 determination support 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 or 'eating' when eating. 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 it 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 using a known technique. 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 obtained 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 heartbeat of the user, 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. Furthermore, 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. a biometric data DB 122 that stores biometric data, a determination support information DB 123 that stores determination support information generated based on biometric data in association with user information, and a user information DB 124 that stores 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 includes 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 biometric data generation unit 132, a determination support 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 stores various data such as measurement data, biometric data, and determination support information in corresponding DBs in association with 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 zone 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, eating, driving, resting, etc.), the user records measurement data or biometric data as tag information (for example, It may be a choice 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. ), tag biometric data etc. by estimating predetermined behavior (for example, sitting, standing, lying down, walking, running, sleeping, waking up, going to bed, eating, driving, resting, etc.) by a known method You may associate as information (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 determination support information generation unit 133, for example, based on the blood sugar level information generated from the measurement data received at predetermined periodic timing by the measurement device 300 that the user wears on a daily basis, Generate determination support information that supports determination of the health condition.

Here, in the conventional invasive blood sugar level measurement, the user can recognize by himself/herself when he/she is hungry or when a predetermined time has passed since the end of a meal. Any one of the measuring device 300, the user terminal device 200, and the management server 100 needs to recognize. Therefore, in the present embodiment, focusing on the fact that it is presumed that the fasting state is used as a standard in general standards because the blood sugar level decreases due to fasting, , 1 day, 24 hours, etc.), the lowest blood sugar level information (minimum blood sugar level information) may be acquired as a target for comparison with the reference blood sugar level information. For example, the reference blood sugar level information may be a general reference value for the fasting blood sugar level information as described above, or the blood sugar level information of a plurality of diabetic patients and the blood sugar level information of healthy subjects are obtained in advance, An appropriate reference value may be set based on the tendency of the minimum blood sugar level information in these blood sugar level information.

In addition, focusing on the fact that the blood sugar level information of a person with a tendency to diabetes tends to be high at any time, Average blood sugar level information, which is an average value of blood sugar level information, may be acquired as a comparison target with reference blood sugar level information. The average blood sugar level information may be the average value of all blood sugar level information acquired during a predetermined period, or the waking period (for example, the period from when the behavior information is awake to the sleeping state, or the entire period may be the average value of the blood sugar level information in the period excluding the sleep state), or the average value of the blood sugar level information (for example, waking up, eating, going to bed, sleeping, etc.) associated with the predetermined behavior information Alternatively, in order to reduce the influence of postprandial blood sugar spikes, it may be the average value of blood sugar level information obtained by removing high-frequency components from the blood sugar level fluctuation information indicating the transition of blood sugar level information, or it may indicate a meal. It may be an average value of blood sugar level information excluding blood sugar level information related to behavior information (especially blood sugar level information within a predetermined time after a meal). For example, for the reference blood sugar level information, the blood sugar level information of a plurality of diabetic patients and the blood sugar level information of healthy subjects are obtained in advance, and an appropriate reference value is set based on the tendency of the average blood sugar level information in these blood sugar level information. good too.

Furthermore, in consideration of noise in the measurement data and fluctuations such as a decrease in blood sugar level when insulin is used, the average of predetermined blood sugar level information acquired during a predetermined period (for example, one week, several days, one day, or 24 hours) Standard deviation blood sugar level information obtained by subtracting twice the standard deviation of the blood sugar level information for a predetermined period from the average blood sugar level information (i.e., blood sugar level information calculated by average blood sugar level information - 2σ (standard deviation)) may be acquired as an object for comparison with the reference blood sugar level information. For example, for the reference blood sugar level information, the blood sugar level information of a plurality of diabetic patients and the blood sugar level information of healthy subjects are obtained in advance, and an appropriate reference value is set based on the tendency of the standard deviation blood sugar level information in these blood sugar level information. may

Then, by comparing at least one of these blood sugar level information (minimum blood sugar level information, average blood sugar level information, standard deviation blood sugar level information) with the corresponding reference blood sugar level information, as a comparison result Generate determination support information that supports determination of the health condition. In addition, by setting the reference value in multiple stages for each reference blood sugar level, it becomes possible for the user to recognize how easily the user is currently diagnosed as having diabetes. The determination support information may be any information as long as it is information that supports determination of a health condition related to diabetes. For example, information indicating which reference value is exceeded (or not exceeded) or information indicating which group (for example, normal group, preliminary group, caution group, etc.) belongs to groupings set with the reference blood sugar level information as a boundary. Alternatively, an estimated measurement value range when converted into a measurement result in a predetermined unit (for example, mg/dl) in general measurement (especially invasive measurement) may be presented.

The data output unit 134 outputs biometric data and determination support information data 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. In addition, when a plurality of groups are provided by setting a plurality of reference blood sugar level information as described above, a predetermined notification (for example, high blood sugar level Alert notification that notifies that the blood sugar level is lowered, advice notification that notifies information for lowering blood sugar level, etc.) ), or the content of the notification may be changed depending on which reference value information is exceeded (for example, the higher the reference value exceeded, the more emphasized the display of notation, color, characters, etc.) (e.g., a notification that has been issued).

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 biometric data is read by the determination support information generation unit 133, and determination support information is generated by a predetermined calculation or the like. The generated determination support information is stored in the determination support information DB 123 by the data management unit 131 .

As the process of step S<b>105 , the data output unit 134 reads the biometric data and/or the determination support information and outputs them to the user terminal device 200 .

<effect>
As described above, the information processing system according to the present embodiment uses the determination support information generating unit 133 to obtain minimum blood sugar level information or average blood sugar level information, standard Based on at least one of the deviation blood glucose level information, determination support information is generated to support determination of diabetes-related health conditions. This enables the user to grasp his/her own health condition related to diabetes, for example, thereby improving convenience for the user.

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 modifications 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 (9)

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 determination support information from the measurement 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 determination support information generation unit that generates determination support information that supports determination of a health condition related to diabetes based on the blood sugar level information;
The determination support information generation unit includes minimum blood sugar level information that is the lowest blood sugar level information in a predetermined period, or average blood sugar level information that is an average value of predetermined blood sugar level information acquired in a predetermined period, Alternatively, at least one of the standard deviation blood sugar level information, which is a value obtained by subtracting twice the standard deviation of the blood sugar level information obtained in the predetermined period from the average blood sugar level information, and the corresponding reference blood sugar level information generating decision support information based on the results of comparing with each other,
An information processing system characterized by: At least one of the minimum blood sugar level information, the average blood sugar level information, and the standard deviation blood sugar level information is provided with a plurality of the corresponding reference blood sugar level information in stages.
The information processing system according to claim 1, characterized by: The average blood sugar level information is an average value of blood sugar level information in the waking period estimated based on the associated behavior information,
3. The information processing system according to claim 1 or 2, characterized in that: The average blood sugar level information is an average value of blood sugar level information whose associated behavior information is at least one of waking up, eating, going to bed, and sleeping.
3. The information processing system according to claim 1 or 2, characterized in that: The average blood sugar level information is an average value of blood sugar level information obtained by removing high frequency components from the blood sugar level fluctuation information indicating the transition of the generated blood sugar level information,
3. The information processing system according to claim 1 or 2, characterized in that: wherein the average blood sugar level information is an average value of blood sugar level information excluding blood sugar level information whose associated behavior information is meal;
3. The information processing system according to claim 1 or 2, characterized in that: 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 determination support 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 determination support information generation unit that generates determination support information that supports determination of a health condition related to diabetes based on the blood sugar level information;
The determination support information generation unit includes minimum blood sugar level information that is the lowest blood sugar level information in a predetermined period, or average blood sugar level information that is an average value of predetermined blood sugar level information acquired in a predetermined period, Alternatively, at least one of the standard deviation blood sugar level information, which is a value obtained by subtracting twice the standard deviation of the blood sugar level information obtained in the predetermined period from the average blood sugar level information, and the corresponding reference blood sugar level information generating decision support information based on the results of comparing with each other,
A server characterized by: An information processing method for receiving measurement data from a measurement device worn by a user via a network at a predetermined cycle and generating biological data and determination support information from the measurement 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;
generating, by a determination support information generation unit, determination support information that supports determination of a health condition related to diabetes based on the blood glucose level information;
The determination support information generation unit includes minimum blood sugar level information that is the lowest blood sugar level information in a predetermined period, or average blood sugar level information that is an average value of predetermined blood sugar level information acquired in a predetermined period, Alternatively, at least one of the standard deviation blood sugar level information, which is a value obtained by subtracting twice the standard deviation of the blood sugar level information obtained in the predetermined period from the average blood sugar level information, and the corresponding reference blood sugar level information generating decision support information based on the results of comparing with each other,
An information processing method characterized by: 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 determination support information from the measurement data,
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;
generating, by a determination support information generation unit, determination support information that supports determination of a health condition related to diabetes based on the blood glucose level information;
The determination support information generation unit includes minimum blood sugar level information that is the lowest blood sugar level information in a predetermined period, or average blood sugar level information that is an average value of predetermined blood sugar level information acquired in a predetermined period, Alternatively, at least one of the standard deviation blood sugar level information, which is a value obtained by subtracting twice the standard deviation of the blood sugar level information obtained in the predetermined period from the average blood sugar level information, and the corresponding reference blood sugar level information generating decision support information based on the results of comparing with each other,
A program characterized by

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