JP5135197B2 - Biometric index management device - Google Patents

Description

  The present invention relates to a technique for supporting personal and active self-health management mainly for healthy persons or persons corresponding to a disease preparatory group.

  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.

  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 people who are healthy or who are in the disease preparatory group (they have not developed symptoms but can show signs somewhere in their bodies) Many are included. In the case of a healthy person or a person in the disease preparatory group, the measurement value obtained by the measuring device is in the normal range, and therefore it is not possible to grasp his / her health condition (disease risk level) 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 healthy people and people in the preparatory group want to know is not individual measurements at a certain point in time, for example, whether they are healthy compared to people or how well they are healthy. 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.

  In order to more accurately evaluate the health condition, it is naturally desirable to measure as many different types of biological indices as possible. However, it is difficult to constantly monitor the value of the biometric index in daily life, and it is not realistic to force the user to perform high-frequency measurements such as once every 30 minutes. However, there is a possibility that the reliability of the evaluation result may be reduced only by the measurement values voluntarily measured by the user, or changes in health status and signs of illness may not be detected in a timely manner.

As prior art relating to measurement and collection of biological information, those listed in Patent Documents 1 and 2 are known. Patent Document 1 discloses a system that calculates a user's degree of compliance with measurement conditions and prompts the user to remeasure when the degree of compliance is low. However, in this method, the user does not always perform remeasurement, and there is a problem that data loss occurs if remeasurement is not performed. Further, Patent Document 2 proposes a system that automatically measures and collects biological information from a user on the phone without mounting the biological measuring device on the telephone without causing the user to be conscious or burdened. ing. However, in this method, since measurement can be performed only at the timing when the user is making a call, biological information is collected at timings necessary for evaluating the health condition (for example, at the time of waking up, after meals, before going to bed). There is a problem that it is not suitable for daily health management systems.
JP-A-2005-305134 JP 2003-284695 A

  FIG. 10 shows a concept model of the 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 technique for measuring and collecting biological indices necessary for evaluation of a health condition in a timely manner. Another object of the present invention is to provide a technique for enabling evaluation of a health condition even when a biometric index is not measured and collected and data loss occurs. Another object of the present invention is to provide a technique for complementing a data missing portion of a biometric index with sufficient validity.

  In order to achieve the above object, the present invention employs the following means and processes.

The biometric index management device according to the present invention includes a measurement data acquisition unit that acquires measurement data measured by a measurement device according to a predetermined measurement timing from the measurement device, with respect to a biometric index used for health condition evaluation, Storage means for accumulating a plurality of measurement data acquired during a day or a predetermined unit period as a data set, and when measurement data of the biometric index cannot be acquired at a certain measurement timing, Remeasurement request means for requesting remeasurement, and in the case where a loss of measurement data occurs in the biometric data set because remeasurement was not performed, the past data set stored in the storage means is used. Complementing means for complementing the missing part of the data set including the missing.

  Here, the “biological index” is a scale indicating the physiological state of the body and its numerical value. 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, BMI, and the like correspond to the biometric indicators. One or more biometric indicators are used for the evaluation of the health condition. Assume that the measurement timing is set in advance for each biometric index, and the user (evaluation target) is required to measure the biometric index according to the measurement timing. A plurality of measurement timings are set in one day, and it is preferable that each measurement timing is set to a timing at which changes in biomarkers and changes in health conditions can be appropriately monitored.

  According to the configuration of the present invention, measurement data measured at the same measurement timing is accumulated every day. The measurement data collected in this way can be used for, for example, fixed point observation of biological indices, early detection of abnormalities, comprehensive evaluation of health conditions, and the like. In the present invention, when the measurement data cannot be acquired, the user is requested to perform re-measurement. Therefore, the measurement can be prevented from being forgotten, and the user is conscious of measuring by himself / herself. There is an advantage that can be encouraged.

  If the measurement data is still not obtained even when re-measurement is requested, the missing portion of the measurement data is supplemented using the past data set. Therefore, even if the measurement of the biological index is not performed for some reason, it is possible to evaluate the health condition using the complementary data. In addition, since the data missing portion is complemented using the data set accumulated in the past, appropriate complement data can be obtained.

  Even if it is appropriate supplementary data, it cannot be denied that accuracy is inferior to actual measurement data. Therefore, as in the present invention, it is preferable that a re-measurement request is first made and a missing portion is complemented as a preliminary means. As a result, it is possible to realize a mechanism in which data supplementation is performed only when a loss occurs unavoidably while giving priority to acquisition of measurement data.

  The complementing means pays attention to measurement data other than the missing part, and evaluates the similarity between each of the data sets including the defect and a plurality of past data sets accumulated in the storage means, It is preferable to select a past data set having the highest degree of similarity as a similar data set, and use the selected similar data set to complement a missing portion of the data set including the missing.

  This is a method of selecting a similar data set to be used for complementation by evaluating the similarity of the data set with respect to a biometric index in which a defect has occurred. This method is preferably applicable when only a part of the data in the data set is missing.

For a plurality of biomarkers, when the measurement data is acquired by the measurement data acquisition unit and the data set is stored in the storage unit, a similar data set can be selected as follows. That is, when a measurement data deficiency occurs in a data set of a first biometric index among the biometric indices of the plurality of items, the complementing means acquires on the same day or the same unit period as the data set including the deficiency By evaluating the degree of similarity between the data set of the other biometric index other than the first biometric index and the plurality of past data sets of the other biometric index stored in the storage unit A past data set of the other biometric index having the highest similarity is selected, and the past of the first biometric index acquired on the same day or in the same unit period as the past data set of the selected other biometric index Can be selected as a similar data set, and the selected similar data set can be used to supplement the missing part of the data set including the missing data. That.

  This is a method of selecting a similar data set to be used for complementation by evaluating the similarity of a data set with respect to a biometric index (other biometric index) other than the biometric index (first biometric index) in which a defect has occurred. This method is preferably applicable when most or all of the data in the data set is missing.

  It is preferable that the complementing means extracts measurement data measured at the same measurement timing as the missing portion from the similar data set, and uses the extracted measurement data as data of the missing portion. This is preferably applicable when only a part of the data in the data set is missing.

  The complementing unit preferably replaces the data set including the deficiency with the similar data set. This method is preferably applicable when most or all of the data in the data set is missing.

  The present invention may be understood as a biometric index management device having at least a part of the above means, or as a system including the biometric index management device and one or more measurement devices. The present invention can also be understood as a biometric index management 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 technique for measuring and collecting the biological index required for evaluation of a health condition in a timely manner can be provided. Further, according to the present invention, even when measurement and collection of a biometric index are not performed and a data loss occurs, the data loss location of the biometric index can be complemented with sufficient validity, and the health condition using the complemented data Can be evaluated.

  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 “biometric index measurement function” for measuring a daily health state 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 the CHECK function (more specifically, the biometric index measurement 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 includes a comprehensive health condition determination device (biological index management 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 data obtained by each measuring device is sent to and aggregated by the comprehensive health condition judging device. Basically, the total health condition determination device and each measurement device are always connected, and data is transmitted from the measurement device to the total health status determination device every time measurement is performed or at a predetermined timing. . As a result, data synchronization between the two devices is achieved. If the total health condition determination device and the measurement device are not always connected, the measurement device or the total health status determination device monitors the connection and automatically synchronizes data when a connection is detected. Good. Of course, the measurement data 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 and IEEE1394, or wireless communication such as Bluetooth (registered trademark), ZigBee (registered trademark), IrDA, and 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 measurement data of various indices, measurement guides, re-measurement requests, and the like, which will be 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 data acquired from each measurement device 2 to 5, information input from the input unit, various indexes described later, and the like. Storage medium. It is composed of a rewritable memory such as an EEPROM (Electrically Erasable Programmable ROM). 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 illustrating functions of the overall health condition determination apparatus 1 (particularly, functions as a biological index management apparatus).

  As shown in FIG. 4, the comprehensive health condition determination apparatus 1 includes, as its functions, a biological index collection unit (measurement data acquisition unit) 10, a user information DB (storage unit) 11, a measurement guide output unit 12, and a remeasurement request unit. (Re-measurement requesting means) 13 and data complementing part (complementing means) 14 are provided. These functions are realized by the CPU 101 reading and executing a program stored in the ROM 112. The user information DB 11 is constructed in the ROM 112.

(Measure biometrics and accumulate data)
The measurement guide output unit 12 is a function for outputting a measurement guide for a biological index to the panel 108. Specifically, information such as the type (measurement item) of the biological index to be measured, the measurement timing of each biological index, the number of times of measurement, and the measurement method is output as a measurement guide. Note that the measurement guide output unit 12 may transmit the measurement guide to each measurement device via the communication connector 104 and output the measurement guide from the display panel or the audio output unit of the measurement device.

  Here, it is desirable that the measurement timing, the number of measurements, the measurement method, and the like of each biomarker be determined from a medical viewpoint. As a method for defining the measurement timing, for example, (1) a method of defining the measurement timing based on the user's event (behavior) such as “when waking up”, “after meal”, “after bathing”, “before going to bed” , (2) A method of defining the measurement timing by time or time zone, such as “10:00 am”, “once every two hours”, “7 am to 9 am”, (3) “morning”, “ There are methods for defining the measurement timing based on the classification of the day such as “before noon”, “evening”, and “midnight”.

Any prescription method may be used, but in the present embodiment, because of the advantage that it is possible to flexibly deal with differences in daily life patterns (time for waking up, eating, sleeping, working, etc.) by people and daily differences, Adopt a prescribed method. For example, regarding the “blood pressure value”, blood pressure at the measurement timing of at least two points of “when waking up” and “before going to bed”, preferably five points including “after breakfast”, “after lunch” and “after dinner” Request a measurement. It is medically recommended to measure blood pressure at waking up within 1 hour after waking up, after urination, before taking medicine, and before breakfast. The blood pressure is preferably measured after resting in a sitting position for 1 to 2 minutes. Therefore, these pieces of information may be output as a measurement guide. For “blood glucose level”, for example, six measurement timings of “before breakfast”, “after breakfast”, “before lunch”, “after lunch”, “before dinner”, “after dinner”, and “before bedtime” are measured. It is good to set. For “body weight” and “BMI”, for example, four measurement timings of “when getting up”, “after breakfast”, “after dinner”, and “before going to bed” may be set. As described above, it is assumed that the measurement timing is set in advance for each biological index, and the user is required to perform measurement of various biological indexes according to the measurement timing. Note that the setting of the measurement timing described here is an example, and each measurement timing may be appropriately set to a timing at which a change in a biological index or a change in health condition can be appropriately monitored.

  When the user measures the biometric index according to the measurement guide, the biometric index collection unit 10 acquires measurement data from the measurement device via the communication connector 104. When the measuring device is always connected, measurement data is collected almost in real time. The measurement data acquired from the measuring device is accumulated in the user information DB 11 that is a storage means. At this time, measurement data is recorded together with information indicating measurement timing such as measurement date and time.

  FIG. 5 shows an example of measurement data stored in the user information DB 11. In the example of FIG. 5, a data set for each day is accumulated and managed for three items of blood glucose level, BMI, and blood pressure value. The data set is a measurement data management unit, and typically includes a group of measurement data for one day. However, the present invention is not limited to this, and a measurement data group acquired during an arbitrarily defined unit period (for example, one week, several days, half a day, several hours, etc.) can be handled as a data set.

  As shown in FIG. 5, according to the present apparatus, measurement data measured at the same measurement timing is accumulated in the user information DB 11. Thus, by continuously collecting and accumulating measurement data of various biological indices, for example, it is possible to perform fixed point observation of biological index values, early detection of abnormalities, comprehensive evaluation of health conditions (estimation of disease risk), etc. Become.

(Process when measurement data cannot be acquired)
As described above, the overall health condition determination apparatus 1 according to the present embodiment is based on the premise that the user measures the biomarker according to the predetermined measurement timing and accumulates the measurement data. However, in reality, there is a possibility that the user forgets to perform the measurement, or the necessary measurement data cannot be acquired due to a measurement failure or a malfunction of the measurement device. Therefore, when the necessary measurement data cannot be acquired at a certain measurement timing, the total health condition determination apparatus 1 prevents the measurement data from being lost by the procedure of the following processing example 1 or 2.

<Processing Example 1>
Processing example 1 is an example in which the biometric index is remeasured on another day. The flow of Processing Example 1 will be described along the flowchart of FIG.

  In step S60, the remeasurement request unit 13 checks whether measurement data has been acquired according to the measurement timing instructed by the measurement guide. If the measurement data has been acquired, that is, if re-measurement or the like is not necessary, the process ends (S60; YES).

On the other hand, when the measurement data has not been acquired (S60; NO), the remeasurement request unit 13 requests the user to remeasure the corresponding biological information (S61). For example, the remeasurement request unit 13 may display a remeasurement request message with a content such as “please remeasure blood pressure at XX tomorrow” on the panel or output the sound. The re-measurement request unit 1
3 may transmit a remeasurement request message to the corresponding measurement device, and output the remeasurement request message on the measurement device side. Furthermore, it is preferable that the remeasurement request unit 13 sends a remeasurement request message by e-mail to a mobile phone or personal computer possessed by the user and outputs a remeasurement request from the mobile phone or personal computer.

  When measurement data can be acquired as requested for remeasurement (S62; YES), the measurement data is accumulated in the user information DB 11 (S63).

  On the other hand, when the re-measurement is not performed (S62; NO), a defect occurs in the measurement data. In this case, for example, a confirmation message such as "Do you want to complement from past data? (It is an estimate because it is not actually measured.)" After asking the user whether or not, the data complementing unit 14 complements the data (S64). Details of the complement processing will be described later. The reason why the user confirms whether or not the supplement is necessary is to allow the user to recognize that the complement data is less accurate than the measurement data. If it is difficult to supplement data because past data is not sufficiently accumulated, the user may be requested to perform remeasurement again without performing data complementation.

<Processing example 2>
Processing example 2 is an example in which re-measurement of the biometric index is performed on the same day. The flow of the processing example 2 will be described along the flowchart of FIG.

  At each measurement timing, a time (remind time) at which a remeasurement request is made is set in advance. The remind time is set at or near the end of the measurement timing. For example, when “wake-up”, which is the measurement timing of the blood pressure value, has a range from 5:30 am to 9:00 am, the remind time is set to 9:00 or around that time.

  When the remind time comes, the process of step S60 in FIG. 6 is started. In step S60, the remeasurement request unit 13 determines whether measurement data has been acquired at the measurement timing corresponding to the remind time. In the case of the above example, at 9:00, the remeasurement request unit 13 refers to the user information DB 11 and determines whether or not the blood pressure value at the measurement timing “when waking up” has been accumulated. .

  If the measurement data has been acquired, that is, if re-measurement or the like is not necessary, the process ends (S60; YES).

  On the other hand, when the measurement data has not been acquired (S60; NO), the remeasurement request unit 13 requests the user to remeasure the corresponding biological information (S61). For example, the re-measurement request unit 13 displays a re-measurement request message with a content such as “Please re-measure the blood pressure value when waking up” on the panel or outputs the sound. Similarly to the processing example 1, the remeasurement request may be output by a measurement device, a mobile phone, or the like.

  When measurement data can be acquired from a measurement device within a predetermined time (for example, within one hour) after a re-measurement request (that is, when re-measurement is performed by the user) (S62; YES), the measurement data Is stored in the user information DB 11 (S63). The reason why the remeasurement time is limited is to prevent confusion between the remeasurement measurement data and the measurement data acquired at another measurement timing.

On the other hand, when the re-measurement is not performed (S62; NO), a defect occurs in the measurement data. In this case, for example, a confirmation message such as "Do you want to complement from past data? (It is an estimate because it is not actually measured.)" After asking the user whether or not, the data complementing unit 14 complements the data (S64). Hereinafter, the supplement processing will be described in detail.

(Data loss completion)
The data complementation part 14 complements the missing part of a data set using the past data set accumulate | stored in user information DB11. Since the value of the biometric index constantly fluctuates, the value of measurement data and its change (transition) differ for each data set. Therefore, it is preferable to evaluate the degree of coincidence of the measurement data values and the degree of coincidence of the change patterns as the degree of similarity between the data sets, and select a data set used for complementation based on the degree of similarity.

  Here, the data complementing method includes (1) a method that focuses on the similarity of a biometric index data set in which a defect has occurred, and (2) a similarity of a biometric index data set other than a biometric index in which a defect has occurred. There are a focused method and (3) a method of using another person's data set. The data complementing unit 14 can adopt any one of the complementing methods, or adopt two or three complementing methods, depending on the ratio of data loss, the type of biometric index, the accumulation status of past data, etc. The complementing method may be switched adaptively. Complement method (1) is suitable when only a part of the data in the data set is missing (when the percentage of missing data is small), and the complement method (2) is used for most or all data in the data set. Suitable for missing cases. Further, the complementing method (3) is suitable when there is little accumulation of past data.

(1) Method Focusing on Similarity of Data Set of Biomarkers in Which Defects Occur FIG. 7 is a diagram for explaining a complementing method (1). FIG. 7 is an example of a data set of “blood pressure value”, and data is obtained from five measurement data D1 to D5 of “when getting up”, “after breakfast”, “after lunch”, “after dinner”, and “before going to bed”. Set is configured.

  In the current data set 70, the measurement data D4 after dinner is missing. In this case, the data complementing unit 14 pays attention to the measurement data D1 to D3 and D5 other than the missing part, and includes each of the data set 70 including the missing data and the plurality of past data sets 71 stored in the user information DB 11. Are evaluated (S71). In addition, as the past data set 71, a data set for a past day can be used, or an average value or a mode value of measurement data in a past certain period (for example, one week, one month, etc.). A data set calculated based on the above can also be used.

As a method for evaluating the similarity, any known method capable of evaluating the similarity between data strings (data sets) may be adopted. For example, when the data string of the current data set 70 is Da1 to Da5 and the data string of the past data set 71 is Db1 to Db5, the similarity may be evaluated by the following score S.
S = Σ | Daj−Dbj | (j = 1, 2, 3, 5)
The score S is a sum of absolute values of differences between corresponding measurement data in the two data sets 70 and 71. The smaller the score S, the higher the similarity between the two data sets.

  As another method, there is a method of evaluating the correlation coefficient between the two data sets 70 and 71. The larger the correlation coefficient, the higher the similarity between the two data sets. There are various other methods for evaluating similarity, such as a method that uses pattern similarity, a method that uses a stochastic transition model such as a hidden Markov model, a method that uses a Bayesian network, and a method that uses fuzzy. Can be used.

After calculating the similarity between the data sets as described above, the data complementing unit 14 selects one past data set 72 having the highest similarity to the current data set 70 (S72).
). This is called a similar data set 72.

  Then, the data complementing unit 14 extracts the measurement data D4 measured at the same measurement timing as the missing part from the similar data set 72, and incorporates the extracted measurement data into the missing part of the data set 70 (S73). Thereby, the missing part of the current data set 70 is complemented.

(2) Method focusing on similarity of biometric data sets other than the biometric data in which the deficiency has occurred In the complementing method (1), when the blood pressure data is missing, the similarity between the blood pressure data sets is calculated. Similar data sets to be used for complementation are selected by evaluation. However, this method has a risk that the complement accuracy decreases as the rate of data loss in the current data set increases (the number of measurement data decreases). Further, when all data in the current data set is missing (when there is no measurement data), the complementing method (1) cannot be used. Complementation method (2) is a method to solve such problems, not only when the percentage of missing data is small, but also with reasonable supplementary data when most or all of the data in the data set is missing. It is a way to get.

  FIG. 8 is a diagram for explaining the complementing method (2). FIG. 8 shows a “blood pressure value” data set composed of five points of measurement data D1 to D5, as in FIG. However, since the measurement data D2 to D5 are missing in the current data set 80, it is difficult to use the complement method (1).

  Therefore, the data complementing unit 14 prepares a data set 81 of another biological index acquired on the same day (or the same unit period) as the blood pressure value data set 80 including a defect (S81). In the example of FIG. 8, a “blood glucose level” data set 81 is read.

  Next, the data complementing unit 14 evaluates the similarity between the blood glucose level data set 81 and each of the plurality of past data sets 82 of blood glucose levels stored in the user information DB 11, and the data with the highest similarity is obtained. A set is selected (S82). As the similarity evaluation method, the same method as described in the complementing method (1) can be used.

  Subsequently, the data complementing unit 14 selects a blood pressure value data set acquired on the same day (or the same unit period) as the selected blood sugar level data set as the similar data set 83 (S83). Then, the data complementing unit 14 extracts the measurement data D2 to D5 measured at the same measurement timing as the missing part from the similar data set 83, and incorporates the extracted measurement data into the missing part of the data set 80 (S84). ). Thereby, the missing part of the data set 80 of the current blood pressure value is complemented.

  In addition, in the complementation method (2), only the similarity of one biological index (blood glucose level) is evaluated, but the deficiency is obtained by comprehensively evaluating the similarity of a plurality of biological indices (for example, blood glucose level and BMI). It is also preferable to specify a similar data set to be used for complementing. For example, the similarity between the blood glucose level data sets and the similarity between the BMI data sets may be calculated, and the data set on the day with the largest sum of the similarities may be used for complementation. Thus, comprehensive evaluation of the similarity of a some biometric parameter | index can obtain complementary data with higher validity.

  Further, in the complementing methods (1) and (2), data corresponding to the missing portion is extracted from the similar data set, and the extracted measurement data is used as the missing portion data of the current data set. Alternatively, it is also preferable to replace the similar data set with the current data set containing the defect. This method is preferably applicable when, for example, most or all of the data in the data set is missing.

(3) Method of using another person's data set If the personal information of the user is not sufficiently stored in the user information DB 11, the complementing methods (1) and (2) cannot be used. Therefore, the data complementing unit 14 supplements the missing portion using past data of another person of the same age and same sex as the user, which is accumulated in the user information DB 11.

  FIG. 9 shows an average blood pressure value in each time zone calculated from past data of another person of the same age and same sex as the user. For example, if the data at 17:00 is missing in the current data set, the average blood pressure value of 121.5 mmHg from 16:00 to 18:00 is extracted from the database of FIG.

  Here, the average value of past data of others is used, but the method of using other people's data sets is not limited to this. For example, as in the complementing methods (1) and (2), the degree of similarity between the user's current data set and another person's past data set is evaluated, and the other person's data set having the highest degree of similarity is used as the user data. It can also be used to complement defects.

(Advantages of this embodiment)
According to the configuration described above, measurement data measured at the same measurement timing is accumulated every day. The measurement data collected in this way can be used for, for example, fixed point observation of biological indices, early detection of abnormalities, comprehensive evaluation of health conditions, and the like. In this embodiment, when measurement data cannot be acquired, the user is requested to perform re-measurement. Therefore, forgetting measurement can be prevented, and the user is encouraged to be aware of the measurement. There is an advantage that you can.

  If the measurement data is still not obtained even when re-measurement is requested, the missing portion of the measurement data is supplemented using the past data set. Therefore, even if the measurement of the biological index is not performed for some reason, it is possible to evaluate the health condition using the complementary data. In addition, since the data missing portion is complemented using the data set most similar to the current state among the data sets accumulated in the past, appropriate complemented data can be obtained.

  Even if it is appropriate supplementary data, it cannot be denied that accuracy is inferior to actual measurement data. Therefore, in the present embodiment, by requesting remeasurement first and complementing the missing portion as a preliminary means, priority is given to the acquisition of measurement data, and data complementation is unavoidable only when a loss occurs. The system of doing is realized.

When outputting the health condition evaluation result or the like, it is preferable to notify the user of the evaluation result obtained only from the measurement data or the evaluation result using the complementary data. For example, a message such as “The blood pressure value estimated from past data is used to calculate this evaluation result. To obtain a more accurate evaluation, actually measure the blood pressure.” Good. Alternatively, information representing reliability may be added to the complementary data itself or an evaluation result using the complementary data. Reliability is information (a scale) representing the degree of variation expected in complementary data and evaluation result values, and can also be referred to as value uncertainty (or certainty). For example, when a disease risk is point-output as an evaluation result, reliability may be expressed by a range of variation such as “disease risk: 70 ± 5”, or a range such as “disease risk: 63 to 75”. The reliability may be expressed as follows. Further, the variation may be expressed by an average value and a variance. Alternatively, the range of variation and the boundary of the range can be made ambiguous by fuzzy sets such as “disease risk: 70 ± about 5” or “disease risk: about 63 to about 75”. As described above, when complementary data is used, the reliability of the evaluation result can be guaranteed by providing a range for the value of the evaluation result or the like.

  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 measurement data stored in the user information DB. FIG. 6 is a flowchart showing the processing when measurement data cannot be acquired. FIG. 7 is a diagram for explaining a data loss complementing method (1). FIG. 8 is a diagram for explaining a data loss complementing method (2). FIG. 9 is a diagram for explaining a data loss complementing method (3). FIG. 10 is a diagram illustrating a concept model of a health management system.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Comprehensive health condition determination apparatus 2-5 Measuring apparatus 10 Biometric index collection part 11 User information DB
12 Measurement guide output unit 13 Re-measurement request unit 14 Data complementing unit 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

Claims (9)

Measurement data acquisition means for acquiring, from the measurement device, measurement data measured by the measurement device according to a predetermined measurement timing for the biological index used for the evaluation of the health condition;
Storage means for storing a plurality of measurement data acquired in one day or a predetermined unit period as a data set;
Remeasurement request means for requesting the user to remeasure the biometric index when measurement data of the biometric index cannot be obtained at a certain measurement timing;
When a measurement data loss occurs in the biometric data set because re-measurement was not performed, a past data set accumulated in the storage means is used to supplement the missing part of the data set including the loss Complementary means to
With
The supplement means is
Focusing on the measurement data other than the missing part, by evaluating the degree of similarity between the data set including the defect and each of a plurality of past data sets accumulated in the storage means, the highest degree of similarity is obtained. Select past data sets as similar data sets,
It picked raw body index management device you characterized by complementing the missing part of the data set including the defect by using the similar data set. Measurement data acquisition means for acquiring, from the measurement device, measurement data measured by the measurement device according to a predetermined measurement timing for the biological index used for the evaluation of the health condition;
Storage means for storing a plurality of measurement data acquired in one day or a predetermined unit period as a data set;
Remeasurement request means for requesting the user to remeasure the biometric index when measurement data of the biometric index cannot be obtained at a certain measurement timing;
When a measurement data loss occurs in the biometric data set because re-measurement was not performed, data including the loss is stored using a past data set stored in the storage means.
Complementing means to complement the missing part of the tuset,
With
For a plurality of items of biomarkers, measurement data is acquired by the measurement data acquisition means and a data set is stored in the storage means,
When a loss of measurement data occurs in the data set of the first biometric index among the plurality of biometric indices,
The complementing means includes a data set of a biometric index other than the first biometric index acquired on the same day or the same unit period as the data set including the defect, and the other data stored in the storage means. By evaluating the degree of similarity of each biometric index with a plurality of past data sets, a past data set of the other biometric index having the highest similarity is selected,
Selecting the past data set of the first biometric index acquired on the same day or the same unit period as the past data set of the selected other biometric index as a similar data set;
It picked raw body index management device you characterized by complementing the missing part of the data set including the defect by using the similar data set. The supplement means is
Extracting measurement data measured at the same measurement timing as the missing portion from the similar data set,
The biometric index management apparatus according to claim 1 or 2 , wherein the extracted measurement data is used as data of the missing portion. The supplement means is
Biomarker management apparatus according to claim 1 or 2, characterized in that to replace the data set including the defect in the similar data set. The biological index management device according to any one of claims 1 to 4 ,
One or a plurality of measuring devices for measuring a biological index from the user;
A biometric index management system comprising: Computer
For the biological index used for the evaluation of the health condition, obtaining measurement data measured by the measurement device according to a predetermined measurement timing from the measurement device;
Storing a plurality of measurement data acquired in one day or a predetermined unit period in a storage means as a data set;
Requesting the user to remeasure the biometric index when measurement data of the biometric index cannot be obtained at a certain measurement timing;
When a measurement data loss occurs in the biometric data set because re-measurement was not performed, a past data set accumulated in the storage means is used to supplement the missing part of the data set including the loss And steps to
In the biological index management method for executing
In the step of complementing the missing portion,
Focusing on the measurement data other than the missing part, by evaluating the degree of similarity between the data set including the defect and each of a plurality of past data sets accumulated in the storage means, the highest degree of similarity is obtained. Select past data sets as similar data sets,
A biometric index management method, wherein a missing portion of a data set including the deficiency is supplemented using the selected similar data set .   Computer
  For the biological index used for the evaluation of the health condition, obtaining measurement data measured by the measurement device according to a predetermined measurement timing from the measurement device;
  Storing a plurality of measurement data acquired in one day or a predetermined unit period in a storage means as a data set;
  Requesting the user to remeasure the biometric index when measurement data of the biometric index cannot be obtained at a certain measurement timing;
  When a measurement data loss occurs in the biometric data set because re-measurement was not performed, a past data set accumulated in the storage means is used to supplement the missing part of the data set including the loss And steps to
In the biological index management method for executing
  For multiple items of biomarkers, acquisition of measurement data and accumulation of data sets in the storage means are performed,
  When a loss of measurement data occurs in the data set of the first biometric index among the plurality of biometric indices,
  In the step of complementing the missing portion,
  A data set of another biometric index other than the first biometric index acquired on the same day or in the same unit period as the data set including the defect, and the past of the other biometric index accumulated in the storage unit By evaluating the similarity with each of a plurality of data sets, the past data set of the other biometric index with the highest similarity is selected,
  Selecting the past data set of the first biometric index acquired on the same day or the same unit period as the past data set of the selected other biometric index as a similar data set;
  Using the selected similar data set, the missing portion of the data set including the deficit is complemented.
A biometric index management method characterized by the above. The program for making a computer perform each step of the biometric index management method of Claim 6 or 7.   A computer-readable recording medium on which the program according to claim 8 is recorded.

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