JP2010026855A - Device for determining health condition - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a new evaluation method and an index, enabling appropriate evaluation of the health condition of a healthy person or a person falling under an illness reserve, and to provide a new method for processing many data collected by measurement or the like into significant information beneficial and useful for a user. <P>SOLUTION: The method for determining health condition includes: an acquisition means which obtains, as information for evaluating the health condition of an evaluation object person, an original index with a plurality of items including a measurement value measured by a measuring device and an input value entered by an operator; a health condition determination means which calculates, based on the value of the original index with a plurality of items, a health age that is an index showing the health condition of the evaluation object person in terms of age; and a display means which displays the health age. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a technique for supporting personal and active self-health management mainly for healthy persons or persons who fall under the disease reserve army.

  Recently, interest in health has been increasing, and the number of people who regularly manage blood pressure, weight, calorie intake, etc., and actively exercise such as jogging and walking is beginning to increase. Conventionally, various types of measuring devices such as blood pressure meters, blood glucose meters, weight scales, body composition meters, thermometers have been widely used as health-related devices for individuals and homes, and as devices for supporting exercise Pedometers and activity meters are provided, and these are used as one of the health management tools. However, the information that can be obtained with these devices is merely a numerical value (and a spot-like numerical value at the time of measurement), and it is up to the user how to use the numerical value for health management. Met.

Patent Documents 1 to 3 propose an apparatus that calculates and outputs an index such as a risk of developing a disease and a health degree from information such as blood pressure and blood glucose level. Although this type of index can be used as a reference for grasping the health condition, the conventional index and output form are not necessarily useful when considering support for individual health management.
JP 2006-163932 A JP 2005-319283 A JP 2004-246521 A

  In view of the above situation, the present inventors have conducted intensive studies on the ideal state of health management in individuals and homes and the elemental technologies necessary for that purpose.

  Most conventional systems are intended to provide numerical information (blood pressure level, blood glucose level, etc.) necessary for disease management and diagnosis. However, not only individuals with illness, but also healthy people and disease reserves (who have not developed symptoms but can show signs somewhere in the body) are users who are subject to health care in individuals and homes. Many are included. In the case of a healthy person or a person with a disease reserve, the measurement value obtained by the measuring device is in the normal range, and it is impossible to grasp his / her health condition (degree of disease risk) only with such a value. In addition, at a stage where it is not known what kind of illness is likely to develop, the user cannot specifically specify what numerical value should be noted and managed. In other words, if you use various measuring devices, you can measure various biological indicators such as blood pressure level, blood glucose level, body weight, body composition, body temperature, etc. at home, but how to manage the individual measured values for most users I don't know what to do with it. In the future, it is expected that various types of measuring devices will become widespread and an environment for daily measurement of many types of biological indices will be realized at home, but the number of raw data obtained by measurement etc. is enormous. Therefore, the more information there is, the more general users are concerned that it will become more difficult to obtain meaningful information, that is, information useful for their own health management.

  The information that a healthy person or a person with a disease reserve wants to know is not an individual measurement at a certain point in time, for example, whether he is healthy compared to a person or how healthy he is. Or an overall assessment of how serious it is if it is not healthy, and more specific actions such as what actions should be taken to maintain or improve the assessment It is considered to be a general guideline.

  “Continuity” is an indispensable viewpoint for supporting health management in individuals and households. In order to maintain a healthy state or to reduce the risk of developing a disease, habits such as daily measurement and evaluation of biological indices and regular exercise are the most effective, and long-term This is because it is possible to provide useful information as the measured values are accumulated. In order to realize such continuity, a mechanism to improve and maintain the user's motivation is necessary, and in order to realize that mechanism, it is easy for the user to understand convincing and reliable information. The key is whether it can be provided. Another way of looking at it is that personal and home measuring devices can be used to easily measure and accumulate biometric indicators on a regular and daily basis rather than being a spot measurement. That is why it exists. Therefore, if there is no feasibility and added value in terms of continuity, it can be said that health management in individuals and homes cannot be established.

  FIG. 13 shows a concept model of a health management system assumed by the present inventors. The system is broadly divided into three categories of functions: “CHECK”, “PLAN”, and “ACTION”, which collects information from living bodies (CHECK), and maintains and improves health based on that information. It comprehensively supports a cycle of making a plan (PLAN) and supporting the implementation of the plan (ACTION) (hereinafter referred to as CPA cycle). By providing such a CPA cycle, it can be expected that active self-health management will be continued in individuals and households.

  An object of the present application is to provide elemental technology related to the CHECK function in the concept model. Specifically, one of the objects of the present invention is to provide a novel evaluation method and index capable of appropriately evaluating the health status of a healthy person or a person corresponding to a disease reserve army. Another object of the present invention is to provide a novel technique for processing a large amount of data collected by measurement or the like into useful semantic information for the user. Another object of the present invention is to provide information that is highly convincing and reliable for the user.

  The solution adopted by the present inventors is roughly as follows. That is, a plurality of types of composite indices are calculated by modeling causal relationships between measured values of biological indices obtained from various measuring devices and evaluating the propagation of the degree of influence between the factors by the model. At this time, as a measurement value used for calculating the composite index, not only a definite value but also a value having uncertainty (for example, a value having a variation range, a range, a distribution, or the like) can be used. In addition to the biometric index, the life index can be considered as one of the factors, and in addition to the measurement value, the attribute index input by the user can also be considered as one of the factors. Then, a plurality of composite indexes are comprehensively evaluated to calculate a total health index and present it to the user.

Here, the “attribute index” is a scale for objectively identifying an individual attribute and its numerical value, for example, sex, age, height, medical history, and the like. The attribute index cannot basically be controlled by one's own intention. The “biological index” is a scale indicating the physiological state of the body and a numerical value thereof. For example, blood pressure values (maximum blood pressure value, minimum blood pressure value), blood glucose level (fasting blood glucose level, blood glucose level at any time), body weight, body fat percentage, serum total cholesterol, and the like correspond to the biometric indicators. The biological index is basically difficult to control by own will. The “life index” is a scale indicating daily activities (sleep, meal, exercise) and a numerical value thereof. For example, walking information (intermittent walking time in unit time, continuous walking time, number of continuous walking, regularity of walking pattern, etc.), sleep information (sleeping time, number of times to wake up, number of breathing, etc.), meal information (calorie intake, etc.) Other information (whether smoking habits, alcohol consumption frequency, etc.) correspond to lifestyle indicators. The life index can basically be controlled by one's own intention, and can be a control target for maintaining and improving health.

  “Compound index” refers to a specific disease based on the relationship between multiple indicators selected from biometric indicators, life indicators, and attribute indicators, and statistically obtained epidemiological information (such as mortality). A measure of the risk to or the state of a particular body organ or function and its numerical value. For example, a composite index indicating a risk for a specific disease includes a stroke risk, a cardiovascular risk, a coronary risk, and the like. Examples of the composite index indicating the state of a specific body organ or body function include blood vessel age, blood pressure age, physical strength age, strength age, and the like. These composite indexes are difficult to control directly, and are indirectly adjusted by control of life indexes.

  "Total health index" is a measure of the relative health status of individuals in a population based on the correspondence between multiple composite indicators and the actual age of a large population, and its numerical value . For example, the health age, health deviation value, and the like correspond to the comprehensive health index.

  Hereinafter, in order to distinguish various indicators, indicators obtained by measurement or input such as biometric indicators, life indicators, and attribute indicators are “original indicators”, and composite indicators obtained from multiple original indicators are “intermediate indicators”, multiple indicators The total health index obtained from the composite index is also referred to as “final index”.

  According to the above configuration, the present invention can evaluate a user's individual disease risk, health condition, and the like based on an original index obtained from the user himself / herself. Also, instead of directly deriving the final comprehensive health index directly from the original index, the raw data such as measured values and input values are once processed into an intermediate index (composite index), and then the final index (total health index) Derived. The advantage of outputting the intermediate index is that it is easier for the user to handle and grasp the information by coarsening the granularity of the information, but it is more convenient for the user than outputting the final index from the raw data in a black box. It is in the point that convincing and reliability can be given. In addition, by adopting an index related to a specific disease or a specific body organ or body function as an intermediate index, there is an advantage that it is easy for the user to understand and can provide useful semantic information. Furthermore, by handling measured values with uncertainty (which can be paraphrased as “reliability”), the reliability of the calculation results can be evaluated when calculating the composite index and the overall health index. The overall health index can be presented to the user along with its reliability. Such reliability information is useful as judgment information for the user when considering measures against disease risk and the like. In addition, clearly indicating the reliability of the output result of the apparatus leads to an increase in the sense of security and reliability of the output of the apparatus. And since this invention presents a user's health condition with a comprehensive health parameter | index, there exists an advantage that one's own health condition can be relatively grasped | ascertained by the comparison with a versus population. For example, when “health age” is indicated as the total health index, the user can intuitively understand how healthy he / she is by comparing the health age with his / her actual age.

  Specifically, the health condition determination apparatus according to the present invention employs the following configuration.

  The health condition determination apparatus according to the first aspect of the present invention includes a plurality of items including a measurement value measured by the measurement apparatus and an input value input by the operator as information for evaluating the health condition of the evaluation target person. An acquisition means for acquiring an original index, a health condition determination means for calculating a health age that is an index obtained by converting the health condition of the evaluation subject into an age based on the value of the original index of the plurality of items, and the health age Display means for displaying.

In this first aspect, the health condition determining means calculates the plurality of intermediate indices after calculating the number of intermediate indices having a number smaller than the number of items of the original indices from the values of the original indices of the plurality of items. It is preferable to calculate the healthy age as a final index from the value of. The intermediate index is preferably an index representing a risk for a specific disease or a state of a specific body organ or body function. Further, it is preferable that the health condition determination means calculates the intermediate index using an evaluation model generated based on epidemiological data. In addition, it is preferable to use a value including reliability information that is not determined as one definite numerical value as the value of the original index. In addition, the health condition determination means calculates a value including information representing reliability, which is not determined as one definite numerical value, as the value of the health age, and the display means calculates information representing the reliability. It is preferable to display the health age in an expression format including the above.

  The health condition determination apparatus according to the second aspect of the present invention includes a plurality of items including a measurement value measured by the measurement apparatus and an input value input by the operator as information for evaluating the health condition of the evaluation target person. From the acquisition means for acquiring the original index, and the value of the original index of the plurality of items, the value of the plurality of intermediate indices smaller than the number of items of the original index, and from the value of the plurality of intermediate indices, A health state determination unit that calculates a general health index indicating a relative health state of the evaluation target person in a predetermined population; and a display unit that displays the plurality of intermediate indexes and the total health index.

  In the second aspect, it is preferable that the intermediate index is an index representing a risk for a specific disease or a state of a specific body organ or body function. Further, it is preferable that the health condition determination means calculates the intermediate index using an evaluation model generated based on epidemiological data. In addition, it is preferable to use a value including reliability information that is not determined as one definite numerical value as the value of the original index. In addition, the health condition determination unit calculates a value including information representing reliability that is not determined as one definite numerical value as the value of the total health index, and the display unit is information representing the reliability. It is preferable to display the comprehensive health index in an expression format including

  The health condition determination apparatus according to the third aspect of the present invention includes a plurality of information including at least a systolic blood pressure value, presence / absence of diabetes, total cholesterol, sex, age, and smoking habits as information for evaluating the health condition of the evaluation subject. By substituting the value of the original index of the plurality of items into the acquisition means for acquiring the original index of the item, and the disease risk assessment models of stroke risk, coronary artery risk, and cardiovascular risk prepared in advance, Disease risk evaluation means for calculating values of stroke risk, coronary artery risk, and cardiovascular risk of the evaluation subject, and a calculation model of healthy age prepared in advance, calculated stroke risk, coronary artery risk, And the health year for calculating the health age, which is an index obtained by converting the health status of the assessment subject to age by substituting the value of the cardiovascular risk Comprising conversion means, calculated stroke risk, coronary risk, and display means for displaying cardiovascular risk, and the value of health age, a.

  In this third aspect, the disease risk assessment model is preferably a proportional hazard model generated based on epidemiological data. The health age calculation model is preferably a model represented by a linear sum of stroke risk, coronary artery risk, and cardiovascular risk, which is generated based on epidemiological data. Further, as the systolic blood pressure value and the total cholesterol value, it is preferable to use a value including information representing reliability expressed by a range, a range, or a distribution of variation. Further, the disease risk evaluation means calculates a value including reliability information represented by a variation range, range, or distribution as the stroke risk, coronary risk, and cardiovascular risk value. Preferably, the display means displays the values of the stroke risk, the coronary artery risk, and the cardiovascular risk in an expression format including information representing the reliability. Further, the health age conversion means calculates a value including information representing reliability expressed by a variation range, a range, or a distribution as the health age value, and the display means calculates the reliability. It is preferable to display the value of the healthy age in an expression format including information to be expressed.

The present invention may be regarded as a health condition determination apparatus having at least a part of the above means, or may be regarded as a health condition determination system including the health condition determination apparatus and one or more measurement devices. The present invention can also be understood as a health condition determination method including at least a part of the above processing, a program for causing a computer to execute the method, or a recording medium on which the program is recorded. Each of the above means and processes can be combined with each other as much as possible to constitute the present invention.

  ADVANTAGE OF THE INVENTION According to this invention, the novel evaluation method and parameter | index which can evaluate appropriately the health state of the healthy person or the person who corresponds to the sick reserve army can be provided. In addition, the present invention can provide a novel method for processing a large amount of data collected by measurement or the like into useful semantic information for the user. In addition, the present invention can provide information that is highly satisfactory and reliable for the user.

  Exemplary embodiments of the present invention will be described in detail below with reference to the drawings.

(Overview of health management system)
FIG. 1 shows the overall configuration of a health management system according to the present invention. This health care system is a system for supporting the CPA cycle described above. As a function related to “CHECK”, a “biological information measurement function” for measuring a daily health condition and a “risk estimation function” for estimating a future risk from information obtained by the measurement are provided. In addition, as a function related to “PLAN”, “risk factor extraction function” for extracting factors such as lifestyle habits that cause risk based on the results obtained by CHECK, setting improvement targets and proposals for improvement plans "Improvement plan support function" is provided. In addition, as a function related to “ACTION”, “improvement effect confirmation function” to support the implementation of life improvement activities (exercise) according to the improvement target / plan obtained in PLAN, and the plan / target are revised as necessary "Improvement plan correction function" is provided. These functions of CHECK, PLAN, and ACTION are organically linked, and the cycle is repeated, so that comprehensive health status determination based on multiple biological indices, future health risk evaluation, and the risk and daily life The relationship with activities in daily life can be visualized, and it can be expected to support the continuous implementation of active self-health management in individuals and homes.

  The overall health condition determination system described below is positioned as an elemental technology that bears a CHECK function (more specifically, a risk estimation function) in the configuration of the health management system.

(Comprehensive health condition judgment system)
FIG. 2 is a diagram showing a configuration example of a comprehensive health condition determination system (hereinafter also simply referred to as “system”) according to an embodiment of the present invention.

  This system is composed of a comprehensive health condition determination device 1 and one or more measurement devices 2 to 5. As the measuring device, a device for measuring a biological index (also referred to as biological information) from a human body, a device for measuring a life index such as a person's activity or lifestyle can be used. Examples of the biological index measuring device include a body weight and body composition meter that can measure body weight, body composition (body fat, muscle, etc.), BMI, blood glucose meter that measures blood glucose level, and blood pressure meter that measures blood pressure and pulse rate. There are thermometers that measure body temperature, heart rate meters that measure heart rate, and the like. Examples of the life index measuring device include an activity meter that measures physical activity and exercise intensity, a pedometer that measures the number of steps, a sleep sensor that measures the state of sleep, and a calorimeter that performs calorie calculation of meals. is there. In the system of the present embodiment shown in FIG. 2, a weight / body composition meter (2), a blood glucose meter (3), a sphygmomanometer (4), and an activity meter (5) are used.

  The comprehensive health condition determination device 1 and each of the measurement devices 2 to 5 can perform data communication by wire or wireless. The measurement values obtained by each measuring device are sent to the comprehensive health condition judging device and aggregated. If the comprehensive health condition determination device and the measurement device are always connected, data transmission from the measurement device to the total health condition determination device may be performed every time measurement is performed or at a predetermined timing. . As a result, data synchronization between the two devices is achieved. On the other hand, when the general health condition determination device and the measurement device are not always connected, the measurement device or the general health condition determination device monitors the connection and automatically synchronizes data when a connection is detected. Good. Of course, the measurement value may be transferred to the health condition determination apparatus by the user's own operation.

(Hardware configuration of comprehensive health condition judging device)
FIG. 3 is a block diagram schematically showing a hardware configuration of the comprehensive health condition determination apparatus 1.

  As shown in FIG. 3, the overall health condition determination apparatus 1 includes a CPU (Central Processing Unit) 101, a button 102 and a user I / F (interface) control unit 103, a communication connector 104, a device communication control unit 105, and an RTC ( Real time clock) 106 and RTC control unit 107, panel 108 and display control unit 109, sound source device 110 and sound control unit 111, ROM (read only memory) 112 / RAM (random access memory) 113 and storage medium control unit 114, power supply 115 and a power supply control unit 116. This device may be configured as a dedicated device, or may be configured by installing necessary hardware for a general-purpose device such as a personal computer (for example, a communication connector with a measuring device) and a necessary program.

  The button 102 is an input unit for inputting information and instructions to the overall health condition determination apparatus 1. Information and instructions input by operating the button 102 are notified to the CPU 101 via the user I / F control unit 103.

  The communication connector 104 and the device communication control unit 105 are communication means for realizing data communication with the various measuring devices 2 to 5. The communication method may be wired communication such as USB or IEEE 1394, or wireless communication such as Bluetooth, ZigBee, IrDA, or wireless LAN.

  The RTC 106 and the RTC control unit 107 are portions that provide a time measuring function.

  The panel 108 and the display control unit 109 are display means for displaying various indexes described later. As the panel 108, for example, a liquid crystal display or an organic EL display can be suitably used.

  The sound source device 110 and the sound control unit 111 are output means for outputting an alert, a voice guide, and the like.

The ROM 112 stores a program that provides a function as the comprehensive health condition determination device 1, various set values, measurement values acquired from the measurement devices 2 to 5, information input from the input unit, various indexes described later, and the like. Storage medium. EEPROM (Erasable Programmable ROM
) And a rewritable memory. The RAM 113 is a storage medium used as a work memory when executing a program. Access to the ROM 112 and the RAM 113 is controlled by the storage medium control unit 114. Note that a storage medium such as a hard disk may be provided in addition to the EEPROM or instead of the EEPROM.

The power supply 115 and the power supply control unit 116 have a function of supplying power to the comprehensive health condition determination apparatus 1. The power source 115 may be a battery or an AC power source.

(Functional configuration of the comprehensive health condition judging device)
FIG. 4 is a functional configuration diagram schematically showing the functions of the comprehensive health condition determination apparatus 1.

  As shown in FIG. 4, the comprehensive health condition determination apparatus 1 includes a function transition control function 130, an initial setting function 140, a lifestyle setting function 150, a biological index collection function 160, and a total health condition determination function 170 as its functions. . The initial setting function 140 includes an attribute index setting function 141 and a date / time setting function 142. The biometric index collection function 160 includes a measurement value communication function 161, a measurement value reliability evaluation function 162, and a measurement value recording function 163. The overall health state determination function 170 includes a health state extraction function 171 and a health state display function 174, the health state extraction function 171 includes a disease risk evaluation function 172 and a health age conversion function 173, and the health state display function 174 includes a health state display function 174. An age display function 175 and a health profile display function 176 are provided. These functions are realized by the CPU 101 reading and executing a program stored in the ROM 112.

(Function transition control function)
The function transition control function 130 is an initial setting function 140, a lifestyle setting function 150, a biometric index collection function 160, a general health according to an event (interruption) generated by a user operation, communication with a measurement device, a program being executed, or the like. This is a function for overall control of switching of the state determination function 170.

(Initial setting function)
The attribute index setting function 141 is a function for allowing a user to input an attribute index (also referred to as attribute information). As an attribute index, for example, age, sex, height, medical history, and the like are assumed. The attribute index setting function 141 displays an attribute index input screen such as “age? __” on the panel, and prompts the user to input the attribute index. When an attribute index is input by operating an input means such as a button, the information is recorded in the user information DB in the ROM 112.

  The date / time setting function 142 is a function for setting the current date and time (local time) in the apparatus. The date / time setting function displays a setting screen such as “year / month / day? _____” on the panel 108 and prompts the user to set the current date and time. When the current date and time is set by operating the input means such as the button 102, the value is written in the RTC 106. Thereafter, the RTC 106 measures the current date and time.

(Lifestyle setting function)
The lifestyle setting function 150 is a function for allowing a user to input a lifestyle index (also referred to as lifestyle). As a life index, for example, the presence or absence of a smoking habit, sleep time, and the like are assumed. The lifestyle setting function 150 displays an input screen such as “smoking habit? Yes / no” on the panel 108 and prompts the user to input. When the life index is input by operating the input means such as the button 102, the information is recorded in the user information DB in the ROM 112.

  The setting of the attribute index, the current date and time, and the life index as described above is performed when the comprehensive health condition determination apparatus 1 is started up in principle. That is, when the comprehensive health state determination device 1 is activated, the function transition control function 130 checks whether an attribute index or the like is set in the ROM 112, and if not set, the initial setting function 140 or the like is automatically called. . Even when the setting has been made, the setting values of the attribute index, the current date and time, and the life index can be changed by the user's changing operation.

(Biometric index collection function)
The measured value communication function 161 is a function for acquiring measured values from various measuring devices via the communication connector 104. The acquired measurement value is stored in the ROM 112 by the measurement value recording function 163. At this time, the measurement value is recorded together with a time stamp indicating the measurement date / time or the acquisition date / time of the measurement value.

  The measured value reliability evaluation function 162 is a function for evaluating the reliability of the measured value. The reliability of the measured value is information (a scale) that represents the degree of variation expected in the measured value. It can be rephrased as uncertainty (or certainty) of the measured value. The reliability of the measurement value is affected by the accuracy of the measurement device, measurement environment, measurement mode, and other disturbances. For example, even with the same sphygmomanometer, the accuracy may be different between the wrist type and the upper arm type, and the accuracy may be different between the high-end machine and the popular machine. Even if the same device is used, there is a possibility that the measured value may vary due to the influence of the place of measurement or the outside temperature. The measurement mode corresponds to, for example, a prediction mode and an actual measurement mode of an electronic thermometer. The prediction mode is less accurate than the measurement mode. In addition, the measurement values may vary depending on the measurement posture and other disturbance factors. If the measurement value reliability evaluation function 162 can acquire the accuracy of the measurement value from the measurement device, it can be used as the reliability of the measurement value. In addition, since the measurement value varies depending on the condition of the person to be measured (physical condition, fatigue, sleep, meal, etc.), the measurement value reliability evaluation function 162 evaluates the distribution and variation of the measurement value in the past predetermined period, It can also be used as the reliability of the measured value.

  There are various methods for expressing the information representing the reliability of the measured value, and any of them may be adopted. For example, reliability may be expressed by a range of variation such as “maximum blood pressure value: 135 ± 6”, or reliability may be expressed by a range such as “maximum blood pressure value: 128 to 139”. . Further, the distribution and variation of the measured value may be expressed by the average value and the variance. Alternatively, the range of variation and the boundary of the range can be made ambiguous by a fuzzy set such as “maximum blood pressure value: 135 ± about 6” or “maximum blood pressure value: about 128 to about 139”. Hereinafter, the expression “the value has a width” is used in the sense that “the value includes information indicating reliability and is not determined to one definite numerical value”.

  The biometric index collection function 160 described above collects measurement values from various measurement devices as needed, and accumulates them in the user information DB in the ROM 112 together with information indicating the reliability of the measurement values as necessary.

  Measurement values measured by a life index measuring device such as an activity meter, a pedometer, or a sleep sensor are also collected by the biometric index collection function 160 in the same manner as the biometric index and stored in the user information DB in the ROM 112. Shall be.

(General health condition judgment function: health condition extraction function 171)
((Disease risk assessment function))
The disease risk evaluation function 172 uses a biometric index, a life index, and an attribute index accumulated in the user information DB (hereinafter, information accumulated in the user information DB is referred to as an original index) to be a disease that is a composite index. This is a function to estimate the risk. The disease risk evaluation function 172 calculates a disease risk by using a risk evaluation model that models the causal relationship of the original index and evaluating the propagation of the degree of influence between the factors by the model. This will be described in detail below.

FIG. 5 shows an example of the causal relationship between the biological index, life index, attribute index, and disease risk accumulated in the user information DB. In an actual apparatus, it is possible to construct a more complicated causal relationship using ten to several tens of factors. In this embodiment, three disease risks of stroke risk, coronary artery risk, and cardiovascular risk are used as a composite index. However, risks related to other diseases may be used, such as blood vessel age and strength age. You may use the parameter | index regarding a body organ or a body function. Further, the number of composite indexes is not limited to three, but may be two or four or more. The causal relationship between the original index and the composite index may be designed by a person based on epidemiological knowledge, or may be automatically generated using a known causal structure estimation method. From FIG. 5, as factors of “stroke risk”, “gender” and “age” of the attribute index, “presence / absence of smoking habit” of life index, “maximum blood pressure value”, “presence / absence of diabetes” and It can be seen that “total cholesterol” can have an effect. In addition, factors such as “gender”, “age”, “presence of smoking habits”, “high blood pressure”, “presence of diabetes”, “total cholesterol”, etc. for “coronary risk” and “cardiovascular risk” Can be seen to have an effect.

The risk assessment model models the strength of the influence of each factor. FIG. 6 shows an example of a risk assessment model for stroke risk. In this embodiment, a proportional hazard model is adopted as the risk evaluation model. That is, as shown in the following equation, the stroke risk _RCE at time t is represented by the product of R (t), which is a function of time, and an exponential function of the linear sum of each influencing factor.

Stroke risk model:
R _CE = R (t) × exp (α ₁ A + α ₂ G + α ₃ BP _S + α ₄ DM + α ₅ TC + ε)

  Here, R (t) is a statistical mortality rate after time t due to stroke, and is called a reference hazard. For example, if the initial population is 100, all 100 people are alive at the time t = 0, so R (0) = 0%. If t = t1, 9 people died of stroke and 10 people could not be confirmed due to death or migration due to other causes, the population was considered to be 90 (= 100-10) R (t1) = (9/90) × 100% = 10%. Thus, by excluding the number of deaths due to causes other than stroke (including those whose survival cannot be confirmed) from the population over time, a pure mortality rate due to stroke can be expressed. In this case, the mortality rate is selected as the reference hazard R (t). Of course, the occurrence rate of events other than death may be selected as the reference hazard R (t). For example, the incidence of events that interfere with daily life such as hospitalization, disability, and severe symptoms may be considered.

A age, G is gender, BP _S is the systolic blood pressure value, DM is the presence or absence of diabetes, TC is the total cholesterol. α _n is a parameter (weight) indicating the influence intensity of each factor on R (t). Ε is a parameter indicating the influence on R (t) by factors other than A, G, BP _S , DM, and TC. As a method for generating the parameters α _n and ε, an Exact method (Monte Carlo exact probability test), Breslow method, Efron method (bootstrap), a discrete method, or the like can be used.

Here, when the value of the factor input to the risk evaluation model is a definite value such as “maximum blood pressure value: 135”, the disease risk is also determined as one value. On the other hand, when the value of the factor has a range, the disease risk is not determined to be one value, but has a range similar to the factor. If the factor value has a width, risk calculation may be performed by selecting a plurality of representative values from the width and substituting each representative value into the risk evaluation model. As representative values, for example, values of −Nσ and + Nσ in the distribution of factor values can be used (N is a positive integer, and σ is a standard deviation). By using Nσ which is a statistic, there is an advantage that information such as variation and probability of factors can be inherited to the risk distribution. Alternatively, the minimum value and the maximum value of the factor can be used as the representative value. When evaluating variations of industrial products, the minimum and maximum values in the value distribution are likely to be noise and are generally excluded as outliers. However, in the case of information measured from a living body, such outliers are more likely to be important information as indicating signs of physical abnormality. Therefore, in this system, it can be said that the latter method of performing risk calculation using the minimum value and the maximum value of the factor is preferable. Thus, when the value of the factor includes reliability information, it is possible to provide reliability information for the disease risk.

In the present embodiment, epidemiological data, which is a result of large-scale epidemiological research, is used as basic data for calculating the reference hazard R (t) and parameters α _n and ε of the risk evaluation model. Representative epidemiological studies include NIPPON DATA 80, Framingham study, Osako study, Hisayama study, Suita study, etc. Based on such epidemiological data, it is possible to achieve high accuracy in the risk assessment model by obtaining the influence intensity between factors and the mortality rate at each time point. In addition, by using the epidemiological data as evidence, it can be expected that the satisfaction and reliability of the user with respect to the evaluation index output by the system can be improved and the motivation for health management can be improved.

((Health age conversion function))
The health age conversion function 173 is a function that comprehensively evaluates a plurality of disease risks obtained by the disease risk evaluation function 172, and calculates “health age” that is an index obtained by converting the user's health state into age.

In the present embodiment, as shown in the following formula, the health age _AH is calculated using a linear sum model of the stroke risk R _CE , the coronary artery risk R _AC , and the cardiovascular risk R _CV . β _n is a parameter indicating the intensity of influence of each disease risk on the healthy age. Further, ε is a parameter indicating the influence on health age by factors other than R _CE , R _AC , and R _CV . These parameters β _n and ε can be calculated by a method such as regression analysis using the epidemiological data described above. If the value of disease risk has a reliability of the information, such as range and distribution, also have a width value of health age A _H.

Health age model:
A _H = β ₁ R _CE + β ₂ R _AC + β ₃ R _CV + ε

FIG. 7A is a schematic diagram for explaining the meaning of the health age model. However, for simplicity of explanation, the cardiovascular risk R _CV is ignored as a fixed value. By substituting “50” for the left side (A _H ) of the health age model formula, one age line corresponding to the actual age of 50 years can be drawn on the stroke risk R _CE -coronary artery risk _RAC plane. it can. Similarly, when “60”, “70”,... Are substituted on the left side of the model formula and an age line corresponding to each age is drawn, the stroke risk R _CE -the coronary artery risk _RAC surface Contour lines representing the height can be drawn. This contour line should generally match the distribution of the sample data (epidemiological data) used to generate the model parameters. When a stroke risk R1 and a coronary artery risk R2 are given as user values, the health age A12 is calculated by the above model formula. In other words, this is substantially equivalent to the process of identifying a person who has the same risk as the user from the sample data population and regarding the age of the person as the user's health age. As shown in FIG. 7B, when the disease risk value has a range, the health age is calculated using a representative value (± Nσ, minimum value / maximum value, etc.) of the disease risk. This process is substantially equivalent to the process of identifying a set showing risks similar to the user from the sample data population and regarding the age distribution of the people making up the set as the user's health age. is there.

(General health condition judgment function: health condition display function)
The health state display function 174 is a function for displaying on the panel 108 various indexes obtained by the health state extraction function 171 described above. Hereinafter, specific examples of screen display by the health state display function 174 will be described with reference to FIGS.

  FIG. 8 is an example of a screen display related to the health age display function 175. For example, when the user instructs display of the healthy age by a button operation, the screen in FIG. 8 is first displayed on the panel. On this screen, the health age, which is a comprehensive evaluation index of the user's health status, is displayed, and multiple disease risks (stroke risk, coronary artery risk, cardiovascular risk) that are the basis for calculating the health age are also displayed. Is displayed.

  The health age is displayed as a numerical value, and the value range of the health age changes according to the reliability of the disease risk as described above. That is, the higher the reliability, the narrower the health age value range, and the lower the reliability, the wider the value range. In this way, if the user's health status is presented by an index called health age, the user can compare the health age with his / her own real age, so he can intuitively understand how well his / her health status is can do. In addition, by displaying the health age in a numerical range with a range corresponding to the reliability instead of a definite numerical value, the reliability (accuracy) of the health age can be informed to the user. This leads to increased security and confidence in output. It should be noted that the method of expressing the reliability of health age is not limited to the method expressed in a value range such as “35 to 38 years old”. For example, a range of variation such as “37 years ± 2 years” or “37 years ± 3%” may be displayed. Further, by using a fuzzy number expression such as “about 35 to about 38 years old” or “37 years ± about 2 years old”, it is possible to eliminate errors in strict numerical expressions.

  On the other hand, disease risk is represented by a radar chart. Each axis of this radar chart is standardized by the average disease risk value of people of the same age and same gender as the user, and a graph of the average disease risk is also displayed as a comparison target (the dotted positive line) Triangle). By looking at such a radar chart, users can easily see how far their average disease risk deviates from the average and what risk factors have the greatest impact on their health age. I can grasp it. Here, as shown in FIG. 8, it is preferable to highlight the risk factor that has the greatest influence on the healthy age because the user's interest can be directed to the risk factor. If the disease risk value has a width corresponding to the reliability, the line width of the graph of the radar chart may be changed according to the reliability. Thereby, the reliability (accuracy) of the disease risk can be informed to the user in an intuitive manner. At this time, the fuzzy expression described above can be applied to the graph display by blurring the boundary of the graph or adding gradation of light and shade.

  FIG. 9 shows another display example of the disease risk. In this display example, a line indicating the user's actual age (see the broken line) and a disease risk value (see the star mark) are plotted on a graph in which the horizontal axis indicates the age and the vertical axis indicates the disease risk. The background of the graph is divided into a plurality of areas such as health / somewhat caution / caution / danger. The threshold for determining the boundary of each area is not constant and changes according to the age (basically, the threshold increases as the age increases). This is because, even if the risk value is the same, the risk level is 50% at the age of 20 and the risk level is 50% at the age of 70, and the severity is completely different. In other words, it can be said that the boundary between the above areas shows a risk evaluation standard suitable for each age. The threshold value of this boundary is statistically obtained from the epidemiological data described above. The user can confirm the severity of the disease risk according to his / her age by checking which area his / her disease risk value belongs to, and where the disease risk value is plotted in the area. Can be easily understood.

  When the risk factor of the radar chart is selected (clicked) on the screen of FIG. 8, the screen display is switched to that of FIG. FIG. 10 is an example of a screen display regarding the health profile display function, and is a screen for displaying detailed information regarding a certain disease risk (FIG. 10 is an example of cardiovascular risk).

In the screen of FIG. 10, the value of the cardiovascular risk is displayed as a bar on the left side. Also in this case, it is good to display with a width according to the reliability of the risk. For example, when the cardiovascular risk is 5% to 8%, the portion corresponding to 5% to 8% is displayed in a different color in the cardiovascular risk bar (indicating 2% to 10%) do it. Also in this case, fuzzy expression can be performed by blurring the boundary of the portion corresponding to 5% to 8% or displaying the gradation.

  On the right side of the screen, the value of an index (factor) that affects cardiovascular risk is displayed in a radar chart. Each axis of the radar chart is standardized by the average index values of people of the same age and sex as the user. A graph of the average value of each index is also displayed as a comparison target (refer to the dashed rectangle). By looking at such a radar chart, the user can easily understand which indicators have an effect on the disease risk, in other words, which indicators should be improved for themselves. it can. In the example of FIG. 10, systolic blood pressure, blood glucose level, total cholesterol, and smoking habits are listed as indices, but any index may be used as long as it is an index that affects the disease risk. When there are a large number of indicators, those that can be improved by the user's own efforts (for example, smoking habits, weight, blood glucose level, etc.) are selected preferentially, and indicators that the user cannot control (for example, gender, height, etc.) ) Should be excluded from the display target. As in the case of FIG. 8, when the index value has a width corresponding to the reliability, fuzzy expression is performed by changing the line width of the graph of the radar chart or further blurring the boundary. Good.

  When the health age portion is selected on the screen of FIG. 8, the screen display is switched to that of FIG. FIG. 11 is an example of a screen display regarding the health profile display function, in which the accumulation of each disease risk is displayed in a radar chart. Each axis of this radar chart corresponds to an index (influencing factor) on the screen of FIG. By viewing such a display, the user can see which index has a large effect on which disease risk, in other words, which disease risk is effective when a certain index is improved. Comprehensive understanding. Since this radar chart shows the cumulative disease risk, it can be said that the outermost shell represents the healthy age.

  When any index portion is selected on the screen of FIG. 10 or FIG. 11, the screen display is switched to the screen of FIG. FIG. 12 is an example of a screen display related to the health profile display function, and is a screen for displaying detailed information related to one original index (FIG. 12 is an example of systolic blood pressure).

  On the left side of the screen, a temporal transition of the value of the index (high blood pressure) selected by the user is displayed in a graph. Specifically, the data for one week each of the previous month, the previous week, and the current week are read from the user information DB, and the statistics (average, variation, etc.) of the measured values for each week are displayed. Also, on the right side of the screen, information on life indicators that affect the improvement of the indicator (high blood pressure) is displayed in a radar chart. As shown in FIG. 5, factors such as “intermittent walking time”, “continuous walking time”, “number of continuous walkings”, and “walking pattern variation” of the life index can affect the systolic blood pressure value. These indicators are information obtained from activity meters. Here, the continuous walking time is a cumulative value per day of continuous walking over a predetermined time, and the intermittent walking time is obtained by subtracting the continuous walking time from the total walking time of one day. The number of continuous walks is the number of times of continuous walks per day. Based on such information, a radar chart as shown in FIG. 12 is displayed. The radar chart also displays the average value for each month, week, and week. As a result, it is possible to easily grasp how much daily exercise is effective in improving the blood pressure value, and it can be expected to maintain motivation to continue health management.

  The configuration of the above-described embodiment is merely an example of the present invention. The scope of the present invention is not limited to the above embodiment, and various modifications can be made within the scope of the technical idea.

FIG. 1 is a diagram showing an overall configuration of a health management system according to the present invention. FIG. 2 is a diagram illustrating a configuration example of a comprehensive health condition determination system according to an embodiment of the present invention. FIG. 3 is a block diagram schematically showing a hardware configuration of the comprehensive health condition determination apparatus. FIG. 4 is a functional configuration diagram schematically illustrating the functions of the comprehensive health condition determination device. FIG. 5 is a diagram illustrating an example of a causal relationship between a biometric index, a life index, an attribute index, and a disease risk accumulated in the user information DB. FIG. 6 is a diagram illustrating an example of a risk assessment model for stroke risk. 7A and 7B are schematic diagrams for explaining the meaning of the health age model. FIG. 8 is a diagram illustrating an example of a screen display related to the health age display function. FIG. 9 is a diagram illustrating another display example of the disease risk. FIG. 10 is a diagram illustrating an example of a screen for displaying detailed information regarding a certain disease risk. FIG. 11 is a diagram illustrating an example of a screen that displays the accumulation of each disease risk in a radar chart. FIG. 12 is a diagram illustrating an example of a screen for displaying detailed information regarding one original index. FIG. 13 is a diagram illustrating a concept model of a health management system.

Explanation of symbols

1 Total health condition judging device 2-5 Measuring device 101 CPU
102 button 103 user I / F control unit 104 communication connector 105 device communication control unit 106 RTC
107 RTC Control Unit 108 Panel 109 Display Control Unit 110 Sound Source Device 111 Sound Control Unit 112 ROM
113 RAM
114 Storage Medium Control Unit 115 Power Supply 116 Power Supply Control Unit 130 Function Transition Control Function 140 Initial Setting Function 141 Attribute Index Setting Function 142 Date / Time Setting Function 150 Lifestyle Setting Function 160 Biometric Index Collection Function 161 Measurement Value Communication Function 162 Measurement Value Reliability Sex evaluation function 163 Measurement value recording function 170 Total health condition judgment function 171 Health condition extraction function 172 Disease risk evaluation function 173 Health age conversion function 174 Health condition display function 175 Health age display function 176 Health profile display function

Claims (13)

An acquisition means for acquiring a plurality of original indices including a measurement value measured by the measurement device and an input value input by the operator as information for evaluating the health condition of the evaluation target person,
Based on the value of the original index of the plurality of items, health state determination means for calculating a health age that is an index obtained by converting the health state of the evaluation subject into an age;
Display means for displaying the health age;
A health condition determination apparatus comprising:   The health condition judging means calculates a plurality of intermediate index values less than the number of items of the original index from the values of the original index of the plurality of items, and then calculates the final index from the values of the plurality of intermediate indices. The health state determination apparatus according to claim 1, wherein the health age is calculated.   The health condition determination apparatus according to claim 2, wherein the intermediate index is an index representing a risk for a specific disease or a state of a specific body organ or body function.   The health condition determination apparatus according to claim 3, wherein the health condition determination means calculates the intermediate index using an evaluation model generated based on epidemiological data.   The health condition determination device according to any one of claims 1 to 4, wherein a value including information representing reliability that is not determined as one definite numerical value is used as the value of the original index. The health condition determination means calculates a value including information representing reliability that is not determined as one definite numerical value as the value of the health age,
The health condition determination apparatus according to claim 1, wherein the display unit displays the health age in an expression format including information representing the reliability. An acquisition means for acquiring a plurality of original indices including a measurement value measured by the measurement device and an input value input by the operator as information for evaluating the health condition of the evaluation target person,
A plurality of intermediate index values smaller than the number of items of the original index are calculated from the original index values of the plurality of items, and the evaluation target person in a predetermined population is calculated from the values of the plurality of intermediate indices. Health condition determination means for calculating a comprehensive health index indicating the relative health condition of
Display means for displaying the plurality of intermediate indices and the overall health index;
A health condition determination apparatus comprising: As an information for evaluating the health condition of the evaluation subject, an acquisition means for acquiring a plurality of original indicators including at least a maximum blood pressure value, presence / absence of diabetes, total cholesterol, sex, age, and smoking habits;
By substituting the values of the original indicators of the plurality of items into the disease risk assessment models for stroke risk, coronary artery risk, and cardiovascular risk that are prepared in advance, the assessment subject's stroke risk, coronary artery risk , And disease risk assessment means for calculating cardiovascular risk values;
This is an index in which the health status of the assessment subject is converted to age by substituting the calculated values of stroke risk, coronary artery risk, and cardiovascular risk into a health age calculation model prepared in advance. Health age conversion means for calculating health age;
Display means for displaying the calculated stroke risk, coronary risk, cardiovascular risk, and health age value;
A health condition determination apparatus comprising: The health condition determination device according to claim 8, wherein the disease risk evaluation model is a proportional hazard model generated based on epidemiological data.   10. The health age calculation model is a model represented by a linear sum of stroke risk, coronary artery risk, and cardiovascular risk, which is generated based on epidemiological data. The health condition determination apparatus described.   The value including information representing reliability expressed by a range, a range, or a distribution of variation is used as the systolic blood pressure value and the total cholesterol value, according to any one of claims 8 to 10. Health condition judgment device. The disease risk evaluation means calculates a value including information representing reliability expressed by a range, a range, or a distribution of variation as a value of the stroke risk, coronary artery risk, and cardiovascular risk,
The said display means displays the value of the said stroke risk, the coronary-system system risk, and the cardiovascular system risk in the expression format containing the information showing the said reliability. Health condition judgment device. The health age conversion means calculates a value including information representing reliability expressed as a range, range, or distribution of variation as the value of the health age,
The health state determination apparatus according to any one of claims 8 to 12, wherein the display means displays the value of the health age in an expression format including information representing the reliability.

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