JP2017097401A - Behavior modification analysis system, behavior modification analysis method and behavior modification analysis program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a system detecting activity information of a subject varying in association with elapse of time and accurately generating a comment on the basis of the activity information varying.SOLUTION: A behavior modification analysis system 1 comprises: a detection section 20 acquiring activity information of a subject P; an analysis section 45 generating analysis information by analyzing the activity information for predetermined periods; and a behavior modification information generation section 46 generating behavior modification information indicating behavior modification of the subject P on the basis of first analysis information generated by analyzing the activity information in a first period including at least one predetermined period and second analysis information generated by analyzing the activity information in a second period including at least the predetermined period different from the first period.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a behavior change analysis system, a behavior change analysis method, and a behavior change analysis program.

2. Description of the Related Art There is known an advice providing system that analyzes health management data obtained from a vital measurement device used by a subject and notifies the subject of comment information associated with the analysis information.
For example, in the following Patent Document 1, the health management data measured by the vital measuring device is compared with a preset reference value of the health management data, and an abnormality in the health management data is detected based on the comparison result. A system for sending advice to a terminal device using a comment information table associated with health management data is disclosed.

JP 2011-24677 A

However, in the conventional advice providing system, since the advice is generated based on the comparison between the measured health management data and the reference value of the health management data, the difference from the reference value at the time when the health management data is measured. However, when the subject's behavior pattern changed over time, changes in health management data caused by the change could not be detected. In other words, the conventional advice providing system cannot detect a change in the life rhythm of the subject.
The present invention has been made in view of the above-described problems, and an object of the present invention is to detect health management data that has fluctuated over time, and to accurately generate advice based on the changed health management data. In other words, the object is to detect changes in the life rhythm of the subject.

  SUMMARY An advantage of some aspects of the invention is to solve at least a part of the problems described above, and the invention can be implemented as the following forms or application examples.

[Application Example 1]
The behavior change analysis system according to this application example includes an activity information acquisition unit that acquires activity information of a subject, an analysis information generation unit that generates analysis information obtained by analyzing the activity information for a predetermined period, and at least one of the predetermined Analyzing the first analysis information generated by analyzing the activity information in the first period including the period, and the activity information in the second period including at least the predetermined period different from the first period A behavior modification information generating unit configured to generate behavior modification information indicating the behavior modification of the subject based on the generated second analysis information.

  According to such a configuration, the first analysis information generated by analyzing the activity information in the first period and the activity information in the second period different from at least the first period are generated. Based on the second analysis information, the behavior change information indicating the subject's behavior change is generated, so that the behavior change information with the passage of time can be generated.

[Application Example 2]
In the behavior change analysis system according to the application example, the analysis information includes an activity amount including at least one of the number of steps, the amount of exercise, the exercise time, and the calorie consumption in the predetermined period on a day of the week or on a day. The index is preferably calculated according to at least one of the time zones.

  According to such a configuration, action modification information in which the amount of activity including at least one of the number of steps, the amount of exercise, the exercise time, and the calorie consumption is changed according to the day of the week or the time zone of the day is generated. it can.

[Application Example 3]
In the behavior change analysis system according to the application example, it is preferable that the analysis information includes a behavior pattern of the subject estimated based on the index.

  According to such a configuration, it is possible to generate behavior change information related to a subject's behavior pattern that has changed over time.

[Application Example 4]
In the behavior change analysis system according to the application example, it is preferable that the behavior change information includes difference information indicating a difference between the first analysis information and the second analysis information.

  According to such a structure, the difference information of the analysis information with the passage of time can be acquired from the behavior change information.

[Application Example 5]
In the behavior change analysis system according to the application example, it is preferable that the difference information indicates a change amount of the step count, the exercise amount, the exercise time, or the calorie consumption in the first analysis information and the second analysis information. .

  According to such a configuration, the amount of change in the number of steps, the amount of exercise, the exercise time, or the calorie consumption over time can be acquired from the behavior change information.

[Application Example 6]
The behavior change analysis system according to the application example described above preferably includes an output unit that outputs text information related to the behavior change of the subject and a graph indicating the behavior change of the subject based on the behavior change information.

  According to such a configuration, text information and a graph based on the behavior change information can be output.

[Application Example 7]
The behavior change analysis system according to the application example described above preferably includes a notification unit that notifies the subject of the behavior change based on the behavior change information.

  According to such a structure, a test subject's action change can be alert | reported.

[Application Example 8]
The behavior change analysis system according to the application example preferably includes a comment generation unit that generates comment information based on the behavior change information.

  According to such a configuration, comment information based on behavior change information can be generated.

[Application Example 9]
In the behavior change analysis system according to the application example, the comment generation unit estimates the cause of the behavior change of the subject based on the behavior change information, and generates the comment information based on the estimation result. Is preferred.

  According to such a configuration, since the factor causing the subject's behavior change is estimated based on the behavior change information, comment information based on the estimation result can be generated.

[Application Example 10]
In the behavior change analysis system according to the application example, it is preferable that the system includes a biological information acquisition unit that acquires biological information of the subject, and the analysis information generation unit generates the analysis information by analyzing the biological information. .

  According to such a configuration, analysis information can be generated by analyzing biological information.

[Application Example 11]
In the behavioral change analysis system according to the application example, the analysis information generation unit calculates a pitch when the subject moves based on the activity information, calculates a heart rate of the subject based on the biological information, The analysis information indicating the total activity time of the subject may be generated based on the pitch and the heart rate.

[Application Example 12]
The behavior change analysis method according to this application example acquires activity information of a subject, generates analysis information obtained by analyzing the activity information for a predetermined period, and the activity in a first period including at least one predetermined period First analysis information generated by analyzing information, and second analysis information generated by analyzing the activity information in a second period including at least the predetermined period different from the first period. Based on the above, behavior change information indicating the behavior change of the subject is generated.

  According to such a method, the first analysis information generated by analyzing the activity information in the first period and the activity information in the second period that is different from at least the first period are generated. Based on the second analysis information, the behavior change information indicating the subject's behavior change is generated, so that the behavior change information with the passage of time can be generated.

[Application Example 13]
The behavior change analysis program according to this application example includes a function of acquiring activity information of a subject, a function of generating analysis information obtained by analyzing the activity information for a predetermined period according to a predetermined period, and at least one predetermined period Analyzing and generating the first analysis information generated by analyzing the activity information in the first period including and the activity information in the second period including at least the predetermined period different from the first period The computer is caused to execute a function of generating behavior change information indicating the behavior change of the subject based on the second analysis information.

According to such a configuration, the first analysis information generated by analyzing the activity information in the first period and the activity information in the second period different from at least the first period are generated. Based on the second analysis information, the behavior change information indicating the subject's behavior change is generated, so that the behavior change information with the passage of time can be generated.

Explanatory drawing showing the outline | summary of the action change analysis system which concerns on embodiment. The block diagram showing the schematic structure of a behavior change analysis system. The entity related figure which shows the relationship of the database table of a server. The figure which normalized walking time per day by classifying walking time for every day of the week. The figure which normalized walking time by classifying walking time according to time zone. The figure which shows an example of the 1st parameter | index of the resting heart rate according to time slot | zone. The figure which totaled the appearance frequency of the two-dimensional data of the pitch at the time of a walk, and a heart rate. The block diagram explaining the modification 1. FIG. The figure which classified the walking time according to time zone into the basic pattern. The block diagram explaining the modification 2. FIG. The figure which shows an example of the typification pattern divided | segmented on weekdays and Saturdays and Sundays. Explanatory drawing showing the outline | summary of the terminal device concerning the modification 3. FIG.

  Embodiments of the present invention will be described below with reference to the drawings.

(Embodiment)
The outline of this embodiment will be described with reference to FIG. FIG. 1 is an explanatory diagram showing an outline of the behavior change analysis system 1.
The behavior change analysis system 1 is a system that detects movement data of the subject P, analyzes changes in the behavior pattern of the subject P based on the detected movement data, and provides the analyzed result as a comment.

The behavior change analysis system 1 is used by a terminal device 2 attached to a subject P, a server 4 installed in a server room, and the like, a mentor M who teaches the subject P, and related parties such as family members and third parties. External device 8 or the like.
The terminal device 2 is a wristwatch-type terminal device that is worn on the wrist WR of the subject P. The terminal device 2 includes a detection unit 20 that detects exercise data of the subject P, and a display unit 21 that displays a comment message to the subject P. It is exposed to the face on the wrist WR side.

The server 4 is one or a plurality of servers configured by a database engine or the like, and implements various functions to be described later as well as the stored data providing service. The server 4 is connected to a network 78, and the server 4 and the terminal device 2 are connected to each other through a communication 3 so that various data can be transmitted and received.
The external device 8 is a general tablet terminal or PC (Personal Computer) used by the mentor M, and includes a display unit 91 and an operation unit 93 that can edit a comment wording. The external device 8 and the server 4 are connected to each other via a communication 5 so that various data can be transmitted and received. In the present embodiment, it is assumed that the external device 8 is operated by the mentor M in order to generate comment information for the subject P.

(Configuration of behavior change analysis system)
FIG. 2 is a block diagram illustrating a schematic configuration of the behavior change analysis system 1.

(Configuration of terminal device)
The terminal device 2 includes a detection unit 20, a display unit 21, an operation unit 23, a communication unit 25, a control unit 27, and the like.

As a preferred example, the detection unit 20 is a sensor unit including a pulse wave sensor, an acceleration sensor, a gyro sensor, and a GPS (Global Positioning System) sensor (all not shown). However, the sensor is not limited to this configuration, and any sensor that can collect posture information, position information, environment information, and exercise state information of the subject P wearing the terminal device 2 may be used.
The pulse wave sensor has a light emitting element such as an LED (Light Emitting Diode) and a light receiving element such as a photodiode, and the light irradiated by the light emitting element is reflected by the blood vessel of the wrist WR and collects the reflected light. Light is received by the light receiving element. At this time, the pulse wave sensor detects the pulse wave of the subject from the variation information of the amount of received light by using a phenomenon in which the reflectance of light is different between when the blood vessel is dilated and when it is contracted. Based on the detected pulse wave data, the controller 27 calculates exercise data such as the pulse rate (heart rate), calories burned derived from the pulse rate, exercise time, and exercise intensity. That is, the exercise data includes activity information and biological information of the subject.

The acceleration sensor is an acceleration sensor attached in one axial direction or two or more axial directions (for example, three axial directions of X, Y, and Z axes), and measures an acceleration change of each axis per unit time.
The gyro sensor measures the angular velocity per unit time with the X, Y, and Z axes in the acceleration sensor as the central axes. Using the acceleration change data and the angular velocity data detected by the acceleration sensor and the gyro sensor, the change amounts are integrated, and the exercise intensity and the exercise amount corresponding to the change amounts are calculated. From the exercise intensity and exercise quantity obtained in this way, exercise time, exercise days, and the like are calculated.
The GPS sensor includes a GPS reception function and a position information calculation circuit, and measures position information (latitude, longitude, altitude) data for each unit time. The movement distance and the movement speed are calculated from the position information for each unit time, and the exercise amount of the subject P is calculated in combination with other sensor information.
Furthermore, an environmental sensor such as a temperature sensor or an atmospheric pressure sensor may be provided to collect environmental information such as the temperature and atmospheric pressure around the terminal device 2.

Further, the detection unit 20 is not limited to being incorporated in the terminal device 2, but communicates with other devices such as a weight measuring device, a height measuring device, a running machine or an exercise bike installed in a sports gym. Thus, it may be configured to acquire various information including physical information measured by other devices as exercise data. In this case, the measurement data may be transmitted from another device to the terminal device 2, and the measurement data may be transmitted from the terminal device to the server 4. Alternatively, the measurement data may be transmitted directly from the other device to the server 4. You may comprise so that it may do.
The detection unit 20 corresponds to an activity information acquisition unit and a biological information acquisition unit.

  The display unit 21 is a display device capable of displaying characters and icons, and is, for example, a flexible dot matrix type EPD (Electrophoretic Display) that can be flexibly deformed. Based on the display signal output from the control unit 27, information such as a comment wording is displayed.

  The operation unit 23 is an input device that includes a touch sensor, a touch panel, and the like. The operation unit 23 is disposed on the surface of the display unit 21 and detects a touched portion by a method such as a capacitance method or a resistance film method. The detection signal is output to the control unit 27.

  As a preferred example, the communication unit 25 is a short-range wireless device, has a common communication protocol with the communication unit 79 of the server 4, and is connected to the server 4 through the communication 3 so that various data can be transmitted and received. Note that the communication unit 25 may be a wired communication device, in which case the communication 3 is connected via a cable or the like. The communication unit 25 may have a communication protocol common to the communication unit 95 of the external device 8 and may be configured to transmit and receive various data between the terminal device 2 and the external device 8. In the present embodiment, the exercise data of the subject P detected by the detection unit 20 is transmitted to the server 4 via the communication of the communication unit 25.

  The control unit 27 includes a processor such as a CPU (Central Processing Unit) and a DSP (Digital Signal Processor), a storage device such as a ROM (Read Only Memory), a flash ROM, and a RAM (Random Access Memory). They are a control device and an arithmetic device that collectively control each part of the terminal device 2 according to various programs stored in the device.

(Server configuration)
The server 4 includes a database server such as a subject information storage unit 30, an activity information management unit 40, and a comment generation unit 60, a communication unit 79, and the like. The server 4 and the communication unit 79 are connected by a network 78.

  The communication unit 79 includes a plurality of communication devices such as a LAN (Local Area Network) communication device, a wireless LAN communication device, and a short-range wireless communication device. The communication unit 79 is connected between the servers in the server 4, the terminal device 2, and an external device. 8 has a common communication protocol, and various devices are communicably connected to each other.

  The subject information storage unit 30 includes a storage unit 33 including a data storage area of a database. The storage unit 33 includes a storage device such as a ROM, a flash ROM, a RAM, an HDD (Hard Disk Drive), and an SSD (Solid State Drive), and a subject information DB 35 managed in a table format is arranged. The subject information DB 35 stores unique information of the subject P.

In this embodiment, the subject information DB 35 is identified by assigning a UID (user ID) to the subject P. The subject information DB 35 stores information such as UID, name, sex, date of birth, exercise purpose, work information, and disease information as unique information of the subject P. The unique information is an example, and other information such as height and weight at the start of the exercise program, address, and local information may also be included.
A configuration example of a table managed by the subject information DB 35 and cooperation with other tables will be described later with reference to FIG.

  The activity information management unit 40 includes a processing unit 41 including a CPU and a database engine such as a relational database, and a storage unit 47 including a data storage area of the database. The database engine has a basic function of managing the database, and processes such as registration, update, deletion, and search of data in the database and transaction processing are executed under the control of the CPU.

The processing unit 41 includes functional units of an exercise data receiving unit 43, an analysis unit 45, and a behavior change information generation unit 46. The functions of these functional units are realized by a CPU (computer) executing a behavior change analysis program (not shown) in which procedures for controlling each process of the database engine, arithmetic processing, and the like are described. Note that these functional units are merely examples, and are not necessarily essential components, and other functional units may be included.
The behavior change analysis program acquires the activity information of the subject P, generates analysis information obtained by analyzing the activity information according to a predetermined period, and shows the behavior change of the subject P based on the analysis information having different periods. It is created based on a behavior change analysis method that generates change information.

  The exercise data receiving unit 43 receives the exercise data and the data related to the exercise data from the terminal device 2 via the communication unit 79, and stores them in the exercise data DB 49.

The analysis unit 45 acquires and analyzes the unique information of the subject P from the subject information storage unit 30 and the exercise data for a predetermined period from the exercise data reception unit 43, and analyzes the analysis results as analysis information (analysis information). And stored in the analysis information DB 51. Analysis information includes the number of days of instruction program, physical fitness level, calorie consumption achievement rate, exercise days, exercise time, zone stay time for each pulse rate band, exercise intensity, calorie consumption increase / decrease, equipment wearing time, day of week and time zone Activity amount (activity amount by day of the week, activity amount by time zone), resting heart rate by day of the week or time zone, walking pitch heart rate distribution, and the like.
Further, the analysis information may include a weight change tendency and a BMI (Body Mass Index) change tendency calculated from physical information collected by other devices. The analysis unit 45 corresponds to an analysis information generation unit.
Further, the analysis information may be information obtained by analyzing exercise data according to the passage of a predetermined time. For example, various exercise data for a predetermined period may be calculated by adding, averaging, or applying each arithmetic expression. In addition, the analysis information may include environmental information and information including the environmental information.

The instruction program elapsed days is the number of days that have elapsed since the subject P started the exercise program.
Further, the physical strength level is an index expressed in five stages by combining the cardiopulmonary ability, muscle strength, exercise ability, etc. of the subject P. From the reference value of the pulse rate representing the physical strength level of each step of the exercise intensity and the subject P Obtained and calculated by comparing with exercise data. Such calculation of the physical strength level is an example, and any calculation method may be used as long as it can be calculated by defining an index representing the level of the physical strength level of the subject P.

The calorie consumption achievement rate is a numerical value (%) in which the achieved ratio is calculated with the target calorie consumption being 100% in the exercise data for a predetermined period.
The number of exercise days is the number of days exercised for a predetermined time (for example, 2 hours) or more per day in the exercise data for a predetermined period.
The exercise time is a time obtained by integrating the exercise time in the exercise data for a predetermined period.

Further, the zone stay time for each pulse rate band is a time obtained by integrating the pulse rate that changes depending on the exercise load for each predetermined band. For example, the predetermined band includes a pulse rate band indicating a fat burning zone and a pulse rate band indicating a muscle strength up zone.
The exercise intensity is an average value of exercise intensity in exercise data for a predetermined period, and the unit is, for example, Mets.
The calorie consumption increase / decrease is information obtained by acquiring information on exercise data in a predetermined period several times before and indicating the increase / decrease result for the calorie consumption in the predetermined period several times ago as “increase” or “decrease”. is there.

Further, the weight change tendency and the BMI change tendency are obtained by acquiring information on exercise data for a predetermined period several times before, and the results of increase / decrease with respect to the body weight and BMI for the predetermined period several times before are increased or decreased. It is the information expressed by.
The device wearing time is a time during which the terminal device 2 is worn by the subject P during a predetermined period.
The activity amount by day of week is an index obtained by tabulating activity amounts such as the number of steps, exercise time, and calorie consumption measured during a certain period in the past for each day of the week.
The activity amount by time zone is an index obtained by tabulating activity amounts such as the number of steps, exercise time, and calorie consumption measured during a certain period in the past for each time zone of the day.

The resting heart rate by day of week is an index obtained by tabulating the resting heart rate measured during a certain period in the past by day of the week.
The resting heart rate by time zone is an index obtained by tabulating the resting heart rate measured during a certain period in the past by the time zone of the day.
The walking pitch heart rate distribution is an index obtained by totaling the walking pitch (steps / minute) and the heart rate frequency measured during a certain period in the past into a two-dimensional histogram.

(Detailed analysis by day and time)
Here, detailed analysis information when day of the week and time zone are adopted as the time axis, and analysis information of walking pitch heart rate distribution will be described.
In this embodiment, the walking time of the subject P is adopted as the amount of activity. However, using the measured values such as the number of steps, exercise time, and calorie consumption, the number of steps by day, the number of steps by time zone, and the exercise time by day of the week. In addition, it is possible to assume a mode in which the exercise time for each time zone is calculated.

(Analysis of walking time by day of the week)
FIG. 4 is a diagram in which the analysis unit 45 classifies the walking time of the past one month or so for each day of the week for the users A to F who are the subjects P, and normalizes the classified result as the walking time per day. It is. Here, the user A, the user B, and the user C are assumed to have a short walking time, and the user D, the user E, and the user F are assumed to have a long walking time. The analysis unit 45 classifies the walking time into three levels of 1 minute to less than 5 minutes, 5 minutes to less than 30 minutes, and 30 minutes or more.
From this classification result, the analysis unit 45 analyzes that a user with a short walking time has a short walking time on each day of the week and has a large number of walks of 1 minute or more and less than 5 minutes. In addition, a user with a long walking time often walks for 5 minutes or more. For example, it is analyzed that the user E is more active on weekdays. Similarly, user F analyzes that he / she is more active on weekends.

(Analysis of walking time by time zone)
FIG. 5 is a diagram in which the analysis unit 45 classifies walking times measured during a certain period in the past by the subject P according to time zones of the day, and normalizes the classified results per time.
Here, FIG. 5 classifies the walking time according to the time zone separately on weekdays and weekends. Since weekdays and Saturdays and Sundays generally have different lifestyle habits, it is effective to separate and tabulate in this way. Of course, when the weekend is not a holiday, it is preferable to set and total the holidays of the subject P individually.

Further, in FIG. 5, the upper row shows a case where the walking time is short, and the lower row shows a case where the walking time is long. The analysis unit 45 classifies the walking time into three levels of 1 minute to less than 5 minutes, 5 minutes to less than 30 minutes, and 30 minutes or more.
From this classification result, the analysis unit 45 analyzes that, for users with a short walking time, walking of 1 minute or more and less than 5 minutes is dominant, the walking time is short as a whole, and the sharpness for each time zone is also poor. Furthermore, since there is no increase in walking time in the morning and evening, the analysis unit 45 analyzes that a private car is used as a commuting method.

  In addition, since users with a lot of walking time often walk for 5 minutes or more, and the walking time in the commuting time zone from morning to evening to night is long on weekdays, the analysis unit 45 makes this subject P public for commuting. Analyzing that they are actively walking during commuting using public transportation. Furthermore, the analysis part 45 can also estimate the normal working hours from the peak of walking time in the morning and evening. Further, since there are many walking times around 6 am on Saturdays and Sundays, the analysis unit 45 analyzes that there is a habit of exercising on the morning of a holiday.

(Analysis of resting heart rate by time of day)
The analysis unit 45 counts the frequency of appearance of the resting heart rate measured for a certain period in the past of the subject P for each value, and indicates the ratio for each time zone of the day, the time of the day. Either or both of the second indices indicating the total average of resting heart rates aggregated by band can be analyzed.
FIG. 6 is a diagram showing an example of a first index of resting heart rate by time zone, with upper user A and user B showing examples of users who do not seem to have habitual drinking, and lower user C and user D are examples of users suspected of habitual drinking.

  As is well known, it is known that the resting heart rate increases due to meals, drinking, stress, tension and the like. The analysis unit 45 shows that the user C and the user D drink alcohol more frequently than the users A and B because the heart rate at rest is seen from the evening to the early morning. And analyze.

(Analysis of walking pitch heart rate distribution)
FIG. 7 is a diagram in which the appearance frequency of two-dimensional data of the pitch (number of steps per unit time) and the heart rate when the subject P is measured during a certain period in the past, for example, walking, is tabulated. . These are three-dimensional graphs, the axis in the height direction indicates the total walking time indicating the total walking time (activity time), one axis on the horizontal plane indicates the walking pitch (steps / minute), and the other The axis of shows the heart rate.
FIG. 7 shows the walking conditions of the users A to D. For example, the user A has a single peak and is a very beautiful mountain, and the analysis unit 45 analyzes that the user is always walking stably. In addition, the user B has two pulse peaks at substantially the same walking pitch, and the analysis unit 45 analyzes that the amount of luggage is related.

Further, since there is a mountain with a high walking pitch in addition to the one peak, the user C analyzes that the analysis unit 45 is performing customary jogging. Since user D has a plurality of peaks, the analysis unit 45 analyzes that there are slopes and stairs on the usual walking route.
In addition, the analysis unit 45 compares the index calculated with the past long-term measurement data with the one calculated with the short-term measurement data such as the most recent week, so that it can be used normally for mountain climbing and hiking. It can be analyzed that you walked differently.
In addition, the aspect performed by the control part 27 of the terminal device 2 can also be assumed for a part of function of the analysis part 45 mentioned above. For example, regarding instruction program elapsed days, physical fitness level, calorie consumption achievement rate, exercise days, exercise time, zone stay time for each pulse rate band, exercise intensity, calorie consumption increase / decrease, equipment wearing time, resting heart rate, walking pitch, etc. Processing may be executed by the control unit 27.

Returning to FIG. 2, the behavior change information generation unit 46 determines the subject P based on the first analysis information analyzed by the analysis unit 45 based on the exercise data and the second analysis information stored in the analysis information DB 51. Behavior pattern change (behavior change) is analyzed, and behavior change information indicating the behavior change of the subject P is generated based on the analysis result. The generated behavior change information is stored in the analysis information DB 51.
In this embodiment, the behavior change information generation unit 46 is longer than the first analysis information (first analysis information) in the first period such as the first period such as the most recent one week, The behavior change information is generated by analyzing the difference between the second analysis information (second analysis information) in the second period such as the past month. In this case, the two periods may have an overlapping region on the time axis, or may be separated without overlapping.

In the present embodiment, the difference between the first analysis information and the second analysis information indicates a change amount (difference information) over time with respect to at least one of the exercise amount, the exercise time, the number of steps, and the calorie consumption. That is, the behavior change information indicates a tendency to change with the passage of time with respect to at least one of the exercise amount, the exercise time, the number of steps and the calorie consumption.
The storage unit 47 is configured by a storage device such as a ROM, a flash ROM, a RAM, an HDD, or an SSD, and an exercise data DB 49 and an analysis information DB 51 managed in a table format are arranged. In the exercise data DB 49, exercise data acquired from the terminal device 2 is stored for each subject P. The analysis information DB 51 stores analysis information and behavior change information calculated based on the exercise data stored in the exercise data DB 49 in association with the exercise data.

The comment generation unit 60 generates comment words and comment word candidates (comment information) to be provided to the subject P based on the analysis information and behavior change information stored in the analysis information DB 51. The generated comment information is transmitted to the external device 8.
For example, when the behavior change information indicates an increase in walking time according to the morning and evening time zones, the comment generating unit 60 is based on the specific information and behavior changing information of the subject P in addition to the increase in the morning and evening walking time. The factor that caused the behavioral change may be estimated, and advice may be generated based on the estimation result. For example, the comment wording may include a guess based on a change in behavior pattern, such as information for estimating that the commuting method has been changed from a private car to public transportation. Moreover, the comment production | generation part 60 may include the exercise menu suitable with respect to the test subject P in a comment wording according to the test subject's P behavior change.

Similarly, when the behavior change information indicates a stable tendency in the resting heart rate for each time zone, the comment generation unit 60 may include, for example, an improvement in lifestyle habits such as drinking habits in the comment wording. In addition, comment language that encourages improvement of lifestyle habits may be included so as to recommend suppression of drinking.
In addition, when the behavior change information indicates changes in a plurality of items, such as analysis of walking time by time zone and analysis of walking pitch heart rate distribution, the comment generation unit 60 can estimate information from the plurality of items. May be included in the comment wording.

(Server / database configuration)
FIG. 3 is an entity relation diagram showing the relation of the database table of the server 4. In the following description, it is assumed that each database is a relational database.
The main key 351 of the subject information DB 35 is a UID. The record 352 is an area for storing unique information, and stores data such as name, sex, date of birth, exercise purpose, work information, and disease information.

The primary key 511 of the analysis information DB 51 is a composite type and includes a WID and a UID. The record 512 is an area where analysis information is stored, the number of days of instruction program elapsed, physical fitness level, calorie consumption achievement rate, exercise days, exercise time, exercise intensity, calorie consumption increase / decrease, weight increase / decrease, equipment wearing time, activity according to day of the week Stores data on volume, activity by time zone, and resting pulse by time zone.
The primary key 731 of the search information DB 73 is composed of AID, WID, and UID. The record 733 is set to the replica X1 of the record 352, and the record 735 is set to the replica X2 of the record 512. .

  The subject information DB 35 and the analysis information DB 51 indicate that they have a predetermined relationship R1. Further, the analysis information DB 51 and the search information DB 73 indicate that they have a predetermined relationship R3.

(External device configuration)
Returning to FIG. 2, the external device 8 will be described.
The external device 8 includes a display unit 91, an operation unit 93, a communication unit 95, a notification unit 96, a storage unit 97, a control unit 80, and the like.

The display unit 91 includes a display panel such as a general LCD (Liquid Crystal Display), and is a display device that performs various displays based on a display signal input from the control unit 80. The display unit 91 displays text information indicated by the behavior change information generated by the activity information management unit 40 and a graph image. The display unit 91 corresponds to an output unit.
The operation unit 93 is an input device including a button switch, a touch panel, and the like, and outputs a pressed button or a touch panel signal to the control unit 80.

The communication unit 95 is a wireless LAN communication device as a preferred example, and has a common communication protocol with the communication unit 79 of the server 4 and is connected to the server 4 via the communication 5 so that various data can be transmitted and received. The communication unit 95 may be a wired communication device. In this case, the communication 5 is connected via a cable or the like.
Further, the communication unit 95 may have a communication protocol common to the communication unit 25 of the terminal device 2 and may be configured to transmit and receive various data between the external device 8 and the terminal device 2. According to this configuration, it is possible to transmit the determined comment word directly from the external device 8 to the terminal device 2 without going through the server 4.
Moreover, the alerting | reporting part 96 alert | reports behavior change based on behavior change information.

  The storage unit 97 is configured by a storage device such as a ROM, a flash ROM, a RAM, an HDD, and an SSD, and stores various programs, data, and the like for realizing each functional unit of the control unit 80.

The control unit 80 includes a processor such as a CPU and a DSP, and a storage device such as a ROM, a flash ROM, and a RAM. The control unit 80 performs overall control of each unit of the external device 8 according to various programs stored in the storage device. Device and arithmetic unit.
The control unit 80 has a function of collecting information such as the unique information, exercise data, and analysis information of the subject P, and a function of acquiring comment information provided from the server 4 based on the collected information. Further, the control unit 80 has a function of editing comment information based on an instruction from the mentor M and a function of providing the edited function to the subject P.
The control unit 80 has a function of notifying the mentor M from the notification unit 96 that the behavior change has occurred based on the behavior change information.

As described above, in the behavior change analysis system 1 according to the present embodiment, the following effects can be obtained.
(1) The behavior change analysis system 1 generates a change in the behavior pattern of the subject P over time as behavior change information, generates a comment based on the generated behavior change information, and notifies the subject P. Since it is possible to generate a comment by capturing the activity change of P, it is possible to appropriately comment based on the activity change of the subject P.
(2) In addition to the change indicated by the behavior change information, the comment generation unit 60 includes a change factor of the behavior pattern estimated from the specific information of the subject P and the behavior change information in the comment, thereby adding to the lifestyle habit of the subject P. Matched comments can be generated.

  Note that the present invention is not limited to the above-described embodiment, and various modifications and improvements can be added to the above-described embodiment. A modification will be described below.

(Modification 1)
Analysis information such as activity by day of the week, activity by day of the week, resting heartbeat by day of the week, resting heartbeat by time of day, and walking pitch heartbeat distribution are all multidimensional indicators and are used as comment search keys. In addition, an aspect of reducing the number of dimensions can be assumed. Below, the case where the walk time according to time zone is assumed as analysis information is demonstrated.
FIG. 8 is a block diagram for explaining the first modification. In the first modification, the walking time for each time zone is calculated from the measurement data of hundreds to thousands of users in advance, and the walking time is normalized by the total walking time of the day, and then the K-average method Using a well-known cluster analysis technique, etc., the pattern is classified into a small number of patterns. FIG. 9 shows an example in which the walking time according to the time zone on weekdays and weekends is classified into six basic patterns.
FIG. 9 shows an example in which, for example, weekday pattern 1 to weekday pattern 6 are classified by normalizing the walking time in each time zone on weekdays. Holiday patterns 1 to 6 show examples in which walking times in each time zone on holidays such as Saturday and Sunday are normalized and classified.

(Modification 2)
FIG. 10 is a block diagram showing a case where pattern matching is adopted as a typification method.
In the second modification, the search key for searching for a comment searches for a pattern closest to the calculated walking time for each time zone by pattern matching from among the typified patterns, and uses the number indicating the categorized pattern. Specifically, normalization of the walking time of a certain user X by time zone is performed in the same manner as in the first modification, and a square error with the typified pattern is obtained by pattern matching processing, etc. Print the number.

In addition, as shown in the table of FIG. 11, in the case of a categorized pattern divided on weekdays and weekends, one comment search key number may be assigned to a combination of weekdays and weekends. That is, when the weekday pattern is “2” and the holiday pattern is “4”, “19” is output as the comment search key number.
Moreover, you may determine a drinking habit using the 1st parameter | index (appearance rate of the heart rate at rest) of the resting heart rate according to time slot | zone. That is, it may be determined by categorizing a pattern in which drinking habits are suspected by clustering as described above and a pattern in which drinking habits are not, and defining a comment search key number according to the presence or absence and degree of drinking habits. Also, using the second index of resting heart rate by time zone (total average of resting heart rate), for example, if the peak of the index is from 7 pm to 3 am, it is determined that there is a drinking habit, so If not, it may be determined that there is no drinking habit.

(Modification 3)
FIG. 12 is an explanatory diagram illustrating an outline of the terminal device 2 according to the third modification.
In the above-described embodiment, the terminal device 2 has been described as a wristwatch-type terminal device including the detection unit 20 that detects the exercise data of the subject P and the display unit 21 that displays the comment information. Absent. The terminal device 2 may have a configuration of a plurality of devices including the sensor band 2 a including the detection unit 20 and the information terminal 2 b including the display unit 21.

The terminal device 2 includes a sensor band 2a attached to the wrist WR of the subject P, an information terminal 2b used by the same subject P, and the like, which are connected to each other via a communication 2c so that various data communications are possible.
The sensor band 2a includes a detection unit 20, a communication unit 25a, a control unit 27a, and the like. The detection unit 20 detects exercise data of the subject P. The communication unit 25a is a short-range wireless communication device as a preferred example, establishes communication with the communication unit 25b of the information terminal 2b via the communication 2c, and transmits and receives various data including transmission of exercise data. The control unit 27a is a CPU or DSP and has a storage device such as a ROM or a RAM.
Since the sensor band 2a is composed of the minimum elements for acquiring exercise data from the subject P, the sensor band 2a is excellent in miniaturization, weight reduction, and power saving, and the exercise data of the subject P over a long period of time. Can be detected.

The information terminal 2b is a general smartphone, tablet terminal, PC, or the like, and includes a display unit 21, an operation unit 23, a communication unit 25b, a control unit 27b, and the like.
The display unit 21 is configured to have a display panel such as a general high-resolution color LCD, and is a display device on which comment information transmitted from the server 4 is displayed.
The operation unit 23 is an input device that includes a button switch, a touch panel, and the like.
The communication unit 25b is a wireless LAN communication device as a preferred example, establishes communication with the communication unit 25a of the sensor band 2a via the communication 2c, and transmits / receives various data including reception of exercise data. The communication unit 25 b establishes communication with the communication unit 79 of the server 4 and transmits and receives various data including exercise data and comment information via the communication 3. The control unit 27b is a CPU or a DSP and has a storage device such as a ROM or a RAM.

  According to this modification, the terminal device 2 can detect the exercise data of the subject P for a long time by the sensor band 2a, and display the comment information for the subject P on the large screen with the information terminal 2b. be able to. Accordingly, it is possible to provide the terminal device 2 that is easy to use for the subject P and can make the comment information visible in an easy-to-understand manner.

(Modification 4)
In the above-described embodiment and modification, the database engine configuring the server 4 has been described by taking a relational database as an example. However, the database engine is not limited to this database engine. It may be managed using a programmed program.

(Modification 5)
Further, it is possible to assume a form in which the analysis result of the server 4 is simply fed back to the user. Thereby, the change of the life rhythm of the subject P is automatically detected by the server 4 and the change not noticed by the subject P can be accurately grasped and notified by notifying the user of the change. .
(Modification 6)
It can also be assumed that an authorized third party, such as a family member or friend, can view the subject's information, not a mentor. Thereby, since the change of the life rhythm of the subject can be notified to a person who has been permitted in advance, the current situation of the subject can also be notified to a long-distance family.

  DESCRIPTION OF SYMBOLS 1 ... Behavior change analysis system, 2 ... Terminal device, 2a ... Sensor band, 2b ... Information terminal, 2c ... Communication, 3 ... Communication, 4 ... Server, 5 ... Communication, 8 ... External device, 20 ... Detection part, 21 ... Display unit, 23 ... operation unit, 25 ... communication unit, 25a ... communication unit, 25b ... communication unit, 27 ... control unit, 27a ... control unit, 27b ... control unit, 30 ... subject information storage unit, 33 ... storage unit, 35 ... Subject information DB, 40 ... Activity information management unit, 41 ... Processing unit, 43 ... Exercise data receiving unit, 45 ... Analyzing unit, 46 ... Behavior change information generating unit, 47 ... Storage unit, 49 ... Exercise data DB, 51 ... analysis information DB, 60 ... comment generation unit, 73 ... search information DB, 78 ... network, 79 ... communication unit, 80 ... control unit, 91 ... display unit, 93 ... operation unit, 95 ... communication unit, 96 ... notification unit 97, storage unit, 351, primary key, 3 2 ... record, 511 ... the primary key, 512 ... record, 731 ... the primary key, 733 ... record, 735 ... record.

Claims (13)

An activity information acquisition unit for acquiring the activity information of the subject;
An analysis information generating unit that generates analysis information obtained by analyzing the activity information for a predetermined period;
First analysis information generated by analyzing the activity information in a first period including at least one of the predetermined periods, and the activity in a second period including at least the predetermined period different from the first period A behavior change analysis system, comprising: a behavior change information generation unit that generates behavior change information indicating the behavior change of the subject based on second analysis information generated by analyzing information. The behavior change analysis system according to claim 1,
In the analysis information, the activity amount including at least one of the number of steps, the amount of exercise, the exercise time, and the calorie consumption in the predetermined period is totaled according to at least one of a day of the week or a time zone in a day. Behavior change analysis system characterized by being an index. The behavior change analysis system according to claim 2,
The analysis information includes a behavior pattern of the subject estimated based on the index. The behavior change analysis system according to any one of claims 1 to 3,
The behavior change analysis system is characterized in that the behavior change information includes difference information indicating a difference between the first analysis information and the second analysis information. In the behavioral change analysis system according to claim 4,
The difference information indicates a change amount of the number of steps, the amount of exercise, the exercise time, or the calorie consumption in the first analysis information and the second analysis information. In the behavioral change analysis system according to any one of claims 1 to 5,
An action change analysis system comprising: an output unit that outputs text information related to the action change of the subject and a graph indicating the action change of the subject based on the action change information. The behavior change analysis system according to any one of claims 1 to 6,
A behavior change analysis system comprising a notification unit that notifies the behavior change of the subject based on the behavior change information. The behavior change analysis system according to any one of claims 1 to 7,
A behavior change analysis system comprising a comment generation unit that generates comment information based on the behavior change information. The behavior change analysis system according to claim 8,
The comment generation unit estimates a factor causing the behavior change of the subject based on the behavior change information, and generates the comment information based on an estimation result. The behavior change analysis system according to any one of claims 1 to 9,
A biological information acquisition unit that acquires biological information of the subject,
The analysis information generation unit generates the analysis information by analyzing the biological information. The behavior change analysis system according to claim 10,
The analysis information generation unit calculates a pitch when the subject moves based on the activity information, calculates a heart rate of the subject based on the biological information, and the subject based on the pitch and the heart rate The behavior change analysis system characterized by generating the analysis information indicating the total of the activity time. Obtain activity information about the subject,
Generate analysis information that analyzes the activity information for a predetermined period,
First analysis information generated by analyzing the activity information in a first period including at least one of the predetermined periods, and the activity in a second period including at least the predetermined period different from the first period A behavior change analysis method that generates behavior change information indicating behavior change of the subject based on second analysis information generated by analyzing information. A function to obtain the activity information of the subject;
A function of generating analysis information obtained by analyzing the activity information for a predetermined period according to a predetermined period;
First analysis information generated by analyzing the activity information in a first period including at least one of the predetermined periods, and the activity in a second period including at least the predetermined period different from the first period A behavior change analysis program that causes a computer to execute a function of generating behavior change information indicating behavior change of the subject based on second analysis information generated by analyzing information.