WO2020196812A1 - Information providing system, information providing program, and non-transitory computer-readable storage medium - Google Patents

Information providing system, information providing program, and non-transitory computer-readable storage medium Download PDF

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WO2020196812A1
WO2020196812A1 PCT/JP2020/013916 JP2020013916W WO2020196812A1 WO 2020196812 A1 WO2020196812 A1 WO 2020196812A1 JP 2020013916 W JP2020013916 W JP 2020013916W WO 2020196812 A1 WO2020196812 A1 WO 2020196812A1
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body composition
health
information
estimated
information providing
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PCT/JP2020/013916
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French (fr)
Japanese (ja)
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児玉　美幸
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株式会社タニタ
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

Definitions

  • This disclosure relates to an information providing system that acquires health diagnosis data and provides information, an information providing program, and a computer-readable non-temporary recording medium that records the program.
  • a body composition meter that measures body composition based on information such as height, weight, age, and gender and bioelectrical impedance of each part of the human body obtained by measurement is known.
  • biochemical test values such as HDL cholesterol, ⁇ -GTP, and blood glucose are measured by tests such as blood tests.
  • health risk assessment and advice for maintaining or recovering health should be given based on these biochemical test values and lifestyle habits such as smoking habits, alcohol intake habits, and exercise habits. There is.
  • risk evaluations and advice based on the results of health examinations are limited to general theory and tendency theory, and in consideration of the individual body composition of the user, how much health risk there is and how much eating and drinking restrictions should be applied. It was difficult to give a quantitative index such as how much exercise should be done.
  • a body composition meter By using a body composition meter, you can know your own body composition, and also advise on lifestyle habits such as eating and drinking and exercising necessary to obtain a body composition with low health risk and a target body composition. Is possible (see, for example, Japanese Patent Application Laid-Open No. 2009-5904). However, a person who does not have a body composition meter cannot obtain information on such body composition, advice, and health information such as health risks.
  • One of the purposes of this disclosure is to provide an information providing system that can obtain body composition or health information based on body composition even without a body composition meter.
  • One aspect is an information providing system, in which a health examination data acquisition unit that acquires health examination data, a body composition estimation unit that estimates body composition based on the health examination data, and the body composition or the body composition. It has a configuration including an output unit that outputs based health information.
  • the output unit may output health guidance information that promotes maintenance or recovery of health as the health information, or may output health risk information indicating a health risk.
  • the health examination data acquisition unit may acquire at least height, weight, and biochemical test values as the health examination data.
  • the body composition estimation unit has, as the body composition, fat ratio, fat mass, defatted fat mass, muscle mass, visceral fat mass, visceral fat level, visceral fat area, subcutaneous fat mass, basal metabolic rate, bone mass, body water. At least one of rate, BMI, intracellular fluid volume, and extracellular fluid volume may be estimated.
  • the body composition estimation unit may estimate the body composition based on the change (change tendency or change tendency and its amount) of the health diagnosis data.
  • the body composition can be estimated more accurately than when simply using the health diagnosis data.
  • the information providing system may consist of a computer connected to a communication network, and the health examination data acquisition unit may acquire the health examination data from an arbitrary terminal via the communication network.
  • the output unit transmits the body composition estimated based on the health examination data or the health information based on the body composition to the terminal that has acquired the health examination data via the communication network. Good.
  • the information providing system can collect the health diagnosis data of many users and analyze the health diagnosis data of many of these users.
  • the information providing system may further include a health information acquisition unit that statistically processes the body composition of the plurality of users to acquire the overall health information of the plurality of users, and the output unit may include the output unit. As the health information based on the body composition, the overall health information of the plurality of users may be output.
  • the health examination data acquisition unit may acquire a health examination result and a health examination target value as the health examination data, and the body composition estimation unit actually measures and estimates the body composition based on the health examination result.
  • the body composition may be estimated, and the target estimated body composition may be estimated as the body composition based on the health diagnosis target value, and the output unit can compare the actually measured estimated body composition with the target estimated body composition. You may output it.
  • the difference between the health diagnosis result and the health diagnosis target value can be recognized as the difference in body composition without using a body composition meter.
  • the information providing system may further include a body composition measuring unit that measures body composition and acquires an actually measured body composition, and the health examination data acquisition unit acquires a health examination target value as the health examination data.
  • the body composition estimation unit may estimate the target estimated body composition as the body composition based on the health diagnosis target value, and the output unit may estimate the measured body composition and the target estimated body composition. The output may be comparable.
  • the health examination data acquisition unit acquires the health examination data targeted by the user, so that the body composition estimation unit can estimate the body composition targeted by the user. Then, the user can compare the measured body composition with the target value of the body composition when the measurement is performed by the body composition measurement unit, and the body composition measurement unit determines whether or not the target health diagnosis value is approached. It can be known by the measurement by.
  • One aspect of the information providing program has a configuration in which a computer is made to acquire health examination data, estimate body composition from the health examination data, and output the body composition or health information based on the body composition.
  • the body composition can be estimated and provided from the health diagnosis data, or the health information based on the body composition can be provided without using the body composition meter.
  • FIG. 1 is a diagram showing an information providing system of the embodiment.
  • FIG. 2 is a graph showing the relationship between HDL cholesterol (horizontal axis), which is health examination data (biochemical test value), and fat mass (kg) (vertical axis), which is body composition.
  • FIG. 3 is a graph showing the relationship between the fat mass estimated by inputting a plurality of types of health diagnosis data in a multiple regression equation (horizontal axis) and the actually measured fat mass (vertical axis).
  • FIG. 4 is a block diagram showing a configuration of a first application example of the information providing system of the embodiment.
  • FIG. 5 is a block diagram showing a configuration of a second application example of the information providing system of the embodiment.
  • FIG. 1 is a diagram showing an information providing system of the embodiment.
  • FIG. 2 is a graph showing the relationship between HDL cholesterol (horizontal axis), which is health examination data (biochemical test value), and fat mass (kg) (vertical axis), which is body composition.
  • FIG. 6 is a diagram showing an example of a display screen by an output unit in the second application example of the information providing system of the embodiment.
  • FIG. 7 is a block diagram showing a configuration of a third application example of the information providing system of the embodiment.
  • FIG. 8 is a diagram showing an example of a display screen by an output unit in the third application example of the information providing system of the embodiment.
  • FIG. 1 is a diagram showing an information providing system of the embodiment.
  • the information providing system 10 includes a health diagnosis data acquisition unit 11, a body composition estimation unit 12, a health information acquisition unit 13, and an output unit 14.
  • the health examination data acquisition unit 11 acquires the health examination data by accepting the input of the health examination result obtained by the user undergoing the health examination.
  • the health examination data includes the numerical values of each item examined in the health examination.
  • the inspection items of the health examination include “physical measurement” including height, weight, etc., blood pressure, "Physiology” including electrocardiogram, “X-ray / ultrasound” including chest X-ray, abdominal ultrasound, etc., “Biochemistry” including total cholesterol, HDL cholesterol, LDL cholesterol, ⁇ -GTP, blood sugar, etc. Includes “hematology” including leukocytes and the like, “serology” including CRP and the like, “urine” and “stool”.
  • the health diagnosis data acquisition unit 11 acquires data of some or all of these measured values as health diagnosis data.
  • the health diagnosis data includes the age, gender, individual identification data, and the like of the subject.
  • the body composition estimation unit 12 estimates the body composition corresponding to the health examination data based on the health examination data acquired by the health examination data acquisition unit 11.
  • FIG. 2 is a graph showing the relationship between HDL cholesterol (horizontal axis), which is health examination data (of which biochemical test values), and fat mass (kg) (vertical axis), which is body composition.
  • HDL cholesterol and fat mass are generally related to the fact that the higher the HDL cholesterol, the lower the fat mass, but the variation is relatively large, and the fat mass can be estimated with high accuracy from the HDL cholesterol. It is difficult.
  • the body composition estimation unit 12 calculates the body composition to be estimated by inputting a plurality of types of health diagnosis data into the multiple regression equation obtained by the above multiple regression analysis.
  • This multiple regression equation is obtained by learning the relationship between a large number of pairs of health diagnosis data and body composition to be estimated, and is a kind of learning model.
  • This multiple regression equation is prepared for each body composition to be estimated.
  • multiple regression equations are prepared for each age and gender.
  • the body composition estimation unit 12 has body composition such as fat ratio, fat mass, defatted fat mass, muscle mass, visceral fat mass, visceral fat level, visceral fat area, subcutaneous fat mass, basal metabolic rate, bone mass, and body water content. , BMI, intracellular fluid volume, and some or all of the extracellular fluid volume are estimated.
  • body fat percentage is health diagnosis data such as height, weight, gender, age, fasting blood glucose level, fasting blood insulin, HbA1c, total cholesterol, HDL cholesterol, LDL cholesterol, triglyceride, GOT, GPT, ⁇ - It can be estimated by a multiple regression equation using GTP, uric acid, systolic blood pressure, and diastolic blood pressure as explanatory variables. Further, for example, the visceral fat area can be estimated by a multiple regression equation using the waist circumference and the hip circumference as explanatory variables in addition to the explanatory variables used for the body fat percentage. As described above, the height, weight, and biochemical test values in the health examination data are particularly preferably used for estimating the body composition.
  • FIG. 3 is a graph showing the relationship between the fat mass estimated by inputting a plurality of types of health diagnosis data in a multiple regression equation (horizontal axis) and the actually measured fat mass (vertical axis).
  • the fat mass can be estimated accurately as shown in FIG.
  • other body compositions can be calculated by inputting the health diagnosis data into a multiple regression equation with a plurality of types of health diagnosis data as explanatory variables and the body composition as the objective variable.
  • the health information acquisition unit 13 acquires health information based on the body composition. Specifically, the health information acquisition unit 13 acquires health guidance information that promotes maintenance or recovery of health and health risk information that indicates a health risk as health information.
  • the health guidance information is, for example, information such as the amount of calories that can be ingested, the amount of calories that should be restricted, and the type and amount of exercise that should be performed.
  • Health risk information is, for example, information such as a disease that may be affected and the magnitude of the possibility. In this way, the health information acquisition unit 13 acquires information including specific contents and amounts as health information.
  • the relationship between body composition and health information is stored in the table in advance for each age and gender.
  • the health information may be determined by one kind of body composition or may be determined by a plurality of body compositions.
  • the fat percentage is high, the fat intake should be restricted, but if the basal metabolism is also high, the degree of fat intake restriction may be small.
  • the energy intake should be limited as a measure against obesity, but when the fat percentage is high and the basal metabolism is low at the same time, the risk of postprandial hyperglycemia is likely to increase. Therefore, while focusing on limiting carbohydrates, protein intake should be increased.
  • the health information acquisition unit 13 may determine health information from a plurality of types of body compositions.
  • the output unit 14 outputs the body composition estimated by the body composition estimation unit 12 and the health information acquired by the health information acquisition unit 13.
  • the output format of this information may be display, audio output, or other output format.
  • the above-mentioned health diagnosis data acquisition unit 11, body composition estimation unit 12, health information acquisition unit 13, and output unit 14 are realized by the processor executing the information providing program of the present embodiment.
  • the information providing program may be provided to the information providing system 10 by being downloaded from the communication network by the information providing system 10, or may be provided to the information providing system 10 via a non-temporary recording medium.
  • the health examination data acquisition unit 11 is an interface for acquiring health examination data by wire from an external device, a communication module for acquiring health examination data by wireless communication from an external device, a media reader for reading a health examination from a storage medium, or a user operation. It may be an operation input device that accepts input.
  • the body composition estimation unit 12 and the health information acquisition unit 13 may be a system including a CPU, RAM, and ROM that operate according to an information providing program. Further, the output unit 14 may be a display or a speaker.
  • the body composition can be estimated from the health diagnosis data. Therefore, even a person who does not have a body composition meter can know his / her own body composition.
  • the body composition estimation unit 12 estimates the body composition based on the past health examination data, so that the user knows his / her past body composition. Can be done.
  • the information providing system 10 of the present embodiment even if the body composition meter is not provided, health information based on the body composition can be provided. Those who have undergone a health examination can obtain health information such as health guidance information and health risk information from doctors based on the results of the health examination, but in that case, it tends to be a general theory or a tendency theory. However, in the present embodiment, since the body composition is estimated and the health information is provided based on the estimated body composition, more specific and quantitative health information can be provided. This is because it can be said that the health diagnosis data captures the phenomenon aspect caused by the body composition. Therefore, it is possible to provide specific and quantitative health information by estimating the body composition that is the cause.
  • FIG. 4 is a block diagram showing the configuration of the first application example of the information providing system.
  • the information providing system 10 is composed of a server computer on a communication network.
  • the information providing system 10 is connected to the communication network 20, and a plurality of terminal devices 30 can also be connected to the communication network 20.
  • the communication network 20 may be the Internet or a dedicated network.
  • the information providing system 10 and each terminal device 30 communicate with each other via the communication network 20.
  • the terminal device 30 may be, for example, a smartphone or a personal computer.
  • the health diagnosis data acquisition unit 11 of the information providing system 10 acquires health diagnosis data from an arbitrary terminal device 30 via the communication network 20.
  • the output unit 14 transmits body composition information and health information to the terminal device 30 that has transmitted the health diagnosis data via the communication network 20.
  • the terminal device 30 displays a function for the user to input health examination data, a function for transmitting the input health examination data to the information providing system 10, and a body composition and health information transmitted from the information providing system 10. It has a function. These functions may be realized by a dedicated application program or may be realized by using a general-purpose browsing application.
  • a database 40 is connected to the information providing system 10, and an analyzer 50 is connected to the database 40.
  • the database 40 stores the health diagnosis data received from the plurality of terminal devices 30 by the health diagnosis data acquisition unit 11.
  • the analyzer 50 analyzes a large number of health examination data stored in the database 40. This analysis may be a statistical analysis or some machine learning. As a result, it is possible to analyze the health diagnosis data of many users collected by the information providing system 10.
  • information on the group to which the patient belongs may be added to the health diagnosis data.
  • the health information acquisition unit 13 may statistically process the estimated body composition for each group to acquire the health information of the entire group.
  • health guidance information and health risk information can be provided for each group such as a company, a school, or a community.
  • FIG. 5 is a block diagram showing a configuration of a second application example of the information providing system.
  • the information providing system 10 is composed of a mobile terminal, specifically, a smartphone provided with a touch display.
  • the information providing system 10 includes a health diagnosis data acquisition unit 11, a body composition estimation unit 12, a health information acquisition unit 13, and an output unit 14, as in the above embodiment. These functions are realized by the smartphone executing a dedicated application program (hereinafter, simply referred to as "application").
  • application a dedicated application program
  • the app divides the results obtained by the actual health examination (hereinafter referred to as “health diagnosis results”) and the target values of the health examination (hereinafter referred to as “health examination target values”) as the health examination data. It has a function to input.
  • the health examination data acquisition unit 11 acquires the health examination result and the health examination target value as the health examination data, respectively.
  • the health examination data may be input by the user by operating the touch display, may be input by importing from a file outside the application into the application, or the result of the health examination using the function of the application. You may input by taking a picture of the printed medium with a camera and performing character recognition.
  • the health examination data acquisition unit 11 may acquire the health examination target value by automatic calculation from the health examination result, or may acquire the health examination target value by the above input by the user.
  • the information providing system 10 stores the person's standard health examination value according to age, gender, height, weight, etc. as a table, or An algorithm for calculating a standard health diagnosis value according to age, gender, height, weight, etc. is stored, and the health diagnosis data acquisition unit 11 uses these tables or algorithms to perform a health diagnosis from the health diagnosis results. Get the target value.
  • the body composition estimation unit 12 estimates the body composition based on each of the health examination result and the health examination target value (hereinafter, the body composition estimated based on the health examination result is referred to as "measured estimated body composition”.
  • the body composition estimated based on the health diagnosis target value is called “target estimated body composition”).
  • the health information acquisition unit 13 acquires health guidance information for setting the actually measured estimated body composition to the target estimated value composition.
  • the health information acquisition unit 13 stores information on the content and amount of eating and drinking restrictions and exercise according to the amount of change in body composition for each type of body composition to be improved.
  • the output unit 14 displays the actually measured estimated body composition, the target estimated body composition, and the health information on the touch display. At this time, the output unit 14 displays the actually measured estimated body composition and the target estimated body composition in a comparable format, and the difference between them, that is, the body required to obtain the target estimated body composition from the actually measured estimated body composition. The amount of composition change is also displayed. As a result, the difference between the health diagnosis result and the health diagnosis target value can be recognized as the difference in body composition without using a body composition meter.
  • FIG. 6 is a diagram showing an example of a display screen by the output unit in the second application example.
  • body weight, fat mass, and basal metabolic rate are shown as body composition related to ⁇ -GTP, which is health diagnosis data
  • the target estimated body composition is shown in the "target” column.
  • the "Current status” column shows the measured estimated body composition
  • the "After to target” column shows the measured estimated body composition to be the target estimated body composition (that is, set ⁇ -GTP to a normal value). Therefore, the amount of change (increase / decrease) in body composition required for) is shown.
  • health guidance information and health risk information are further shown as health information. Specifically, the content of food and drink restrictions and the amount of restriction per predetermined period required to make the actually measured body composition the target estimated body composition, the content of exercise, the amount per predetermined period, and the actually measured estimated body composition were maintained. The names and morbidities of the diseases that can sometimes occur are shown.
  • the user can concretely understand what kind of measures should be taken to improve which item of the health diagnosis data based on the health diagnosis result.
  • FIG. 7 is a block diagram showing a configuration of a third application example of the information providing system.
  • the information providing system 10 is composed of a mobile terminal, specifically, a smartphone having a touch display and a short-range wireless communication function.
  • the information providing system 10 includes a health diagnosis data acquisition unit 11, a body composition estimation unit 12, and an output unit 14. Also in this example, each function of the information providing system 10 is realized by the application.
  • the information providing system 10 performs wireless communication with an external body composition measuring device 60 by short-range wireless communication (for example, communication by Bluetooth (registered trademark)).
  • a body composition measuring device 60 bioelectric impedance is measured using 4-pole or 8-pole electrodes and a circuit through which a weak current is passed, and fat is obtained from the measured bioelectric impedance, weight, height, age, and the like.
  • a conventional body composition meter that calculates body composition such as mass, muscle mass, and bone mass can be used.
  • the health diagnosis data acquisition unit 11 acquires the health diagnosis target value as the health diagnosis data.
  • the method of acquiring the health diagnosis target value is the same as that of the second application example.
  • the body composition estimation unit 12 estimates the target estimated body composition as the body composition based on the health diagnosis target value.
  • the information providing system 10 acquires the body composition measured by the body composition measuring device 60 (hereinafter, referred to as “measured body composition”) from the body composition measuring device 60.
  • the output unit 14 displays the target estimated body composition estimated by the body composition estimation unit 12 and the actually measured body composition acquired from the body composition measuring device 60 in a comparable format.
  • FIG. 8 is a diagram showing an example of a display screen by the output unit in the third application example.
  • the body weight, fat mass, and basal metabolic rate are the "target”, "current status", and "after reaching the target” columns as the body composition related to the health diagnosis data ⁇ -GTP.
  • the target estimated body composition is shown in the "Target” column.
  • the "current state” column shows the actually measured body composition measured by the body composition measuring device 60
  • the "after reaching the target” column shows the measured body composition to be the target estimated body composition.
  • the amount of change (increase / decrease) in body composition required for that is, to bring ⁇ -GTP to a normal value) is shown.
  • the information providing system 10 does not have the health information acquisition unit 13, but the health information acquisition unit 13 may be provided as in the second application example.
  • the measured body composition measured by the body composition measuring device 60 is also input to the health information acquisition unit 13, and the measured body composition is targeted by the health information acquisition unit 13 as in the second application example.
  • Health information for obtaining the estimated body composition may be acquired and output by the output unit 14 in the format shown in FIG.
  • the measured body composition is compared with the target estimated body composition for improving the health examination data, and between them. It is possible to confirm how much the difference is and whether the body composition is close to the target estimated body composition.
  • the body composition estimation unit 12 estimates the body composition based on the health examination data, but the body composition estimation unit 12 adds the health examination data to the health examination data.
  • Body composition may be estimated based on changes in. That is, even with the same health diagnosis data, different body compositions may be estimated depending on whether the data is increasing or decreasing, and depending on the degree (change amount). Furthermore, past change trends may also be judged. That is, the most recent tendency (for example, an increasing tendency) may have a different influence on the estimation of body composition depending on whether the tendency is a decreasing tendency or a stable tendency in the past. As a result, the body composition can be estimated more accurately than when the health diagnosis data is simply used.
  • Health diagnosis data acquisition unit 12 Body composition estimation unit 13 Health information acquisition unit 14 Output unit 20 Communication network 30 Terminal device 40 Database 50 Analyzer 60 Body composition measurement device

Abstract

The present disclosure provides an information providing system that makes it possible to acquire a body composition or health information based on a body composition, even if a body composition analyzer is not available. An information providing system (10) has a configuration comprising: a health diagnosis data acquisition unit (11) for acquiring health diagnosis data; a body composition estimation unit (12) for estimating a body composition on the basis of the health diagnosis data; a health information acquisition unit (13) for acquiring health information on the basis of the estimated body composition; and an output unit (14) for outputting the body composition or the health information.

Description

情報提供システム、情報提供プログラム、及びコンピュータ読み取り可能な非一時的記憶媒体Information providing systems, information providing programs, and computer-readable non-temporary storage media 関連出願の相互参照Cross-reference of related applications
　本出願では、２０１９年３月２８日に日本国に出願された特許出願番号２０１９－０６３４８６の利益を主張し、当該出願の内容は引用することによりここに組み込まれているものとする。 This application claims the benefit of patent application number 2019-063486 filed in Japan on March 28, 2019, and the content of the application is incorporated herein by reference.
　本開示は、健康診断データを取得して情報を提供する情報提供システム、情報提供プログラム、及び同プログラムを記録したコンピュータ読み取り可能な非一時的記録媒体に関する。 This disclosure relates to an information providing system that acquires health diagnosis data and provides information, an information providing program, and a computer-readable non-temporary recording medium that records the program.
　従来、身長、体重、年齢、性別等の情報と測定により得られた人体の各部位の生体電気インピーダンスとに基づいて、体組成を測定する体組成計が知られている。 Conventionally, a body composition meter that measures body composition based on information such as height, weight, age, and gender and bioelectrical impedance of each part of the human body obtained by measurement is known.
　一方、健康診断では、血液検査等の検査によってＨＤＬコレステロール、γ－ＧＴＰ、血糖等の生化学検査値が測定される。健康診断では、さらに、これらの生化学検査値と、喫煙習慣、アルコール摂取習慣、運動習慣等の生活習慣とに基づいて、健康リスクの評価や健康維持ないし健康回復のためのアドバイスが行われることがある。 On the other hand, in the health examination, biochemical test values such as HDL cholesterol, γ-GTP, and blood glucose are measured by tests such as blood tests. In the health examination, health risk assessment and advice for maintaining or recovering health should be given based on these biochemical test values and lifestyle habits such as smoking habits, alcohol intake habits, and exercise habits. There is.
　しかしながら、健康診断の結果に基づくリスク評価やアドバイスは、一般論や傾向論に留まり、ユーザ個人の体組成を考慮して、どの程度の健康リスクがあるのか、どの程度の飲食制限をすればよいのか、あるいはどの程度の運動をすればよいかといった定量的な指標を与えることは困難であった。 However, risk evaluations and advice based on the results of health examinations are limited to general theory and tendency theory, and in consideration of the individual body composition of the user, how much health risk there is and how much eating and drinking restrictions should be applied. It was difficult to give a quantitative index such as how much exercise should be done.
　体組成計を用いることで、自らの体組成を知ることができ、さらに、健康リスクの低い体組成や、目標とする体組成を得るために必要な飲食や運動等の生活習慣をアドバイスすることは可能である（例えば、特開２００９－５９０４号公報参照）。しかしながら、体組成計を有していない者は、そのような体組成の情報やアドバイス、健康リスク等の健康情報を得ることはできない。 By using a body composition meter, you can know your own body composition, and also advise on lifestyle habits such as eating and drinking and exercising necessary to obtain a body composition with low health risk and a target body composition. Is possible (see, for example, Japanese Patent Application Laid-Open No. 2009-5904). However, a person who does not have a body composition meter cannot obtain information on such body composition, advice, and health information such as health risks.
　本開示は、体組成計がない場合にも体組成又は体組成に基づく健康情報を得ることができる情報提供システムを提供することを目的の一つとする。 One of the purposes of this disclosure is to provide an information providing system that can obtain body composition or health information based on body composition even without a body composition meter.
　一態様は、情報提供システムであって、健康診断データを取得する健康診断データ取得部と、前記健康診断データに基づいて体組成を推定する体組成推定部と、前記体組成又は前記体組成に基づく健康情報を出力する出力部とを備えた構成を有している。 One aspect is an information providing system, in which a health examination data acquisition unit that acquires health examination data, a body composition estimation unit that estimates body composition based on the health examination data, and the body composition or the body composition. It has a configuration including an output unit that outputs based health information.
　この構成により、体組成計を用いなくても、健康診断データから体組成を推定して提供し、あるいは、体組成に基づく健康情報を提供できる。 With this configuration, it is possible to estimate and provide the body composition from the health diagnosis data or to provide the health information based on the body composition without using the body composition meter.
　前記出力部は、前記健康情報として、健康の維持又は回復を促す健康指導情報を出力してよく、あるいは、健康リスクを示す健康リスク情報を出力してよい。 The output unit may output health guidance information that promotes maintenance or recovery of health as the health information, or may output health risk information indicating a health risk.
　この構成により、ユーザは、健康診断結果に基づいて、健康診断データのどの項目を改善するために、どのような対策をすればよいかを具体的に理解することができる。 With this configuration, the user can concretely understand what kind of measures should be taken to improve which item of the health diagnosis data based on the health diagnosis result.
　前記健康診断データ取得部は、前記健康診断データとして、少なくとも、身長、体重、及び生化学検査値を取得してよい。 The health examination data acquisition unit may acquire at least height, weight, and biochemical test values as the health examination data.
　前記体組成推定部は、前記体組成として、脂肪率、脂肪量、除脂肪量、筋肉量、内臓脂肪量、内臓脂肪レベル、内臓脂肪面積、皮下脂肪量、基礎代謝量、骨量、体水分率、ＢＭＩ、細胞内液量、細胞外液量の少なくともいずれかを推定してよい。 The body composition estimation unit has, as the body composition, fat ratio, fat mass, defatted fat mass, muscle mass, visceral fat mass, visceral fat level, visceral fat area, subcutaneous fat mass, basal metabolic rate, bone mass, body water. At least one of rate, BMI, intracellular fluid volume, and extracellular fluid volume may be estimated.
　前記体組成推定部は、前記健康診断データの変化（変化傾向又は変化傾向とその量）にも基づいて前記体組成を推定してよい。 The body composition estimation unit may estimate the body composition based on the change (change tendency or change tendency and its amount) of the health diagnosis data.
　この構成により、単に健康診断データを用いる場合と比較してより正確に体組成を推定できる。 With this configuration, the body composition can be estimated more accurately than when simply using the health diagnosis data.
　前記情報提供システムは、通信ネットワークに接続されたコンピュータからなるものであってよく、前記健康診断データ取得部は、前記通信ネットワークを介して任意の端末から前記健康診断データを取得してよく、前記出力部は、前記健康診断データを取得した前記端末に対して、前記通信ネットワークを介して、当該健康診断データに基づいて推定された前記体組成又は前記体組成に基づく前記健康情報を送信してよい。 The information providing system may consist of a computer connected to a communication network, and the health examination data acquisition unit may acquire the health examination data from an arbitrary terminal via the communication network. The output unit transmits the body composition estimated based on the health examination data or the health information based on the body composition to the terminal that has acquired the health examination data via the communication network. Good.
　この構成により、情報提供システムは、多くのユーザの健康診断データを収集することができ、これらの多くのユーザの健康診断データを分析することができる。 With this configuration, the information providing system can collect the health diagnosis data of many users and analyze the health diagnosis data of many of these users.
　前記情報提供システムは、複数のユーザの前記体組成を統計的に処理して、前記複数のユーザの全体の健康情報を取得する健康情報取得部をさらに備えていてよく、前記出力部は、前記体組成に基づく健康情報として、前記複数のユーザの全体の健康情報を出力してよい。 The information providing system may further include a health information acquisition unit that statistically processes the body composition of the plurality of users to acquire the overall health information of the plurality of users, and the output unit may include the output unit. As the health information based on the body composition, the overall health information of the plurality of users may be output.
　この構成により、特定のユーザのグループについての健康情報を提供できる。 With this configuration, it is possible to provide health information about a specific group of users.
　前記健康診断データ取得部は、前記健康診断データとして、健康診断結果と健康診断目標値とを取得してよく、前記体組成推定部は、前記健康診断結果に基づいて、前記体組成として実測推定体組成を推定し、前記健康診断目標値に基づいて、前記体組成として目標推定体組成を推定してよく、前記出力部は、前記実測推定体組成と前記目標推定体組成とを比較可能に出力してよい。 The health examination data acquisition unit may acquire a health examination result and a health examination target value as the health examination data, and the body composition estimation unit actually measures and estimates the body composition based on the health examination result. The body composition may be estimated, and the target estimated body composition may be estimated as the body composition based on the health diagnosis target value, and the output unit can compare the actually measured estimated body composition with the target estimated body composition. You may output it.
　この構成により、体組成計を用いなくても、健康診断結果と健康診断目標値との差を体組成の差として認識できる。 With this configuration, the difference between the health diagnosis result and the health diagnosis target value can be recognized as the difference in body composition without using a body composition meter.
　前記情報提供システムは、体組成を測定して実測体組成を取得する体組成測定部をさらに備えていてよく、前記健康診断データ取得部は、前記健康診断データとして、健康診断目標値を取得してよく、前記体組成推定部は、前記健康診断目標値に基づいて、前記体組成として目標推定体組成を推定してよく、前記出力部は、前記実測体組成と前記目標推定体組成とを比較可能に出力してよい。 The information providing system may further include a body composition measuring unit that measures body composition and acquires an actually measured body composition, and the health examination data acquisition unit acquires a health examination target value as the health examination data. The body composition estimation unit may estimate the target estimated body composition as the body composition based on the health diagnosis target value, and the output unit may estimate the measured body composition and the target estimated body composition. The output may be comparable.
　この構成により、健康診断データ取得部が、ユーザが目標とする健康診断データを取得することで、体組成推定部はユーザが目標とする体組成を推定することができる。そうすると、ユーザは、体組成測定部にて測定をしたときに、測定された体組成と体組成の目標値とを比較でき、目標とする健康診断値に近づいているか否かを体組成測定部による測定によって知ることができる。 With this configuration, the health examination data acquisition unit acquires the health examination data targeted by the user, so that the body composition estimation unit can estimate the body composition targeted by the user. Then, the user can compare the measured body composition with the target value of the body composition when the measurement is performed by the body composition measurement unit, and the body composition measurement unit determines whether or not the target health diagnosis value is approached. It can be known by the measurement by.
　一態様の情報提供プログラムは、コンピュータに、健康診断データを取得させ、前記健康診断データから体組成を推定させ、前記体組成又は前記体組成に基づく健康情報を出力させる構成を有している。 One aspect of the information providing program has a configuration in which a computer is made to acquire health examination data, estimate body composition from the health examination data, and output the body composition or health information based on the body composition.
　この構成によっても、体組成計を用いなくても、健康診断データから体組成を推定して提供し、あるいは、体組成に基づく健康情報を提供できる。 With this configuration, the body composition can be estimated and provided from the health diagnosis data, or the health information based on the body composition can be provided without using the body composition meter.
図１は、実施の形態の情報提供システムを示す図である。FIG. 1 is a diagram showing an information providing system of the embodiment. 図２は、健康診断データ（生化学検査値）であるＨＤＬコレステロール（横軸）と体組成である脂肪量（ｋｇ）（縦軸）との関係を示すグラフである。FIG. 2 is a graph showing the relationship between HDL cholesterol (horizontal axis), which is health examination data (biochemical test value), and fat mass (kg) (vertical axis), which is body composition. 図３は、複数種類の健康診断データを重回帰式に入力して推定される脂肪量（横軸）と、実際に測定された脂肪量（縦軸）との関係を示すグラフである。FIG. 3 is a graph showing the relationship between the fat mass estimated by inputting a plurality of types of health diagnosis data in a multiple regression equation (horizontal axis) and the actually measured fat mass (vertical axis). 図４は、実施の形態の情報提供システムの第１の応用例の構成を示すブロック図である。FIG. 4 is a block diagram showing a configuration of a first application example of the information providing system of the embodiment. 図５は、実施の形態の情報提供システムの第２の応用例の構成を示すブロック図である。FIG. 5 is a block diagram showing a configuration of a second application example of the information providing system of the embodiment. 図６は、実施の形態の情報提供システムの第２の応用例における出力部による表示画面の例を示す図である。FIG. 6 is a diagram showing an example of a display screen by an output unit in the second application example of the information providing system of the embodiment. 図７は、実施の形態の情報提供システムの第３の応用例の構成を示すブロック図である。FIG. 7 is a block diagram showing a configuration of a third application example of the information providing system of the embodiment. 図８は、実施の形態の情報提供システムの第３の応用例における出力部による表示画面の例を示す図である。FIG. 8 is a diagram showing an example of a display screen by an output unit in the third application example of the information providing system of the embodiment.
　以下、図面を参照して本開示の実施の形態を説明する。なお、以下に説明する実施の形態は、本開示を実施する場合の一例を示すものであって、本開示を以下に説明する具体的構成に限定するものではない。本開示の実施にあたっては、実施の形態に応じた具体的構成が適宜採用されてよい。 Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. It should be noted that the embodiments described below show an example of the case where the present disclosure is carried out, and the present disclosure is not limited to the specific configuration described below. In carrying out the present disclosure, a specific configuration according to the embodiment may be appropriately adopted.
　図１は、実施の形態の情報提供システムを示す図である。情報提供システム１０は、健康診断データ取得部１１と、体組成推定部１２と、健康情報取得部１３と、出力部１４とを備えている。健康診断データ取得部１１は、ユーザが健康診断を受けて得られた健康診断結果の入力を受け付けることで健康診断データを取得する。健康診断データには、健康診断で検査される各項目の数値が含まれる。 FIG. 1 is a diagram showing an information providing system of the embodiment. The information providing system 10 includes a health diagnosis data acquisition unit 11, a body composition estimation unit 12, a health information acquisition unit 13, and an output unit 14. The health examination data acquisition unit 11 acquires the health examination data by accepting the input of the health examination result obtained by the user undergoing the health examination. The health examination data includes the numerical values of each item examined in the health examination.
　日本人間ドック学会（The Japan Society of Ningen Dock）の平成３０（２０１８）年度一日ドック基本検査項目表によれば、健康診断の検査項目には、身長、体重等を含む「身体計測」、血圧、心電図等を含む「生理」、胸部Ｘ線、腹部超音波等を含む「Ｘ線・超音波」、総コレステロール、ＨＤＬコレステロール、ＬＤＬコレステロール、γ－ＧＴＰ、血糖等を含む「生化学」、赤血球、白血球等を含む「血液学」、ＣＲＰ等を含む「血清学」、「尿」、「便」が含まれる。健康診断データ取得部１１は、健康診断データとして、これらの一部又は全部の計測値のデータを取得する。また、健康診断データには、被検者の年齢、性別、個人の識別データ等も含まれる。 According to the 2018 (2018) 1-day dock basic inspection item table of The Japan Society of Ningen Dock, the inspection items of the health examination include "physical measurement" including height, weight, etc., blood pressure, "Physiology" including electrocardiogram, "X-ray / ultrasound" including chest X-ray, abdominal ultrasound, etc., "Biochemistry" including total cholesterol, HDL cholesterol, LDL cholesterol, γ-GTP, blood sugar, etc. Includes "hematology" including leukocytes and the like, "serology" including CRP and the like, "urine" and "stool". The health diagnosis data acquisition unit 11 acquires data of some or all of these measured values as health diagnosis data. In addition, the health diagnosis data includes the age, gender, individual identification data, and the like of the subject.
　体組成推定部１２は、健康診断データ取得部１１が取得した健康診断データに基づいて、その健康診断データに対応する体組成を推定する。図２は、健康診断データ（のうちの生化学検査値）であるＨＤＬコレステロール（横軸）と体組成である脂肪量（ｋｇ）（縦軸）との関係を示すグラフである。図２に示すように、ＨＤＬコレステロールと脂肪量とは、おおむねＨＤＬコレステロールが高いほど脂肪量が少ないという関係にあるが、そのばらつきは比較的大きく、ＨＤＬコレステロールから脂肪量を高精度に推定することは困難である。 The body composition estimation unit 12 estimates the body composition corresponding to the health examination data based on the health examination data acquired by the health examination data acquisition unit 11. FIG. 2 is a graph showing the relationship between HDL cholesterol (horizontal axis), which is health examination data (of which biochemical test values), and fat mass (kg) (vertical axis), which is body composition. As shown in FIG. 2, HDL cholesterol and fat mass are generally related to the fact that the higher the HDL cholesterol, the lower the fat mass, but the variation is relatively large, and the fat mass can be estimated with high accuracy from the HDL cholesterol. It is difficult.
　しかしながら、複数種類の健康診断データを説明変数として、特定の体組成を目的変数とする重回帰分析を行うことで、健康診断データと体組成との相関関係を得ることができる。そこで、体組成推定部１２は、複数種類の健康診断データを上記の重回帰分析によって得られた重回帰式に入力することで、推定すべき体組成を算出する。この重回帰式は、複数種類の健康診断データと推定すべき体組成との多数の組の関係を学習することで得られるものであり、学習モデルの一種である。この重回帰式は、推定すべき体組成ごとに用意されている。また、重回帰式は、年齢及び性別ごとに用意されている。体組成推定部１２は、体組成として、脂肪率、脂肪量、除脂肪量、筋肉量、内臓脂肪量、内臓脂肪レベル、内臓脂肪面積、皮下脂肪量、基礎代謝量、骨量、体水分率、ＢＭＩ、細胞内液量、細胞外液量の一部又は全部を推定する。 However, it is possible to obtain a correlation between the health examination data and the body composition by performing multiple regression analysis with a specific body composition as the objective variable using a plurality of types of health examination data as explanatory variables. Therefore, the body composition estimation unit 12 calculates the body composition to be estimated by inputting a plurality of types of health diagnosis data into the multiple regression equation obtained by the above multiple regression analysis. This multiple regression equation is obtained by learning the relationship between a large number of pairs of health diagnosis data and body composition to be estimated, and is a kind of learning model. This multiple regression equation is prepared for each body composition to be estimated. In addition, multiple regression equations are prepared for each age and gender. The body composition estimation unit 12 has body composition such as fat ratio, fat mass, defatted fat mass, muscle mass, visceral fat mass, visceral fat level, visceral fat area, subcutaneous fat mass, basal metabolic rate, bone mass, and body water content. , BMI, intracellular fluid volume, and some or all of the extracellular fluid volume are estimated.
　体組成推定部１２が推定する体組成の例を挙げると以下のとおりである。例えば、体脂肪率は、健康診断データである身長、体重、性別、年齢、空腹時血糖値、空腹時血中インスリン、ＨｂＡ１ｃ、総コレステロール、ＨＤＬコレステロール、ＬＤＬコレステロール、トリグリセライド、ＧＯＴ、ＧＰＴ、γ－ＧＴＰ、尿酸、最高血圧、最低血圧を説明変数とする重回帰式によって推定することができる。また、例えば、内臓脂肪面積は、体脂肪率で用いる説明変数に加えて、ウエスト周囲径、ヒップ周囲径を説明変数とする重回帰式によって推定することができる。このように、健康診断データのうちの身長、体重、生化学検査値は特に体組成を推定するのに好適に用いられる。 An example of the body composition estimated by the body composition estimation unit 12 is as follows. For example, body fat percentage is health diagnosis data such as height, weight, gender, age, fasting blood glucose level, fasting blood insulin, HbA1c, total cholesterol, HDL cholesterol, LDL cholesterol, triglyceride, GOT, GPT, γ- It can be estimated by a multiple regression equation using GTP, uric acid, systolic blood pressure, and diastolic blood pressure as explanatory variables. Further, for example, the visceral fat area can be estimated by a multiple regression equation using the waist circumference and the hip circumference as explanatory variables in addition to the explanatory variables used for the body fat percentage. As described above, the height, weight, and biochemical test values in the health examination data are particularly preferably used for estimating the body composition.
　図３は、複数種類の健康診断データを重回帰式に入力して推定される脂肪量（横軸）と、実際に測定された脂肪量（縦軸）との関係を示すグラフである。適切に重回帰式を生成することで、図３に示すように精度よく脂肪量を推定することができる。他の体組成についても同様に、複数種類の健康診断データを説明変数とし体組成を目的変数とする重回帰式に健康診断データを入力することで算出することができる。 FIG. 3 is a graph showing the relationship between the fat mass estimated by inputting a plurality of types of health diagnosis data in a multiple regression equation (horizontal axis) and the actually measured fat mass (vertical axis). By appropriately generating the multiple regression equation, the fat mass can be estimated accurately as shown in FIG. Similarly, other body compositions can be calculated by inputting the health diagnosis data into a multiple regression equation with a plurality of types of health diagnosis data as explanatory variables and the body composition as the objective variable.
　健康情報取得部１３は、体組成に基づいて健康情報を取得する。具体的には、健康情報取得部１３は、健康情報として、健康の維持又は回復を促す健康指導情報、及び健康リスクを示す健康リスク情報を取得する。健康指導情報は、例えば、摂取してよいカロリー量、制限すべきカロリー量、行うべき運動の種類と量等の情報である。健康リスク情報は、例えば、患う可能性のある疾患とその可能性の大きさ等の情報である。このように、健康情報取得部１３は、健康情報として、具体的な内容と量を含む情報を取得する。 The health information acquisition unit 13 acquires health information based on the body composition. Specifically, the health information acquisition unit 13 acquires health guidance information that promotes maintenance or recovery of health and health risk information that indicates a health risk as health information. The health guidance information is, for example, information such as the amount of calories that can be ingested, the amount of calories that should be restricted, and the type and amount of exercise that should be performed. Health risk information is, for example, information such as a disease that may be affected and the magnitude of the possibility. In this way, the health information acquisition unit 13 acquires information including specific contents and amounts as health information.
　体組成と健康情報との関係は、年齢及び性別ごとにあらかじめテーブルに記憶されている。ここで、健康情報は、一種類の体組成によって決定されてもよいし、複数の体組成によって決定されてもよい。例えば、脂肪率が高い場合には、脂分の摂取を制限すべきであるが、同時に基礎代謝も高い場合には脂分摂取制限の度合いは小さくてよい。また、例えば、脂肪率が高い場合には、肥満対策として摂取エネルギーを制限すべきであるが、脂肪率が高いだけでなく同時に基礎代謝が低い場合は、食後高血糖のリスクがより高まりやすいことから、糖質を重点的に制限するとともに、蛋白質の摂取は増やすべきである。また、例えば、脂肪率が高くても基礎代謝が充分に高い場合は、軽めの摂取エネルギー制限程度でよく、蛋白質量摂取の増加も重視しなくてもよい。このように、健康情報取得部１３は、複数種類の体組成から健康情報を決定してよい。 The relationship between body composition and health information is stored in the table in advance for each age and gender. Here, the health information may be determined by one kind of body composition or may be determined by a plurality of body compositions. For example, if the fat percentage is high, the fat intake should be restricted, but if the basal metabolism is also high, the degree of fat intake restriction may be small. In addition, for example, when the fat percentage is high, the energy intake should be limited as a measure against obesity, but when the fat percentage is high and the basal metabolism is low at the same time, the risk of postprandial hyperglycemia is likely to increase. Therefore, while focusing on limiting carbohydrates, protein intake should be increased. Further, for example, when the basal metabolism is sufficiently high even if the fat percentage is high, a light energy intake limit may be sufficient, and an increase in protein mass intake may not be emphasized. In this way, the health information acquisition unit 13 may determine health information from a plurality of types of body compositions.
　出力部１４は、体組成推定部１２で推定された体組成、及び健康情報取得部１３で取得された健康情報を出力する。これらの情報の出力形式は、表示、音声出力、その他の出力形式であってよい。 The output unit 14 outputs the body composition estimated by the body composition estimation unit 12 and the health information acquired by the health information acquisition unit 13. The output format of this information may be display, audio output, or other output format.
　上記の健康診断データ取得部１１、体組成推定部１２、健康情報取得部１３、及び出力部１４は、プロセッサが本実施の形態の情報提供プログラムを実行することにより実現される。情報提供プログラムは、情報提供システム１０が通信ネットワークからダウンロードすることで情報提供システム１０に提供されてもよく、あるいは、非一時的な記録媒体を介して情報提供システム１０に提供されてもよい。 The above-mentioned health diagnosis data acquisition unit 11, body composition estimation unit 12, health information acquisition unit 13, and output unit 14 are realized by the processor executing the information providing program of the present embodiment. The information providing program may be provided to the information providing system 10 by being downloaded from the communication network by the information providing system 10, or may be provided to the information providing system 10 via a non-temporary recording medium.
　健康診断データ取得部１１は、外部装置から有線で健康診断データを取得するインターフェース、外部装置から無線通信によって健康診断データを取得する通信モジュール、記憶媒体から健康診断を読み出すメディアリーダ、又はユーザの操作入力を受け付ける操作入力装置であってよい。体組成推定部１２及び健康情報取得部１３は、情報提供プログラムに従って動作するＣＰＵ、ＲＡＭ、ＲＯＭを含むシステムであってよい。また、出力部１４は、ディスプレイやスピーカであってよい。 The health examination data acquisition unit 11 is an interface for acquiring health examination data by wire from an external device, a communication module for acquiring health examination data by wireless communication from an external device, a media reader for reading a health examination from a storage medium, or a user operation. It may be an operation input device that accepts input. The body composition estimation unit 12 and the health information acquisition unit 13 may be a system including a CPU, RAM, and ROM that operate according to an information providing program. Further, the output unit 14 may be a display or a speaker.
　以上のように、本実施の形態の情報提供システム１０によれば、健康診断データから体組成を推定できる。よって、体組成計を有していない者であっても、自分の体組成を知ることができる。ユーザが過去の健康診断データを保有している場合には、体組成推定部１２が当該過去の健康診断データに基づいて体組成を推定することで、ユーザは自分の過去の体組成を知ることができる。 As described above, according to the information providing system 10 of the present embodiment, the body composition can be estimated from the health diagnosis data. Therefore, even a person who does not have a body composition meter can know his / her own body composition. When the user has past health examination data, the body composition estimation unit 12 estimates the body composition based on the past health examination data, so that the user knows his / her past body composition. Can be done.
　また、本実施の形態の情報提供システム１０によれば、体組成計を有していない場合にも、体組成に基づく健康情報の提供を受けることができる。健康診断を受けた者は、健康診断結果に基づいて医師等から健康指導情報や健康リスク情報等の健康情報を得ることも可能であるが、その場合には一般論や傾向論になりがちであるところ、本実施の形態では、体組成を推定した上で、推定した体組成に基づいて健康情報を提供するので、より具体的で定量的な健康情報を提供できる。これは、健康診断データは、体組成を原因として生じる現象面を捉えたものであるということができるからである。そのため、原因である体組成を推定することで具体的かつ定量的な健康情報を提供できることになる。 Further, according to the information providing system 10 of the present embodiment, even if the body composition meter is not provided, health information based on the body composition can be provided. Those who have undergone a health examination can obtain health information such as health guidance information and health risk information from doctors based on the results of the health examination, but in that case, it tends to be a general theory or a tendency theory. However, in the present embodiment, since the body composition is estimated and the health information is provided based on the estimated body composition, more specific and quantitative health information can be provided. This is because it can be said that the health diagnosis data captures the phenomenon aspect caused by the body composition. Therefore, it is possible to provide specific and quantitative health information by estimating the body composition that is the cause.
　以下、上記の情報提供システム１０の具体的な応用例及び変形例を説明する。 Hereinafter, specific application examples and modification examples of the above information providing system 10 will be described.
　図４は、情報提供システムの第１の応用例の構成を示すブロック図である。この例では、情報提供システム１０は、通信ネットワーク上のサーバコンピュータによって構成される。情報提供システム１０は、通信ネットワーク２０に接続されており、複数の端末装置３０も通信ネットワーク２０に接続可能である。通信ネットワーク２０は、インターネットであっても専用ネットワークであってもよい。情報提供システム１０と各端末装置３０とは通信ネットワーク２０を介して互いに通信を行う。端末装置３０は、例えば、スマートフォンやパソコンであってよい。 FIG. 4 is a block diagram showing the configuration of the first application example of the information providing system. In this example, the information providing system 10 is composed of a server computer on a communication network. The information providing system 10 is connected to the communication network 20, and a plurality of terminal devices 30 can also be connected to the communication network 20. The communication network 20 may be the Internet or a dedicated network. The information providing system 10 and each terminal device 30 communicate with each other via the communication network 20. The terminal device 30 may be, for example, a smartphone or a personal computer.
　情報提供システム１０の健康診断データ取得部１１は、通信ネットワーク２０を介して任意の端末装置３０から健康診断データを取得する。また、出力部１４は、健康診断データを送信してきた端末装置３０に対して、通信ネットワーク２０を介して体組成情報や健康情報を送信する。この構成により、端末装置３０のユーザは、自己の健康診断データを端末装置３０に入力して情報提供システム１０に送信すると、情報提供システム１０から、自己の健康診断データから推定された体組成の情報や健康情報を受信して、端末装置３０にて出力（表示）することができる。 The health diagnosis data acquisition unit 11 of the information providing system 10 acquires health diagnosis data from an arbitrary terminal device 30 via the communication network 20. In addition, the output unit 14 transmits body composition information and health information to the terminal device 30 that has transmitted the health diagnosis data via the communication network 20. With this configuration, when the user of the terminal device 30 inputs his / her own health examination data into the terminal device 30 and transmits it to the information providing system 10, the body composition estimated from his / her own health examination data from the information providing system 10 Information and health information can be received and output (displayed) on the terminal device 30.
　端末装置３０には、ユーザが健康診断データを入力する機能、入力された健康診断データを情報提供システム１０に送信する機能、及び情報提供システム１０から送信されてきた体組成及び健康情報を表示する機能を備えている。これらの機能は専用のアプリケーションプログラムによって実現されてもよく、汎用のブラウジングアプリケーションを用いて実現されてもよい。 The terminal device 30 displays a function for the user to input health examination data, a function for transmitting the input health examination data to the information providing system 10, and a body composition and health information transmitted from the information providing system 10. It has a function. These functions may be realized by a dedicated application program or may be realized by using a general-purpose browsing application.
　また、図４に示すように、情報提供システム１０にはデータベース４０が接続されており、データベース４０には分析装置５０が接続されている。データベース４０には、健康診断データ取得部１１が複数の端末装置３０から受信した健康診断データを記憶する。分析装置５０は、データベース４０に記憶された多数の健康診断データを分析する。この分析は、統計分析であってよく、あるいは何らかの機械学習であってもよい。これにより、情報提供システム１０が収集した多くのユーザの健康診断データを分析できる。 Further, as shown in FIG. 4, a database 40 is connected to the information providing system 10, and an analyzer 50 is connected to the database 40. The database 40 stores the health diagnosis data received from the plurality of terminal devices 30 by the health diagnosis data acquisition unit 11. The analyzer 50 analyzes a large number of health examination data stored in the database 40. This analysis may be a statistical analysis or some machine learning. As a result, it is possible to analyze the health diagnosis data of many users collected by the information providing system 10.
　また、本例において、健康診断データに所属グループ（例えば、会社、学校、地域等）の情報が付加されてもよい。この場合には、健康情報取得部１３は、推定された体組成を所属グループごとに統計的に処理して、グループ全体の健康情報を取得してよい。これにより、会社、学校、地域といったグループ単位で健康指導情報や健康リスク情報を提供することができる。 Further, in this example, information on the group to which the patient belongs (for example, company, school, area, etc.) may be added to the health diagnosis data. In this case, the health information acquisition unit 13 may statistically process the estimated body composition for each group to acquire the health information of the entire group. As a result, health guidance information and health risk information can be provided for each group such as a company, a school, or a community.
　図５は、情報提供システムの第２の応用例の構成を示すブロック図である。この例では、情報提供システム１０は、携帯端末、具体的には、タッチディスプレイを備えたスマートフォンによって構成される。情報提供システム１０は、上記の実施の形態と同様に、健康診断データ取得部１１と、体組成推定部１２と、健康情報取得部１３と、出力部１４とを備えている。これらの機能は、スマートフォンが専用のアプリケーションプログラム（以下、単に「アプリ」という。）を実行することにより実現される。 FIG. 5 is a block diagram showing a configuration of a second application example of the information providing system. In this example, the information providing system 10 is composed of a mobile terminal, specifically, a smartphone provided with a touch display. The information providing system 10 includes a health diagnosis data acquisition unit 11, a body composition estimation unit 12, a health information acquisition unit 13, and an output unit 14, as in the above embodiment. These functions are realized by the smartphone executing a dedicated application program (hereinafter, simply referred to as "application").
　アプリは、健康診断データとして、実際の健康診断によって得られた結果（以下、「健康診断結果」という。）と、健康診断の目標値（以下、「健康診断目標値」という。）とを分けて入力する機能を備えている。健康診断データ取得部１１は、健康診断データとして、健康診断結果と、健康診断目標値をそれぞれ取得する。なお、健康診断データは、ユーザがタッチディスプレイを操作して入力してもよく、アプリ外のファイルからアプリにインポートすることで入力してもよく、あるいは、アプリの機能を用いて健康診断の結果を印刷した媒体をカメラで撮影して文字認識をすることで入力してもよい。 The app divides the results obtained by the actual health examination (hereinafter referred to as "health diagnosis results") and the target values of the health examination (hereinafter referred to as "health examination target values") as the health examination data. It has a function to input. The health examination data acquisition unit 11 acquires the health examination result and the health examination target value as the health examination data, respectively. The health examination data may be input by the user by operating the touch display, may be input by importing from a file outside the application into the application, or the result of the health examination using the function of the application. You may input by taking a picture of the printed medium with a camera and performing character recognition.
　また、健康診断データ取得部１１は、健康診断結果から自動計算により健康診断目標値を取得してもよいし、ユーザによる上記の入力によって健康診断目標値を取得してもよい。自動計算により健康診断目標値を取得する場合には、情報提供システム１０には、年齢、性別、身長、体重等に応じたその者の標準的な健康診断値がテーブルとして記憶されており、あるいは、年齢、性別、身長、体重等に応じた標準的な健康診断値を演算するアルゴリズムが記憶されており、健康診断データ取得部１１は、これらのテーブル又はアルゴリズムを用いて健康診断結果から健康診断目標値を取得する。 Further, the health examination data acquisition unit 11 may acquire the health examination target value by automatic calculation from the health examination result, or may acquire the health examination target value by the above input by the user. When the health examination target value is acquired by automatic calculation, the information providing system 10 stores the person's standard health examination value according to age, gender, height, weight, etc. as a table, or An algorithm for calculating a standard health diagnosis value according to age, gender, height, weight, etc. is stored, and the health diagnosis data acquisition unit 11 uses these tables or algorithms to perform a health diagnosis from the health diagnosis results. Get the target value.
　体組成推定部１２は、健康診断結果及び健康診断目標値のそれぞれに基づいて、体組成を推定する（以下、健康診断結果に基づいて推定された体組成を「実測推定体組成」といい、健康診断目標値に基づいて推定された体組成を「目標推定体組成」という。）。 The body composition estimation unit 12 estimates the body composition based on each of the health examination result and the health examination target value (hereinafter, the body composition estimated based on the health examination result is referred to as "measured estimated body composition". The body composition estimated based on the health diagnosis target value is called "target estimated body composition").
　健康情報取得部１３は、改善すべき体組成がある場合には、実測推定体組成を目標推定値組成にするための健康指導情報を取得する。このために、健康情報取得部１３は、改善すべき体組成の種類ごとに、体組成の変化量に応じた飲食制限及び運動の内容及び量の情報が記憶されている。 When there is a body composition to be improved, the health information acquisition unit 13 acquires health guidance information for setting the actually measured estimated body composition to the target estimated value composition. For this purpose, the health information acquisition unit 13 stores information on the content and amount of eating and drinking restrictions and exercise according to the amount of change in body composition for each type of body composition to be improved.
　出力部１４は、実測推定体組成と目標推定体組成と健康情報とをタッチディスプレイに表示する。このとき、出力部１４は、実測推定体組成と目標推定体組成とを比較可能な形式で表示し、かつ、それらの差分、即ち実測推定体組成から目標推定体組成になるために必要な体組成変化量も表示する。これにより、体組成計を用いなくても、健康診断結果と健康診断目標値との差を体組成の差として認識できる。 The output unit 14 displays the actually measured estimated body composition, the target estimated body composition, and the health information on the touch display. At this time, the output unit 14 displays the actually measured estimated body composition and the target estimated body composition in a comparable format, and the difference between them, that is, the body required to obtain the target estimated body composition from the actually measured estimated body composition. The amount of composition change is also displayed. As a result, the difference between the health diagnosis result and the health diagnosis target value can be recognized as the difference in body composition without using a body composition meter.
　図６は、第２の応用例における出力部による表示画面の例を示す図である。この画面では、健康診断データであるγ－ＧＴＰに関連する体組成として、体重、脂肪量、基礎代謝量が示されており、「目標」の列には目標推定体組成が示されており、「現状」の列には実測推定体組成が示されており、「目標まであと」の列には、実測推定体組成を目標推定体組成にするため（即ち、γ－ＧＴＰを正常値にするため）に必要な体組成の変化量（増減量）が示されている。 FIG. 6 is a diagram showing an example of a display screen by the output unit in the second application example. On this screen, body weight, fat mass, and basal metabolic rate are shown as body composition related to γ-GTP, which is health diagnosis data, and the target estimated body composition is shown in the "target" column. The "Current status" column shows the measured estimated body composition, and the "After to target" column shows the measured estimated body composition to be the target estimated body composition (that is, set γ-GTP to a normal value). Therefore, the amount of change (increase / decrease) in body composition required for) is shown.
　図６の画面では、更に、健康情報として、健康指導情報と健康リスク情報とが示されている。具体的には、実測推定体組成を目標推定体組成にするために必要な飲食の制限内容及び所定期間あたりの制限量、並びに運動の内容及び所定期間あたりの量、実測推定体組成を維持したときに罹患する可能性がある疾患名と罹患率が示されている。 On the screen of FIG. 6, health guidance information and health risk information are further shown as health information. Specifically, the content of food and drink restrictions and the amount of restriction per predetermined period required to make the actually measured body composition the target estimated body composition, the content of exercise, the amount per predetermined period, and the actually measured estimated body composition were maintained. The names and morbidities of the diseases that can sometimes occur are shown.
　この応用例によれば、ユーザは、健康診断結果に基づいて、健康診断データのどの項目を改善するために、どのような対策をすればよいかを具体的に理解することができる。 According to this application example, the user can concretely understand what kind of measures should be taken to improve which item of the health diagnosis data based on the health diagnosis result.
　図７は、情報提供システムの第３の応用例の構成を示すブロック図である。この例では、情報提供システム１０は、携帯端末、具体的には、タッチディスプレイ及び近距離無線通信機能を備えたスマートフォンによって構成される。情報提供システム１０は、健康診断データ取得部１１と、体組成推定部１２と、出力部１４とを備えている。本例においても、情報提供システム１０の各機能はアプリによって実現される。 FIG. 7 is a block diagram showing a configuration of a third application example of the information providing system. In this example, the information providing system 10 is composed of a mobile terminal, specifically, a smartphone having a touch display and a short-range wireless communication function. The information providing system 10 includes a health diagnosis data acquisition unit 11, a body composition estimation unit 12, and an output unit 14. Also in this example, each function of the information providing system 10 is realized by the application.
　情報提供システム１０は、外部の体組成測定装置６０と近距離無線通信（例えば、Ｂｌｕｅｔｏｏｔｈ（登録商標）による通信）により、無線通信を行う。体組成測定装置６０として、４極又は８極の電極及びそれらの微弱の電流を流す回路を用いて生体電気インピーダンスを測定し、測定された生体電気インピーダンス、体重、身長、年齢等の情報から脂肪量、筋肉量、骨量等の体組成を算出する従来の体組成計を用いることができる。 The information providing system 10 performs wireless communication with an external body composition measuring device 60 by short-range wireless communication (for example, communication by Bluetooth (registered trademark)). As a body composition measuring device 60, bioelectric impedance is measured using 4-pole or 8-pole electrodes and a circuit through which a weak current is passed, and fat is obtained from the measured bioelectric impedance, weight, height, age, and the like. A conventional body composition meter that calculates body composition such as mass, muscle mass, and bone mass can be used.
　健康診断データ取得部１１は、健康診断データとして、健康診断目標値を取得する。健康診断目標値の取得の方法は第２の応用例と同様である。体組成推定部１２は、健康診断目標値に基づいて、体組成として目標推定体組成を推定する。一方で、情報提供システム１０は、体組成測定装置６０から、体組成測定装置６０にて測定された体組成（以下、「実測体組成」という。）を取得する。出力部１４は、体組成推定部１２にて推定された目標推定体組成と、体組成測定装置６０から取得した実測体組成とを比較可能な形式で表示する。 The health diagnosis data acquisition unit 11 acquires the health diagnosis target value as the health diagnosis data. The method of acquiring the health diagnosis target value is the same as that of the second application example. The body composition estimation unit 12 estimates the target estimated body composition as the body composition based on the health diagnosis target value. On the other hand, the information providing system 10 acquires the body composition measured by the body composition measuring device 60 (hereinafter, referred to as “measured body composition”) from the body composition measuring device 60. The output unit 14 displays the target estimated body composition estimated by the body composition estimation unit 12 and the actually measured body composition acquired from the body composition measuring device 60 in a comparable format.
　図８は、第３の応用例における出力部による表示画面の例を示す図である。この画面では、図６と同様に、健康診断データであるγ－ＧＴＰに関連する体組成として、体重、脂肪量、基礎代謝量が「目標」、「現状」、「目標まであと」の各列に示されており、「目標」の列には目標推定体組成が示されている。本応用例では、「現状」の列には、体組成測定装置６０で測定された実測体組成が示され、「目標まであと」の列には、実測体組成を目標推定体組成にするため（即ち、γ－ＧＴＰを正常値にするため）に必要な体組成の変化量（増減量）が示されている。 FIG. 8 is a diagram showing an example of a display screen by the output unit in the third application example. On this screen, as in FIG. 6, the body weight, fat mass, and basal metabolic rate are the "target", "current status", and "after reaching the target" columns as the body composition related to the health diagnosis data γ-GTP. The target estimated body composition is shown in the "Target" column. In this application example, the "current state" column shows the actually measured body composition measured by the body composition measuring device 60, and the "after reaching the target" column shows the measured body composition to be the target estimated body composition. The amount of change (increase / decrease) in body composition required for (that is, to bring γ-GTP to a normal value) is shown.
　なお、第３の応用例は、情報提供システム１０が健康情報取得部１３を備えていないが、第２の応用例と同様に、健康情報取得部１３を設けてもよい。この場合には、体組成測定装置６０で測定された実測体組成は、健康情報取得部１３にも入力され、第２の応用例と同様に、健康情報取得部１３にて実測体組成を目標推定体組成にするための健康情報が取得されて、出力部１４で図６に示すような形式で出力されてよい。 In the third application example, the information providing system 10 does not have the health information acquisition unit 13, but the health information acquisition unit 13 may be provided as in the second application example. In this case, the measured body composition measured by the body composition measuring device 60 is also input to the health information acquisition unit 13, and the measured body composition is targeted by the health information acquisition unit 13 as in the second application example. Health information for obtaining the estimated body composition may be acquired and output by the output unit 14 in the format shown in FIG.
　第３の応用例によれば、体組成測定装置で体組成を測定するごとに、測定された体組成と健康診断データを改善するための目標推定体組成とを比較して、それらの間にどの程度の差があるか、体組成が目標推定体組成に近づいているかを確認することができる。 According to the third application example, each time the body composition is measured by the body composition measuring device, the measured body composition is compared with the target estimated body composition for improving the health examination data, and between them. It is possible to confirm how much the difference is and whether the body composition is close to the target estimated body composition.
　なお、上記の実施の形態及びその応用例では、体組成推定部１２は、健康診断データに基づいて体組成を推定したが、体組成推定部１２は、健康診断データに加えて、健康診断データの変化にも基づいて体組成を推定してよい。すなわち、同じ健康診断データであっても、増加傾向にあるのか減少傾向にあるのかによって、また、その度合い（変化量）によって、異なる体組成が推定されてよい。さらに過去の変化傾向も併せて判断してもよい。すなわち、直近の傾向（例えば増加傾向）が、以前は減少傾向であった場合と安定傾向であった場合とで、体組成の推定に異なる影響を与えてもよい。これにより、単に健康診断データを用いる場合と比較してより正確に体組成を推定できる。 In the above-described embodiment and its application example, the body composition estimation unit 12 estimates the body composition based on the health examination data, but the body composition estimation unit 12 adds the health examination data to the health examination data. Body composition may be estimated based on changes in. That is, even with the same health diagnosis data, different body compositions may be estimated depending on whether the data is increasing or decreasing, and depending on the degree (change amount). Furthermore, past change trends may also be judged. That is, the most recent tendency (for example, an increasing tendency) may have a different influence on the estimation of body composition depending on whether the tendency is a decreasing tendency or a stable tendency in the past. As a result, the body composition can be estimated more accurately than when the health diagnosis data is simply used.
　１０　情報提供システム
　１１　健康診断データ取得部
　１２　体組成推定部
　１３　健康情報取得部
　１４　出力部
　２０　通信ネットワーク
　３０　端末装置
　４０　データベース
　５０　分析装置
　６０　体組成測定装置 10 Information provision system 11 Health diagnosis data acquisition unit 12 Body composition estimation unit 13 Health information acquisition unit 14 Output unit 20 Communication network 30 Terminal device 40 Database 50 Analyzer 60 Body composition measurement device

Claims (12)

  1. 　健康診断データを取得する健康診断データ取得部と、
    　前記健康診断データに基づいて体組成を推定する体組成推定部と、
    　前記体組成又は前記体組成に基づく健康情報を出力する出力部と、
    　を備えた、情報提供システム。     The Health Examination Data Acquisition Department, which acquires health examination data,
    A body composition estimation unit that estimates body composition based on the health diagnosis data,
    An output unit that outputs the body composition or health information based on the body composition,
    Information provision system equipped with.
  2. 　前記出力部は、前記健康情報として、健康の維持又は回復を促す健康指導情報を出力する、請求項１に記載の情報提供システム。 The information providing system according to claim 1, wherein the output unit outputs health guidance information that promotes maintenance or recovery of health as the health information.
  3. 　前記出力部は、前記健康情報として、健康リスクを示す健康リスク情報を出力する、請求項１に記載の情報提供システム。 The information providing system according to claim 1, wherein the output unit outputs health risk information indicating a health risk as the health information.
  4. 　前記健康診断データ取得部は、前記健康診断データとして、少なくとも、身長、体重、及び生化学検査値を取得する、請求項１から３のいずれかに記載の情報提供システム。 The information providing system according to any one of claims 1 to 3, wherein the health examination data acquisition unit acquires at least height, weight, and biochemical test values as the health examination data.
  5. 　前記体組成推定部は、前記体組成として、脂肪率、脂肪量、除脂肪量、筋肉量、内臓脂肪量、内臓脂肪レベル、内臓脂肪面積、皮下脂肪量、基礎代謝量、骨量、体水分率、ＢＭＩ、細胞内液量、細胞外液量の少なくともいずれかを推定する、請求項１から４のいずれかに記載の情報提供システム。 The body composition estimation unit has, as the body composition, fat ratio, fat mass, defatted fat mass, muscle mass, visceral fat mass, visceral fat level, visceral fat area, subcutaneous fat mass, basal metabolic rate, bone mass, and body water. The information providing system according to any one of claims 1 to 4, which estimates at least one of the rate, BMI, intracellular fluid volume, and extracellular fluid volume.
  6. 　前記体組成推定部は、前記健康診断データの変化にも基づいて前記体組成を推定する、請求項１から５のいずれかに記載の情報提供システム。 The information providing system according to any one of claims 1 to 5, wherein the body composition estimation unit estimates the body composition based on a change in the health diagnosis data.
  7. 　前記情報提供システムは、通信ネットワークに接続されたコンピュータからなり、
    　前記健康診断データ取得部は、前記通信ネットワークを介して任意の端末から前記健康診断データを取得し、
    　前記出力部は、前記健康診断データを取得した前記端末に対して、前記通信ネットワークを介して、当該健康診断データに基づいて推定された前記体組成又は前記体組成に基づく前記健康情報を送信する、請求項１から６のいずれかに記載の情報提供システム。     The information providing system consists of a computer connected to a communication network.
    The health examination data acquisition unit acquires the health examination data from an arbitrary terminal via the communication network, and obtains the health examination data.
    The output unit transmits the body composition estimated based on the health diagnosis data or the health information based on the body composition to the terminal that has acquired the health diagnosis data via the communication network. , The information providing system according to any one of claims 1 to 6.
  8. 　複数のユーザの前記体組成を統計的に処理して、前記複数のユーザの全体の健康情報を取得する健康情報取得部をさらに備え、
    　前記出力部は、前記体組成に基づく健康情報として、前記複数のユーザの全体の健康情報を出力する、請求項１から７のいずれかに記載の情報提供システム。     Further provided with a health information acquisition unit that statistically processes the body composition of the plurality of users and acquires the overall health information of the plurality of users.
    The information providing system according to any one of claims 1 to 7, wherein the output unit outputs overall health information of the plurality of users as health information based on the body composition.
  9. 　前記健康診断データ取得部は、前記健康診断データとして、健康診断結果と健康診断目標値とを取得し、
    　前記体組成推定部は、前記健康診断結果に基づいて、前記体組成として実測推定体組成を推定し、前記健康診断目標値に基づいて、前記体組成として目標推定体組成を推定し、
    　前記出力部は、前記実測推定体組成と前記目標推定体組成とを比較可能に出力する、請求項１から８のいずれかに記載の情報提供システム。     The health examination data acquisition unit acquires the health examination result and the health examination target value as the health examination data.
    The body composition estimation unit estimates the actual measurement estimated body composition as the body composition based on the health diagnosis result, and estimates the target estimated body composition as the body composition based on the health examination target value.
    The information providing system according to any one of claims 1 to 8, wherein the output unit outputs the actually measured estimated body composition and the target estimated body composition in a comparable manner.
  10. 　体組成を測定して実測体組成を取得する体組成測定部をさらに備え、
    　前記健康診断データ取得部は、前記健康診断データとして、健康診断目標値を取得し、
    　前記体組成推定部は、前記健康診断目標値に基づいて、前記体組成として目標推定体組成を推定し、
    　前記出力部は、前記実測体組成と前記目標推定体組成とを比較可能に出力する、請求項１から８のいずれかに記載の情報提供システム。     Further equipped with a body composition measuring unit that measures body composition and acquires measured body composition,
    The health examination data acquisition unit acquires a health examination target value as the health examination data, and obtains the health examination target value.
    The body composition estimation unit estimates the target estimated body composition as the body composition based on the health diagnosis target value.
    The information providing system according to any one of claims 1 to 8, wherein the output unit outputs the actually measured body composition and the target estimated body composition in a comparable manner.
  11. 　コンピュータに、
    　健康診断データを取得させ、
    　前記健康診断データから体組成を推定させ、
    　前記体組成又は前記体組成に基づく健康情報を出力させる、
    　情報提供プログラム。     On the computer
    Get health check data
    The body composition is estimated from the health diagnosis data, and the body composition is estimated.
    To output the body composition or health information based on the body composition.
    Information provision program.
  12. 　コンピュータに、
    　健康診断データを取得させ、
    　前記健康診断データから体組成を推定させ、
    　前記体組成又は前記体組成に基づく健康情報を出力させる、
    　情報提供プログラムを記憶した、コンピュータ読み取り可能な非一時的記憶媒体。     On the computer
    Get health check data
    The body composition is estimated from the health diagnosis data, and the body composition is estimated.
    To output the body composition or health information based on the body composition.
    A computer-readable, non-temporary storage medium that stores information-providing programs.
PCT/JP2020/013916 2019-03-28 2020-03-27 Information providing system, information providing program, and non-transitory computer-readable storage medium WO2020196812A1 (en)

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