WO2010146811A1 - Behavior suggestion device and method - Google Patents

Behavior suggestion device and method Download PDF

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Publication number
WO2010146811A1
WO2010146811A1 PCT/JP2010/003877 JP2010003877W WO2010146811A1 WO 2010146811 A1 WO2010146811 A1 WO 2010146811A1 JP 2010003877 W JP2010003877 W JP 2010003877W WO 2010146811 A1 WO2010146811 A1 WO 2010146811A1
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action
data
behavior
proposed
unit
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PCT/JP2010/003877
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French (fr)
Japanese (ja)
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田中毅
愛木清
栗山裕之
河本健
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株式会社日立製作所
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Priority to JP2009146416 priority
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Publication of WO2010146811A1 publication Critical patent/WO2010146811A1/en

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    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • A61B5/4857Indicating the phase of biorhythm

Abstract

Provided is a behavior suggestion device that infers a person's behavior on the basis of biological information such as amount of sleep, number of steps walked, and amount of exercise, and presents improvement means that improve health indicators and the like for that person. From the person's biological information and behavior history (information) obtained from sensor nodes over a long period of time, pieces of biological information (sensor data) happening at the same times of day and having the same characteristics are classified as habitual behavior, and a behavior guide generation program on a personal computer computes correlations between the times of, lengths of, and transitions between habitual behaviors and target indicator data that the user wants to improve. The main behaviors of the user are displayed chronologically; simultaneously, a display device presents optimal behavior times and lengths for improving the target indicators, and more concrete behavior examples and comments for implementing said optimal behavior times and lengths. Said optimal behavior times and lengths, behavior examples, and comments are generated using a behavior history inputted and recorded by the user in the past, and behavior history data inputted by other people.

Description

Action proposed apparatus, and method

The present invention can be attached to the human body, from the information of the sensor terminal that measures the biological information and action state indicates the character of the life estimate the human behavior, a technique for presenting the improved means.

Disturbance of the life rhythm of the night type life and lack of sleep or the like of the modern, it has been pointed out that the factors such as lifestyle-related diseases. On the other hand, now I like a pedometer or an activity meter for measuring the like human movements and the number of steps is recognized in common. As introduced in Non-Patent Document 1, called Mote (registered trademark), a sensor, a radio, a small sensor nodes equipped with a microcomputer or the like is also in practical stage. This sensor node, start only sensing and wireless communication is required timing, by the intermittent operation to reduce power consumption when the power is turned off otherwise, while working for a long time with a small internal battery, diameter 3cm and small Yes, it is easy to wear people. Therefore, in daily life, the period of activity and sleep, etc. in a person's life, that it has become possible to easily collect the information of life rhythm.

In Patent Document 1, calorie consumption and heart rate of the individual, body temperature, sleep depth, and the rhythm of life obtained by the input of record, such as fitness clubs, hospitals, body weight and other health at the same time inform the biological information concerning (display) to be by, it discloses a means to recognize the cause of the quality of the biometric information.

In Patent Document 2, when a person moves a long distance at a high speed to overseas, by detecting the human life rhythm from the acceleration sensor and an ambient light sensor (biorhythm) the deviation of the day-night rhythm, the correction jet lag the means for emitting stimulating light to the living body to disclose.

JP-9-103413 discloses JP-10-68787 discloses

"Wireless sensor network MOTE-2007" catalog, Crossbow, Inc., "2007 May 1 Search", Internet <URL: http: //www.xbow.jp/mote2dot.pdf>

Be measured movement and the number of steps by the sensor as shown in Non-Patent Document 1, it is difficult that attach multiple sensors to wear 24/7, waist and arm like a wristwatch as pedometer that find has been put into practical use. However, only the information obtained from a single sensor, sleep time and number of steps, the value of such momentum only not quantitatively evaluated, it is difficult to promote effective life improvement. For example, in the diet, only just increased the daily number of steps is not always possible to effectively lose weight.

Presented in Patent Document 1, and the index of the plurality of life rhythm, to display the biological information such as body weight at the same time, but have presented information leading to life improvement to the user, the specific improvement methods suitable for each individual It means that does not disclose.

Also in Patent Document 2 discloses a means for correcting sleep rhythms related to jet lag, it does not disclose a means of improving the health index and the like obtained from other biological information.

An object of the present invention is based on the sleep time and the number of steps, biometric information such as momentum, estimates the human behavior, to provide the health index such actions proposed device for presenting a means of improving, and the method .

To achieve the above object, in the present invention, it includes a processing unit and a storage unit, as the action proposed device for performing personal action proposed based on individual biometric information, the processing unit collects the biometric information of the individual, based on the collected biometric information, to determine the behavior of individual extracts behavioral element data, from the action element data of a predetermined period, it generates the personal habits behavior data, and these actions element data and habit behavior data, personal There based on the target index data preset to generate action guidelines individuals, based on the generated action guidelines, to provide an action proposed apparatus and method for behavioral suggestions individuals.
Further, as the action proposed apparatus of the present invention, there is provided an action proposed apparatus and method further comprising a display unit for displaying the action guidelines and proposals for action.
Furthermore, actions proposed apparatus of the present invention, the processing unit performs a correlation analysis between the habits behavior data and the target index data of a plurality of predetermined periods, the habit behavior data is highly correlated in the correlation analysis, the Action Guidelines addition to providing an action proposed apparatus and method for displaying on the display unit.

That is, in order to achieve the above object, in a preferred embodiment of the present invention, the human biological information and action history over a long period of several weeks to several months obtained by the information input means such as an acceleration sensor, at the same time zone classifies biometric information having the same characteristics as the habitual behavior of singly and habitual behavior time and customs behaviors such as length of time and the transition relation data, weight obtaining the user improved stress, life satisfaction calculates the correlation between the target metrics such as operating efficiency, and at the same time displayed in chronological order major action of the user, the length of time or time optimal action to improve the target index as an action proposed It is presented on the display device. In addition, a more concrete action examples and comments to realize the length of time and the time of its optimal behavior, behavioral history and by itself was recorded input in the past, even if the action history of the input of others use generated, it is presented.

According to the present invention, the user simultaneously their life pattern and action content for a certain period of time, display such characteristics and the time zone and the length of time behavior, and as readily occur from combinations thereof, goals and method of improving the optimal action to achieve the improvement of the indicators that can be known. In addition, in response to the feedback about what progress presented optimal behavior is can be executed, it is possible to modify the behavior.

According to the first embodiment, it is a block diagram of a system for generating an action guidelines, and proposals for action. It is a block diagram showing the structure of a program for updating the database of the system according to the first embodiment. It is a diagram illustrating a configuration example of a database to store sensor data of the system according to the first embodiment. It is a diagram for explaining a method for calculating a momentum of the system according to the first embodiment. It is a diagram illustrating a configuration example of a database that stores the momentum and the number of steps of the system according to the first embodiment. The system according to the first embodiment, is a diagram illustrating a configuration example of a behavior definition database storing conditions to determine the action from the sensor data. The system according to the first embodiment, is a diagram illustrating a configuration example of a database that stores the motion elements are determined by behavior from the sensor data. The system according to the first embodiment, and shows the process of generating habit behavior classified similar behavior daily display examples. The system according to the first embodiment, is a diagram illustrating a configuration example of a database that stores the habit behavior classified similar behavior daily. The system according to the first embodiment, is a diagram illustrating a configuration example of a database that stores the action history entered by the user. Is a diagram illustrating an example of a habit behavior display screen of the system according to the first embodiment. Analyzed by the system according to the first embodiment, the target indicator of a certain user (work efficiency), is a plot showing the correlation between resting time of the morning. Is a diagram showing an example of action guidelines display screen of the system according to the first embodiment. Is a diagram showing an example of action proposed display screen of the system according to the first embodiment. Is a diagram illustrating an example of a behavior history input screen of the system according to the first embodiment. It is a diagram illustrating a flowchart illustrating the details of the action determination processing of the system according to the first embodiment. It is a diagram illustrating a flowchart showing details of Principles generation process of the system according to the first embodiment. It is a block diagram of a sensor node of the system according to the first embodiment. It is an external view of the sensor nodes of the system according to the first embodiment. It is a diagram showing a screen display example of a sensor node according to the first embodiment. Is a diagram showing an example of an event input operation of the sensor node according to the first embodiment. According to the second embodiment, a block diagram of a system configuration for performing the analysis by the server. According to the third embodiment analyzes the server, a personal computer: a block diagram of a system configuration view the results in a browser (Personal Computer PC). Is a block diagram showing an example of the internal configuration of a PC or server in each example. Is a diagram illustrating an example of a flowchart of the processing of action proposed program in each example.

Hereinafter, in accordance with the accompanying drawings, an embodiment of the present invention. In this specification, a program executed processed in the processing unit of the PC or server such as a computer may be expressed as "parts" or "means". For example, or the like is referred to as a "Code of Conduct generating unit" and "Code of Conduct generating means" and "Code of Conduct generating program".

Figure 1 is a diagram showing a main configuration of a system for generating an action guidelines, and proposals for action of the first embodiment. In this system configuration, and it receives the sensor information is data that the user 8 is measured of a sensor node 1 worn, indicators user 8 is aimed at improving daily, for example the efficiency and results of the work, satisfaction to propose a method for improving the index representing a degree, the past target index data 310, a past behavior is determined from the sensor data by analyzing the behavioral component data 300 recorded to calculate the improvement guideline, the display device 3 such as a and outputs to the output device.

As later described, the sensor node 1 shape a person suitable for wearing, for example, wristwatch-type sensor nodes, arteries, information of a person such as motion (hereinafter, biometric information) is measured, the sensor wirelessly transmitting as data. When the recording and keep you and special events that are leaving, want to keep the time of the behavior of something, a liquid crystal display device at the touch of a button: Select the icon to be displayed on the (Liquid Crystal Device LCD), event information as a function of recording the event type and time. This will not only eliminate the need to enter the action content from the later, it is possible to prevent forgetting the exact contents and time. Also, a storage unit of the nonvolatile memory for recording the measured data in the internal. The sensor node 1 are each unique identification ID Mac: are stored (Media Access Control MAC) address is assigned. Further, only the unique identification ID in a network composed of one base station 6 (short address) can also be stored. By adding these addresses to the data by wireless transmission, it is possible to identify whether a transmitted data from any sensor node 1.

The base station 6 from the antenna 7 receives the radio wave of the radio, is transmitted in accordance with a request from PC2 connected to the contents of the sensor data transmitted from the sensor terminal. Further, when the base station 6 that constitutes one of a wireless network, performed by the communication procedure of the network subscribers, called the association and communication with the sensor node 1, to one 1 MAC addresses, one short address the allocate. The base station 6, the correspondence table of the MAC address and short address, held in the internal memory, and converts all the addresses in the MAC address added to the received data from the sensor node 1, a personal computer (Personal Computer: to send to the PC) 2. As a result, it is possible to easily identify the sensor node 1 is PC2 in the received source data.

PC2 has, for example, a general computer configuration shown in Figure 24. That is, in FIG. 24, PC shown in 2401 via the internal bus 2406, a processor central processing unit (Central Processing Unit: CPU) 2403, a storage unit main storage unit 2404, an auxiliary storage unit 2405, and further networks and the Internet 9, Yu SB of the data of the sensor data 1 is connected to the base station 6 required for incorporation into PC: a network device that interfaces (Universal Serial Bus USB) and the like are connected to each other. The display and device 3 is a display such as an LCD shown in FIG. 1, the input device 4 such as a keyboard and a mouse are connected by a suitable interface.

The PC2, a sensor data receiving program 220 for receiving and storing the sensor data from the base station 6 to the database, and various programs executed by a CPU, a sensor data 280 and a data measured by the sensor node 1, human behavior of the sensor data 280 based on, for example sleeping, walking, resting, various data are stored in a storage unit such as a definition of the threshold etc. necessary action definition data 290 to the discrimination of motion such as .
Furthermore, the PC2, compares reads the sensor data 280 in time series by using the action definition data 290, to determine the action, action determination program 230 to be stored in the database, from the sensor data in order to simplify the action determination momentum is an intermediate data to calculate, step count data 320, action determination program individual behavior is determined at 230, the action element data 300 is a database for storing the motion elements, actions of the same action defined in the same time zone in the motion elements habit behavior data 330 elements grouped, the target index data 310 is a database for storing an indication that the user 8 is wishes to improve, by analyzing the variation of past behavior element data 300 and the target index data 310, historical how to change the behavior of life from the behavior of, for example, early late No time of time Principles generator 240 to be displayed on the display device 3 is a display unit generates the information long slow, that, from the results in which Principles data Principles generated by action guidelines generation program 240, and its action guidelines past of their own, or action proposed program 250 to be displayed on the display device 3 to search for concrete action history of others from the database, the action history and comments, such as a diary that user 8 has input using the input device 4 that matches action history input program 210 to be stored in the database, the database user 8 is stored in the action history data 270, PC2 is a database that stores the behavior history and comments that you enter themselves, via a network such as an intranet or the Internet, updated by receiving data from a computer, such as other servers Equipped with a personal data update program 260 of the eye.
On the other hand, the server 5, an intranet or via the network 9 such as the Internet is connected to the PC2, includes a processing unit and the storage unit of the usual computer configuration as shown in FIG. 24, action defined in the storage unit, a data 506 and the target index data 510 and action history data 511. Action definition data 506 and the target index data 510, action definition data 290 PC2, or the same as the target index data 310, and more new content. For example, if the score of the target index is measured, such as another sensor not be added directly to the action index data 310, once stored in the target index data 510 of the server 5 to update copy it to PC2 it can. Further, when adding the contents of the action definition data 506, that the data of the server 5, each of the users to copy the behavior definition data 290, it is possible to facilitate the updating operation.

Sensor data receiving program 220 in the PC2 is by a program processing unit, functions as a biometric information receiving unit, an interface with the base station 6 which is initially connected to PC2, recognized through the dedicated driver software or the like. The rewritable ID for the sensor data reception program 220 to identify in association with one user 8 or a plurality of users, using the sensor node 1, each user is wearing PC2 holding the table. Thus, the received data, ID for identifying the user 8, or by adding a name, the sensor data 280 can be stored as biometric information of the user. Further, key operation to the sensor node 1, or having an input means of the button operation, their actions and events are user 8, i.e. to record not forget to event information, entered by operating the sensor node 1, it is efficient for receiving similarly to the sensor data. In this case, the sensor data reception program 220 stores the event information received in the action history data 270.

Now, action determination program 230 in FIG. 1, the program processing in the processing unit, by using the action definition name stored in the action definition data 290, a list of determination and detection conditions such as a threshold value corresponding thereto, the sensor data go in comparison with the time series 280 of data. As a result, for matches to the determination and detection conditions as one action element, and stores the action name, or identification ID and the time of the action, the time information in the action element data 300. Thus, the sensor data 280 is not only a collection of waveform data measured by the acceleration sensor or the like, can be converted into information that can be understood by viewing the person waveform data in the form of action. Moreover, therewith it is possible to add a time, the information that the time to act simultaneously. In other words, actions and time associated therewith, the numerical information of time, by going to record over a long period of time, changes in behavior can be realized be quantitatively evaluate the changes.

Target index data 310, an index wishes to improve the user 8, recorded over a long period of time. For example, a person in everyday life, if you wish to improve the satisfaction of the efficiency and life of work, what kind of a good or if you take the action, is the fact that what should be what kind of life problems to become. In terms of efficiency and job satisfaction, performance of work, achievement of objectives, objective evaluation, subjective evaluation and the like can be considered to be available. However, in the case of the performance and achievement of objectives is, by the industries of the work there is a case where the period that result comes out becomes a once in a few months or half a year, sufficient data can not be obtained necessary for the analysis, also may not be capturing the fine change daily becomes a problem. Also with respect to objective evaluation, it is not easy when viewed in the long run determine the evaluation on a daily basis to others.
Therefore, subjective evaluation, for example questionnaire to answer about once every day or a few hours, to obtain the results can be most easily achieved. The score is a result can be targeted metrics. Moreover, by utilizing the data of the sensor node 1, it is also possible to estimate the score of subjective evaluation. This sensor and to apply varies depending contents of evaluation, it becomes possible to generate a predictive equation using a known technique such as multiple regression analysis. The prediction result may be applied as a target index data 310. Target indicators data 310 is to score such as the satisfaction of a job like this and life is not limited. For example, the target indicators may also be measurements of living body information such as weight or blood pressure. In the case of the action index data 310 and the body weight so that it is able to support life improvement for the diet. This, as obtained in a health diagnosis, it becomes possible to apply the same healthcare purposes in other health indicators.

Principles generation program 240, the program processing in the processing unit, the time series change behavior element data 300 and the target index data 310, and generates an action guidelines analyzed for correlation. Action definition ID of the Principles behavioral elements, date and time, as action guidelines data consisting of time length, etc., are held in the storage unit, not shown. If you apply the simplest approach, when the time of a certain action is fast (for example, if attendance time is earlier), if the satisfaction score of the work of the target indicators data 510 is always raised, always the time of the action it is possible to derive the guideline action that it should be faster. The analysis method for guiding the correlation of these two values, the like Pearson product moment correlation coefficient is generally well known, it is possible to apply these known correlation analysis technique. In addition, when carrying out the present analysis, from the action element data 300, it is necessary to recognize that the that the same action beyond the day or week. In this method, for example, morning and evening commute, regular meetings, lunch, evening of jogging, practice behaviors such as sleep, to identify and event action is not a habit, is based on assessing the day-to-day of the time change. In such a multi-day, in the same time zone, and grouped the action elements of the same behavior definition, it is a group of one of them and habit behavior. This habit behavior, because it contains a plurality of motion elements, with their time and time can quantitatively evaluate such correlation analysis.

The action history input program 210, the program processing of the processing unit, what the user to easily past or current action content, via the input device 4 and displayed on the display device 3 a user interface for inputting, inputted as the action history, recorded in the action history data 270. Here, the action history input program 210 by displaying with reference to the sensor data 280 and behavioral element data 300, is recalling the historical action content to the user 8, it is possible to assist the user input 8. Moreover, the action history input program 210 sends the input action content to the server 5 connected through a network 9, can be stored in the action history data 511 is a database as well. Thus, backup and data, not only enables the input from a plurality of terminals, a knowledge of the other users lifestyle improvement, leverage action history data 511 of the server 5. In Principles generation program 240, and displays the guidance derived on the display device 3, by notifying the user 8 can prompt the lifestyle improvement of the user 8. The user 8 by enabling to select whether to transmit the action content entered in the server 5, real privacy.

Action suggestion program 250, from the program processing of the processing unit, in cooperation with the action guidelines generator 240 receives the action guidelines data held is generated, the contents of Principles, actions defined, Time from the past to display the action content that matches search the behavior history data 270 to the display device 3. The user 8 can be as knowledge of their own past actions, to recognize the specific measures of life improvement. Moreover, action proposed program 250, action history data 511 of the server 5 may in other words be referred action history of another user. As a result, since there is valid knowledge from its own past actions may not be obtained, it is possible to learn the behavior of others, prompting the life improvement.

Figure 25 is a processing action proposed program 250 executed in PC2 in the processing unit is shown in detail in the flow chart of FIG. 1, the action guidelines data generated by the action guidelines generator 240, action history data 270 and, to achieve the target pointer from the action history data 511 of the server 5, it shows a preferred example of processing for generating a more specific action proposed.

Complete Action Guidelines generator 240, Principles action proposed program 250 and data is generated holding initiates action proposal processed in the processing 251.

In the processing 252, read the Code of Conduct data generated by the Code of Conduct generating program 240. Principles data read out is the action elements in the high addictive behavior contribution ratio to achieve the target indicators, behavioral definition ID 302, date 303, the time length 306.

In process 253, actions defined in the action elements of the read action guidelines data processing 252 ID 302, date 303, a past action content of the user 8 that matches the duration 306, and retrieved from the action history data 270, reads. Further, PC2 are connected via a network 9 to the server 5, when possible reading action history data 511, reads if action history do not overlap.

In process 254, similarly to process 253 PC2 are connected via a network 9 to the server 5, you can read the action history data 511, if there is action history entered by the user other than the user 8, the behavior of Principles data element action definition ID 302, date 303, reads the action history matching the time length 306.

In process 255, process 253, the action history read in process 254, as shown for example in Principles display screen 431 shown in FIG. 14, the action history action proposed display 432 of the user 8. user behavior other than the user 8 the history is displayed separately on proposals for action display 433. Action proposed display 432, the order to be displayed on the proposals for action display 433, rearrange the order in which target indicators has improved. In this case, since it is impossible to display all of the screen size of the display device 3, and displays it sorted order. In addition, add the user interface of the scroll operation on the screen to display all. Next, FIG. 2 is a block diagram showing in detail the personal data update 260 for PC2. Personal data update program 260, action definition generation program 261, behavior evaluation program 262, behavior definition update program 263, and a target indicators update program 264.

In the figure, the behavior definition generation program 261 refers to the action history data 270 and sensor data 280 can be added modify the action definition data 290, or a new definition. The initial value of the threshold, etc., stored in the action definition data 290, even the user 8 with whom is set to true in common. However, if the guess human behavior from the sensor data, such as motion, individual differences is a problem when trying to increase the accuracy. Therefore, based on the action history data 270 is the actual action content, referring to find the corresponding sensor data 280, and generates a new determination condition can be determined with high probability, to add to the action definition data 290b that can. Further, in the initial state in the same manner it is also possible to add the action definition which is not present in the action definition data 290.

Behavioral evaluation program 262, based on the sensor data 280 is a program for generating a target indicator data 310. As above, when the target index data 310 and a subjective assessment of satisfaction, etc. work, by a technique such as multiple regression analysis, generate an approximate expression results of subjective evaluation, calculates the sensor data 280 based on can do. Behavioral evaluation program 262, in the simplest implementation, the approximate expression of the subjective evaluation, and generates a target index data 310.

Behavioral definition updates 263 reads the action definition data 506 communicates with the server 5, which is a program for updating the action definition data 290 of PC2. In this case, among the action definition data 290, the action definition generation program 261, modify, not overwrite the generated item. In other words, while the combined judgment conditions in each individual left as it is, a common determination condition as a whole is able to reflect the latest content.

Similarly target indicators update 264 reads the target index data 510 of the server 5, a program to be added to the target index data 310. If another or sensor to the server 5, the aggregation results of the questionnaire are stored, it is possible to reflect the latest data to PC2.

Figure 3 is a configuration example of the sensor data 280 shows a case where storing the data measured by 50 millisecond intervals by the triaxial acceleration sensor. Acceleration behavior and human from data, particularly the number of steps, such as also to identify exactly, is 10 times or more measurements are suitable for one second. When the sensor is measured in time 281 indicates the time the sensor node 1. Acceleration X282, acceleration Y283, acceleration z284 represents the acceleration measurement values ​​of the three axes. Digital value of the output of the acceleration sensor, or if the resolution of the digital values ​​to analog values ​​and AD conversion of the output of the acceleration sensor is 8 bits, the range of values ​​will be 0-255. If the measurement range is ± 3G ~ ± 5G about the acceleration sensor, it is sufficient to identify the movement of people. Temperature 285 represents the temperature measured by the sensor node 1. Pulse 286, the sensor node 1, only when provided with a pulse sensor of the optical type or the like, and stores the output value of the pulse waveform.

4, from the acceleration sensor data, shows a method of calculating the number of times of the zero crossing indicating the amount of waveform swings. Zero crossing count is proportional to the amount of motion, it can be regarded as a momentum. Further, from the momentum of the level, it is possible to determine sleep and exercise, rough behavior desk or the like. As a method for obtaining the simplest zero crossing times mentioned above, the accelerations in the three axes, is to convert the scalar value 1 axis. If not considering the position can be estimated momentum only scalar values. At this time, in order to remove extraneous noise components and movement of people, it is preferable to apply a band pass filter. When it is desired to suppress the detection of fine movements, it is preferable to set the threshold. For example, in FIG. 4, it detects only 12 points 0.03G acceleration scalar value 11 crosses have been counted, in estimating the human behavior from the momentum, based on the actual data, the most suitable threshold it is.

Figure 5 is a motion amount calculated from the sensor data 280, and the momentum for storing the number of steps of the data shows a configuration example of a step count data 320. Momentum data is intermediate data which is generated by the action determination program 230, by comparing the determination condition of the data and the action definition data 290, to facilitate the definition and processing. The method of calculating the movement amount is as shown in FIG. Time range of one values ​​is minimized time range of behaviors to be recognized, assuming recall can act units behavior one day, about 1 minute to 5 minutes is preferred. Date 321, data corresponding to 1 minute from the value shown indicates that it is stored in the bank. Momentum 232 stores a value calculated by the method of FIG. Number of steps 323, if Shimese the simplest way, to the acceleration of the scalar wave, to detect the periodicity by a known technique such as autocorrelation, it is possible to calculate the number of steps from the number of successive detected period.

Figure 6 shows a configuration example of a behavior definition data 290. Action definition data 290 stores a determination condition for classifying the plurality of actions, add later, modified high accuracy and the like, it is possible to respond to individual differences. Momentum, by determining relative step number data 320 facilitates setting process and conditions. Behavior definition ID291 is a unique identification ID into action defined. The action definition name 292 shows the name of the action is determined in conditions that are stored in the bank. The discrimination condition 293 can store a plurality of conditions, the threshold values. For example, not only the definition of momentum and the number of steps, other detection condition can also be specified, the action determination program 230, for each condition, the determination process at the logical OR (or configurable in logical product) . The determined one action units were referred to as motion elements. The following shows a configuration example of the determination condition. Momentum 294 indicates the condition corresponding to the momentum 322 stored momentum, the number of steps data 320. Step count 295 indicates the condition corresponding to the number of steps 323. Continuous time 296, if the match how much time the condition of the momentum 294 and the number of steps 295, indicates whether the discrimination. In other words, it is matched only if continued a certain time out. This is not seen as distinctive behavior if less resting time motion is short as about 1 minute, if you have about 10 minutes resting, it is highly likely to be recalled as a characteristic action .

Figure 7 shows by which action element data 300 that contains an action that is determined by the action determination program 230. Action element INDEX301 is a unique identification (ID) for all of the action elements. Action Definition ID302 stores an action definition ID291 corresponding to the determined conditions. Date 303 indicates the date and time in the presence of motion elements, the start date and time 304, including the end time and date 305. Duration 306 is the duration of action elements, which is the difference between the end time 305 and start time 304. As described above, the motion elements, the level and the number of steps of the momentum, characterized by date (time), when viewed after a user 8, a conceivable real storage. Also, these times as described later, and long-term analysis, makes it possible to perform the quantitative evaluation.

Figure 8 is a Action Guidelines generation program 240 in the present embodiment shows a method of performing quantitative evaluation evaluation of long-term action, i.e. habitual behavior of the person. To act element data 300, close to the time, and if the same action definition, grouping as a similar action. This is because it is a similar action across multiple days, can be referred to as a habit behavior, or life rhythm. Figure 8 shows an example of analysis of the 1-week behavioral element data 300. In the example of FIG. 8, in neighboring time it was classified groups 601-607 of the same behavior definition. It is treated with a range of about one hour before and after the close of this time.
Next, it expressed in transition diagram form a respective group as a habit behavior 608-615. Furthermore, from the context of the action elements of the habit behavior 608-615, it is possible to know the transition relation of habit behavior. Based on this transition relationship, a habit behavior 608-615 can be added to the arrow, make it easier to recognize the pattern of life. Also, from each of the number of transitions, it is possible to calculate the transition probabilities may also be known transition pattern characteristic behavior. The habit behavior 608-615 represented by a figure such as a circle, indicating the length of time of the action of, respectively, respectively in size. The duration of the habit behavior is readily calculated by averaging the duration of the action elements that make up the habit behavior. The center point of the motion elements position constituting representing the respective habit behavior, a time 616 when the three examples of behavioral elements. By the expression, look the person, not only recall the real action from color and context for each customs action, it becomes possible to quantitatively evaluate the time changes in behavior elements constituting.

Figure 9 is an example habit behavior 608-615 of FIG. 8 shows a configuration example of a habit behavior data 330 grouped action elements of the same actions defined in the row the same time zone. In Principles generation program 240, based on the habit behavior data 330, the time of action elements constituting respective habits action, a correlation analysis between the target index data 310. Habit behavior INDEX331 is a unique identification number for each of the customs action. Action definition ID332 indicates a common action definition ID to the action elements that make up the habit behavior. Start time 333 and end time 334, the start of the average of the action elements that make up the habit behavior, which is the end time. This change the display position of the habit behavior to the original. Duration 335 is the difference between the end time 334 start time 333.
Action element INDEX336 is an INDEX of the action elements that make up the habit behavior. That is, by searching for motion elements data 300 from the motion elements INDEX336, it can be read all the information behavioral elements constituting the habit behavior. Based on the readout time information, performing a correlation analysis target index data 310. Transition source INDEX337 is the information necessary to know the transition relation of habit behavior. Based on the transition source INDEX337, you can connect the arrow when displaying habit behavior. Further, the number of transition 338 is obtained by counting the number of transitions from the respective transition source, we can know the transition probability number of transitions 338 based.

Figure 10 shows an example of a configuration of action history data 270. Action history data 270, the user 8 via the action history input program 210, and stores the result input. It also stores event information user 8 inputs by button operation by the sensor node 1. By the start date and time 272 and ending date and time 273, indicating the duration of the action. Action content 274, the user 8 is directly stores the selected content from the content inputted by using the input device 4 or more candidates. By leaving the data that the user 8 has entered himself, it can be used to modify or add the action definition data 290, also can generate the action proposed contents using the input content.

Figure 11 is a display example in practice action display screen 400 Principles generation program 240 in the present embodiment to display and transmit generated and the display device 3. In this display example, for the six months of 2008, and calculates the habit behavior 403-428 divided the holiday display 402 and weekday display 401. By dividing the holidays and weekdays, for example, on weekdays to work, even in the case that the life pattern of weekdays and holidays is largely different, it is possible to make it easy to recognize their own habits behavior and life pattern when viewed from the user 8. In addition, in the holidays and weekdays, also in a similar action in the same time zone, because there is a case where entirely different meaning, lead to improve the accuracy of analysis. Each of habit behavior 403-428 are color-coded by the action legend 429. Typically, warm to high motion behavior can intuitively recognize the assign cold color to less motion behavior. The color coding and time of action, and the transition relation, the user 8 becomes conceivable real behavior shown by (...). In the above display method, the arrangement of the habit behavior 403-428 is the horizontal axis is specified by time, rather than specifying the vertical axis, arranged and optimized such that each do not overlap.

Figure 12 is, on the basis of the actual one user of the data with a one-year, shows the results of the analysis by the Code of Conduct generating program 240 in the graph 500. Each plot shows the average data of the week. The vertical axis of the graph 500 as the target index data 310, applies an indication that work efficiency of human. Here at work efficiency, people in work time, shows whether the how immersed in the work, and the results obtained in the survey of more than once (self-diagnosis) during the past of work, before and after questionnaire acceleration data by multiple regression analysis based on a constitution that the state in which devoted to work only the acceleration data can be calculated as an index. The horizontal axis of the graph 500 shows the time length of the action elements that make up the habit behavior of rest appearing at around 10:00. As seen from FIG. 12, plot is suspected to be in correlation since the arrangement close to a straight line. Further, when the actual correlation analysis, the correlation coefficient is 0.59, since the significance probability is also 0.0001 or less, it can be seen that there is a significant correlation. Therefore, as the rest time is long, has been immersed in the work, it can be seen that a high work efficiency. Thus, by analyzing for all customs action, correlation with human respective target index and customs action is obtained. The Code of Conduct generation program 240, displays the guiding principle of this correlation in the original, is proposed.

13, action proposed program 240 generates, shows a display example of Principles display screen 430 for displaying and transmitted to the display device 3. While weekday display 401 shows the same habit and behavior habits action display 400, and calculates a correlation coefficient between the respective customs action 403-416 and the target index (work efficiency in the example) by the method shown in FIG. 12, is the value of the vertical axis. As a result, it is possible and what habit behavior, improvement of the target index to recognize at a glance whether you are related. Additionally, directions for improving action, i.e. to indicate guidance at the same time, the most relevant habit behavior, add the direction of the arrow to improve target index. For example, using the results of Figure 12, to improve work efficiency and a longer time, add arrows to widen the habit behavior 408 next, when the user recognizes its own life pattern simultaneously recognize ways to improve at a glance can do. In addition, as long recognized that there is a significant correlation, in addition to customs action with the most correlation, it is also possible to display by adding the same guidelines.

14, action proposed program 250 is generated, shows a display example of action proposed display screen 431 for displaying and transmitted to the display device 3. The action proposed program 250, based on the results of the action guidelines of the Code of Conduct generation program 240 has generated action guidelines display screen 430, searches the behavior history data 270, displays the past behavior history consistent with the Code of Conduct. For example, searching habits act 408, as in the example shown in action proposed display 432 displays an actual input contents in the past. As a result, based on the self of action, it is possible to display the most appropriate action proposals. Also, if you obtained the knowledge from other than the self-action history is assumed. In action proposed display 433, action history data 511 of the server 5, i.e. from past behavior of others, by searching along the Action Guidelines, it is made possible to obtain knowledge. This is, and if the action history data 270 that was my input is small, only from the past behavior of the self is effective if sufficient improvement results can not be obtained.

Figure 15 is generated by the action history input program 210 shows a display example of action input screen 440 to be displayed by transmitting to the display device 3. In action input screen 440, for inputting efficiently past behavior to the user 8, the date and time of the momentum graph 442 specified by date and time selection 441, a time 444, and displays to the determined action element 443. By inputting while seeing the momentum and behavior elements, and can be input conveniently be forgotten and separated detailed time, since already have determined a rough action as the action element, a more detailed behavior it is possible to recall the contents and comments.

The processing behavior determining program 230 which processor in FIG. 16 is executed, the flow chart in shows in detail, the movement of people and biometric information, shows a preferred embodiment for implementing the process of determining human behavior. In process 3, if classifying human behavior in several, utilizing the fact that appear characteristic of the amount of motion, sensor data obtained by measuring the movement of a person, such as acceleration, once momentum data representing the amount of motion to convert to. Further, the periodicity of the motion data waveform to detect the number of steps, used for determination of whether the moving. The calculated momentum and the number of steps, compared with the determination condition for action definition data 290, to determine the behavior. UnTsu amount, step count data 320 is a nonvolatile, once calculated data, it is desirable to conduct determination program 230 is held be ended.

In the process 231. To begin processing the behavior determining program 230. Action determining program 230, a new data is added to the sensor data 280, starts by detecting whether updated.

In process 232, to the sensor data, in a range (time period) to perform the action determination, momentum, have already calculated step number data 320, to confirm whether it is recorded. If, if it is already calculated, the process proceeds to 235 without these calculation process, the process proceeds to 233 if it is not already calculated.

In step 233, it calculates the momentum from the sensor data 280, momentum, and records the count data 320. In this process, for example if the waveform data of the sensor data 280 is 3-axis acceleration sensor, then converted to a scalar value which is the absolute value of the vector, the zero crossing number of waveforms is counted how deflected times per unit time and momentum. Wherein the unit of time, since the movement of the unit of several seconds not considered actions, about 1 minute is desired. In this process, the intermediately generated scalar value, over a band pass filter, it is desirable to remove the extraneous frequency components and movement of people.

In process 234, from the data obtained by measuring the motion of the human sensor data 280, it calculates the number of steps. Again similarly to the processing 233, calculates the scalar value once it or FFT (frequency analysis) by known means such as self-correlation analysis to detect periodicity, if there is periodicity, per unit time cycle counts the number of subsequently a number of steps. The calculated number of steps momentum, and records the count data 230.

In process 235, momentum, with reference to the step count data 230, the momentum, the value of the number of steps, compared the discrimination conditions contained in each action definition data 290.

In process 236, the result of matching in the processing 235, the name and ID of the action definition, start time, recording information, such as end time action element data 300.

And it ends the process of behavior determining program 231 in the processing 237. Action determination program 231, the sensor data 280 is executed each time it is added.

17, the process is shown in detail in the flowchart of Action Guidelines generation program 240, and action element data 300, from the target index data 310, suitable for processing to generate optimal action guidelines to improve the target indicators It shows an example.

In the process 241, to start the process of the Code of Conduct generating program 240.

In the processing 242, in generating the action guidelines, set the required conditions. For example, the range to be analyzed, such as day of the week specified performed. This is either a fixed value determined in advance by a program, a value which the user 8 is input via the input device 4.

In process 243, the action element data 300, reads data in the range specified by the processing 242, reference.

In process 244, it generates the habit behavior data 330 representing the human behavior patterns. Unit period for generating one habit behavior data applies the period set by the processing 242. The process 244, as shown in FIG. 8, in this unit period, regardless of the date, grouping the action elements of the same behavior definition close in time to one of habit behavior data. These habits action adds a habit behavior ID is an identification ID. In proximity of setting this time varies depending granularity of behavior patterns wants to see the user 8, 1 to 2 hours in any case be desirable. However, the customs actions only appear once or twice a day of sleep, such as, for example, in order to prevent the connection of action is divided in rolling over, etc., it is suitable for this time of about 5 hours. Taking the average of the action elements that make up the habit behavior grouped, to record the start time and end time of the habit behavior. In addition, to record the ID of the action elements that make up. Moreover the connection of the time series of motion elements, to record the habit behavior immediately before reaching the certain habits act as a transition source, for recording the number of transitions from the respective transition source. The information of the customs action, be recorded in the habit behavior data 330.

In process 245, the target index data in the analytical range readout reference to all, further reads the habit behavior data corresponding to the date and time of the target index data. For example, if the target index data is every weekday of work efficiency in 2008, as well as also compared reading habits behavior of 2008 from habit behavior data 330. In order to analyze, the every weekday of the action elements that correspond to the target index, read from each of habit behavior. Here, in the case where there are a plurality of action elements on the same day, taking the average of the time and one of the action elements. Then, the time and duration of each weekday motion elements contained in each habit behavior, a transition relation or the like, the every weekday target variables correlation analysis, the correlation coefficient is calculated habits behavior and target variables.

In step 246, displaying associated habits action on the display device 3 as can be seen high correlation coefficient sequence.

In process 247, the high addictive behaviors highest correlation coefficient, Principles for improving the target variable, for example, faster time slows, lengthening, displays an instruction, such as shortening.

To complete the processing of the Code of Conduct generating program 240 in the processing 248.

Figure 18 shows an example of the configuration of the sensor node 1 in the present embodiment. The sensor node 1 includes a wireless communication unit 106 having an antenna 115, an acceleration sensor 102, the pulse sensor 103, a temperature sensor 104, a microcomputer 120, and functions as a timer for triggering at regular intervals to the microcomputer 120 further time information real-time clock for generating: a (Real time clock RTC) 105, storage 140 is a nonvolatile rewritable storage medium, e EP ROM (Electrically Erasable and Programmable Read Only memory: EEPROM) 160, character Ya waveform, and LCD101 that displays a graph or the like, a plurality of switches 110 and 111 can be triggered against a microcomputer 120, a trigger microcomputer 120 detects a USB connection from the external device to the terminal 112 over, the An external power source detecting unit 108 to output the status to the microcomputer 120, the USB communication unit 107 for transferring the data transmitted by the serial communication with the microcomputer 120 to the external device USB connection, a secondary battery 26, a personal computer a charging / power feeding circuit unit 109 supplies power to the sensor node 1 instead via a USB connection to an external device to charge the secondary battery 113 in the power supplied or the secondary battery 113, etc., USB cable It is composed of a terminal 25 for connecting.

The EEPROM 160, as shown in FIG. 18, from which to select a region 152 for recording the date and time of an event, the event record table 150 that includes a region 153 for recording the event ID is an identification code for classifying an event, the event ID an area 155 for recording the event ID is an item to be, when selecting the event ID, comprises an event list table 154 containing the corresponding area 156 for recording the icon data for displaying an icon image to LCD101 to . For event list table 154 is rewritable, it sets the frequently used any event by the user using the sensor node 1, can be recorded.

The event record table 150 not only date and time the event occurred, by adding the event ID, describing the contents of the event with a simple operation, the contents when viewing the event information can be easily recall later.

As shown in the figure, the storage 140 includes a data table 141 for recording the sensed data. Data recorded in the data table 141 is separated by a variable length for each packet that is transmitted from the wireless communication unit 16. Thus, by a wireless or wired transmittable without processing directly data one packet worth of data read out from the storage 140, it is possible to reduce processing.

One packet is recorded at the position of the corresponding address 142, area 143 for recording the flag is also included in the data table 141. Address 142 are uniquely assigned to the data table within 141, storage 140 by referring to the address contained by the microcomputer 100 reads in serial communication or the write command, an arbitrary position recorded in the storage 160 data can be written or read, the.

Flag 143 is when the data is transmitted wirelessly, a 1 if the A all successfully transmitted, write 0 if it contains data for transmission failure. In other words, when reading the packet storage 160 later, it is possible to determine whether including the untransmitted data, only the unsent data efficiently and allows reading without leaving.

The microcomputer 120 includes a CPU 121 that performs arithmetic processing, and ROM130 for recording a program 131 running on CPU 121, a RAM127 temporarily record such data, real-time clock 105 and the storage 140 and EEPROM160 the LCD11 and the acceleration sensor 12 a temperature sensor 14 and pulse sensor 13 and the I / O port 125 to the serial communication unit 122 and 126, the input digital signal or an output, for transmitting and receiving radio communication unit 16 and the signal at USB communication unit 17 and the digital signal When configured to include an interrupt controller 123,124,128 to interrupt the signal from the outside to the CPU121 running program 131 as a trigger.

The program 131 recorded in advance in the ROM 130, including connection to the sensing program 132 switching program 133 and event recording program 134. Process described in the event recording program 134 is executed by CPU 121, and starts processing the signal from the switch 110 and 111 as a trigger, it acquires the time information and communicate via real-time clock 15 and the serial communication unit 102 , it is recorded in the date and time 152 of the event record table 150 of EEPROM160. Further, it is possible to further the operation of switches 110 and 111, by selecting from the event list table 154 to pre-programmed event ID155 to classify an event corresponding to the time information, is recorded in the event ID 153. To assist the operation by the user, it displays an icon 156 corresponding to the event ID155 the LCD 101.

Process described in the sensing program 131 is executed by CPU 121, as a trigger signal of the real-time clock 105, takes in the acceleration sensor 102 through the serial communication unit 122, the data sensed by the temperature sensor 104 and the pulse sensor 103 in RAM127 the data taken into the RAM127 controls the wireless communication unit 106 wirelessly transmits a predetermined gateway further records written to storage 160.

Also process described in connection switching program 133 also runs at CPU 121, transmitted signals from the external power source detecting unit 108 to start the wired communication as a trigger, are recorded in the storage 140, and to the outside by wireless or wired communication It reads the data not (untransmitted data), and sends to the USB communication unit 107, wired transmitting from the USB communication unit 107 to the external device.

Real-time clock 105 may generate an interrupt signal to the interrupt control unit 123 of the microcomputer 120 at a constant period. This period can be changed by the serial communication command. This interrupt signal, the processing of sensing described in the microcomputer 120 in the sensing program 131, without being affected by the execution status of other processing can be started at a constant period.

External power detection unit 108 detects that the power terminal 112 is connected. In other words, it detects the connection with the external device via a USB with power. When the connection is detected, the external power source detecting unit 108 generates an interrupt signal to the interrupt controller 124 of the microcomputer 120, to the I / O port 125 for outputting a first digital signal. Also it generates an interrupt signal when it detects the disconnection, to the I / O port 125 for outputting a first digital signal. That is, the microcomputer 120 immediately detects the change in the connection to the terminal 112, it starts a USB communication via the USB communication unit 107, or stop.

The signal of the serial communication with the USB communication unit 107 microcomputer 120, converts the USB standard signal through data line of the USB terminal 112 (transmission, reception). Therefore, the control of the microcomputer 120, converts only the data to be transmitted to the external device only transmits the USB communication unit 107 in serial communication, automatically the data of the USB standard can be transmitted to the external device. Further, since the power supply of the USB communication unit 107 is supplied only from the external device via the power supply terminal 112, it does not consume extra power during USB unconnected.

Figure 19 shows the external appearance of the sensor node 1 according to the configuration of the present embodiment. 19, terminal 112 for USB connection of the sensor node 1, since the side when viewed from the mounting surface with a pulse sensor 103, in a wired communication and charging can also be worn by the user at all times, the sensing characterized in that it does not interfere. Below, the individual will be described.

The sensor node 1, the band 116 can be worn on the wrist similarly to and in association with both ends, a typical wristwatch. As can be seen from the structure of the band 116 in FIG. 19, a surface having a pulse sensor 103 when wearing contact with the skin of the user. The pulse sensor 103 is a known optical measurement method, an infrared irradiating the living body surface, to enable estimating pulse rate from the change in the reflected light of the vessel due to pulsation. That is, the pulse sensor 103 is essential that in contact with the skin of the user.

Terminal 112 is in a different side from the mounting surface with a pulse sensor 103. Terminal 112 corresponds to the USB cable, a power supply terminal, a data terminal (transmission, reception) by connecting to an external device corresponding to the USB, communication is possible and the power supply.

Further, the LCD 101, it is possible to display time and battery level user can be seen at all times, the wireless communication state or the like. Menu is displayed on the LCD 101, by operating the switch 110 and 111, CPU 121 shown in FIG. 18, using the internal functions of the microcomputer 120 of the various programs in the interrupt control unit 128, ROM 130, Ya distance sensing the settings such as the radio channel the user is capable of changing.

Figure 20 shows the display of the LCD101 sensor node 1. In Figure 9, the user 8 during mounting of the sensor node 1, the waveform display 166 of the sensing data, time information 164, the radio wave state 161, remaining battery level 162, it is possible to check the remaining memory 163.

Radio wave state 161, that is, the results of the radio transmission. Also, it does not appear if you do not at all use the wireless communication.

Battery level 162, displays the voltage of the secondary battery 113. Thus, the user 8 can know the timing required to charge the USB connection.

Remaining memory capacity 163 indicates the amount of sensor data recordable unsent storage 140, user 3 in an environment that can not be wireless or wired communication, estimates the time that can record sensor data not yet transmitted to the storage 140 can do.

Figure 21 is press switch 110 and 111, select the event, when running the process of recording, a diagram illustrating an example of a transition of the display of the LCD 101. In the display example of FIG. 21, the selection of an event, from doing in record selection icon only, even when busy daily life, a short time readily selected, and wherein the recording are possible. For also controls the display of the switching, can of course be implemented by the internal functions of the microcomputer 120 in FIG. 18.

In the display state of FIG. 20, pressing the switch 110 is switched to the display 167. The point as an event occurrence time, and acquires the time information from the real-time clock 105. Event ID event is unselected ID: 0 and when, if the event ID of 0 is displayed 167. Especially or when there is no need to classify, such as when there is no time that the selected record this.

Further pressing the switch 110, an icon corresponding to the next event ID is displayed. For example, the display 168 is an icon indicating a meal, and 1 event ID.

Further pressing the switch 110, sequentially switched to display 169, display 170. As an example, the display 169 is traveling by car, the display 170 is an icon indicating that the running. In a state where they display 167-170 are displayed on the LCD 101, by pressing the switch 111, it can be recorded in EEPROM160 the event ID (0 ~ 3) corresponding to the display.

Figure 22 is a diagram showing the system configuration of the second embodiment. In the configuration of this embodiment, unlike the embodiment of FIG. 1, a sensor data receiving program 501, an action determination program 502, the sensor data 507, and action definition data 506, and action element data 509, the target metrics and 510, and action history data 511, and action definition generation program 504, the guiding principle generation program 505, and action proposed program 514, momentum, and step count data 512, the habit behavior data 513, rather than PC2, provided to the server 5 . Also in the server 5 includes a sensor data receiving program 501 for receiving data directly from a base station connected to the network 9, a function of the WEB server, a WEB display generation program 503 for generating a display screen of the WEB browser. These programs, processor such as a server 5 inside the CPU. The PC2, characterized in that it comprises guiding principle generator 505, the generated results of behavioral proposed program 514, the action guidelines / suggestions display program 350 to display and transmit to the display device 3 and received via the network 9 to. Incidentally, behavioral proposed program 514 has a function similar to that of the action proposed program 250 shown in FIG. 25.

PC2 includes a sensor data receiving program 220 stored in the database to receive data from the base station 6, the action history input for storing the action history and comments such as diary user 8 inputs using the input device 4 into the database includes a program 210, the result of the action guidelines generator 505 and action proposed program 514 of the server 5 receives, via the network 9, the action guidelines / suggestions display program to be displayed on the display device 3. Sensor data reception program 220 stores the sensor data transmitted from the base station 6, the sensor data 507 in the server 5 via the network 9. The action history input program 210, the result of the user 8 is input via the input device 4 via the network 9 and stores it in the action history data 511. That is, to PC2 does not hold a database. As a result, if the PC connected to the network 9, without limitation, to collect sensor data from anywhere, and analyzed in the server 5, to allow the display to receive the results. Moreover, action determination program 502 and action definition program 504, Principles generation program 505, in the case where the processing of action proposed program 514 can not be treated with complex PC2 also because it is often less constrained in the server 5 the size and power consumption at high throughput while low cost, it is possible to complete in a short time process.

Action determination program 502, the momentum from Similarly the sensor data 507 and action determination program 230 in FIG. 1, to calculate the step count data 512, stored in the action definition data 506, and action name, determination threshold such that the corresponding with a list of conditions, momentum, will determine the number of steps data 512 in time series. Consequently, as the action element of the one that matches the judgment condition, and stores the action name, or identification ID and the time of the action, the time information in the action element data 509.

Target index data 510, an index wishes to improve the user 8, recorded over a long period of time. Unlike target index data 310 in FIG. 1, the results or measured by other sensors, also the score of such results of work input via another PC can be stored.

Action Guidelines generator 505, generates a habit behavior data 513 similarly to Principles generation program 240 of FIG. 1, the time-series change in the behavioral component data 509 and the target index data 310 included in each habit behavior, the correlation between analysis, and to generate an optimal action guidelines to user 8. Unlike Principles generation program 240, Principles generation program 505 may be initiated by a request from the Action Guidelines / suggestions display program 350 of the PC2. The resulting results are transmitted to the Action Guidelines / suggestions display program 350, it is possible the user 8 to browse the results using PC2.

Similarly, actions proposed program 514, or comply with the requirements of the Code of Conduct / proposed display program 350 is started at the same time as action guidelines generator 505 is completed, and sends the result to the Action Guidelines / suggestions display program 350, the user 8 PC2 in will be able to browse. The other processing is similar to the action proposed program 250 of FIG.

Action Definition generator 504, similarly to the behavior definition generation program 261 in FIG. 2, with reference to the action history data 511 and sensor data 507 can be added modify the action definition data 290, or a new definition. Also, unlike the action definition generation program 261, stored in the sensor data 507 and action history data 511, it is possible to carry out analysis processing by using the data of other users other than the user 8, a precision determination conditions reduction and, it is possible to diversification of the definition.

Figure 23 is a diagram showing a system of a third embodiment, the configuration performed instead to dispense action guidelines / suggestions program 350 shown in PC2 in FIG. 22, the general purpose of the WEB browser 520, the same processing having. According to this embodiment, by using the WEB browser 520, there is no need to provide a dedicated program to PC, anywhere, many PC or mobile phone with a similar function, easily act from a terminal or the like it is possible to browse the guidelines / suggestions result. The base station 16 is different from the base station 6 shown in FIG. 1 and FIG. 22, connected to the network 9 directly, it is possible to send the sensor data received by the server 5.
The server 5, by providing the sensor data reception program 220 and the same sensor data program 501 in FIG. 1, it is possible to store the data transmitted over the network 9 from the base station 16 to the sensor data 507. That is, a plurality installed base station 16 to the office or home, if connected to the network 9, connecting it with personal PC or the like, there is no need to manage, can easily collect sensor data. WEB input and output generation program of the server 5 is provided with a function of the WEB server, the display contents Action Guidelines generation program 505 and actions proposed program 514 has generated, in accordance with a request from the WEB browser 520, and sends it to the WEB browser 520. WEB browser 520 displays the display content received on the display device 3. Further, WEB output generator 503, an action input screen 440 generated by the action history input program 512, and transmitted according to the request of the WEB browser 520, the WEB browser 520 displays on the display device 3. Moreover, the action history that the user 8 is input via the input device 4 transmits the WEB browser 520 to the WEB output generator 503, via the action history input program 512 may be stored in the action history data 511.

The present invention can be attached to the human body, from the information of the sensor terminal that measures the biological information and action state indicates the character of the life estimate the human behavior, useful as a technique for presenting the improved means high.

1 ... sensor node 2 ... personal computer 7 ... antenna 8 ... user 9 ... network 11 ... acceleration scalar value 12 ... intersection 105 ... real-time clock (RTC)
110, 111 ... Switch 112 ... terminal 113 ... secondary battery 114 ... ground 115 ... antenna 120 ... microcomputer)
121 ... computing unit (CPU)
127 ... volatile storage unit (RAM)
130 ... non-volatile storage unit (ROM)
132 ... sensing program 133 ... connection switching program 134 ... event recording program 141 ... packet recording table 153 ... event record table 154 ... event list table 160 ... electrically rewritable nonvolatile storage unit (EEPROM)
161 ... radio communication status 162 ... battery indication 163 ... memory remaining display 164 ... time display 165 ... sensing status 166 ... sensor waveform display 167-170 ... event display 231 to 237,241 to 248 ... processing 401 ... weekdays habit action display 402 ... holiday habits action display 429 ... action legend 442 ... momentum 443 ... action element 444 ... time 445 ... action history 403 to 428,608 to 615 ... habit behavior 601-607 ... group of similar action elements.

Claims (20)

  1. Comprising a processing unit and a storage unit, individual biometric information, a behavior proposed apparatus that performs actions proposed individual,
    Wherein the processing unit,
    Based on the collected the personal biometric information, and an action element data to determine the behavior of the individual,
    Wherein the action element data of a predetermined period, generates the habit behavior data of said individual,
    Wherein the action element data and the habit behavior data, based on the target index data of said individual, to produce an action guidelines of the individual,
    Based on the generated the action guidelines, performs an action proposed for the personal,
    Action proposed apparatus, characterized in that.
  2. A behavior proposed apparatus according to claim 1,
    Further comprising the action guidelines and a display unit for displaying the action proposal,
    Action proposed apparatus, characterized in that.
  3. A behavior proposed apparatus according to claim 2,
    Wherein the processing unit,
    From the sensor corresponding to the individual, the biological information includes a sensor data receiving unit for collecting the sensor data reception unit stores the behavioral elements data extracted from the biometric information in the storage unit,
    Action proposed apparatus, characterized in that.
  4. A behavior proposed device according to claim 3,
    Wherein the processing unit, based on the target index data and the action data elements the habit behavior data has action guidelines generation unit which generates the action guidelines,
    The Action Guidelines generating unit displays the generated the action guidelines on the display unit,
    Action proposed apparatus, characterized in that.
  5. A behavior proposed apparatus according to claim 4,
    Wherein the processing unit, based the action guidelines, has an action suggestion unit which outputs the action proposed to display the action proposed in the display unit,
    Action proposed apparatus, characterized in that.
  6. A behavior proposed apparatus according to claim 5,
    Wherein the processing unit includes an action history input unit for inputting the action history of the individual,
    The action history input unit stores the action history entered in the storage unit,
    Action proposed apparatus, characterized in that.
  7. A behavior proposed device according to claim 6,
    The action suggestion unit, based on the action history accumulated with the Principles, and outputs the action proposal,
    Action proposed apparatus, characterized in that.
  8. A behavior proposed apparatus according to claim 4,
    The Action Guidelines generating unit, based on said action element data of a predetermined time period, said generating habits behavior data and holds the generated the habit behavior data in the storage unit,
    Action proposed apparatus, characterized in that.
  9. A behavior proposed apparatus according to claim 8,
    The Action Guidelines generating unit performs a correlation analysis between the habit behavior data held in the plurality of the predetermined period and the target index data, and displays the correlation analysis results on the display unit,
    Action proposed apparatus, characterized in that.
  10. A behavior proposed apparatus according to claim 9,
    The Action Guidelines generator, the habit behavior data is highly correlated in the correlation analysis, in addition to the action guidelines displayed on the display unit,
    Action proposed apparatus, characterized in that.
  11. A display unit and the processing unit and the storage unit, individual biometric information, a behavior proposed method in a system for the action proposed individual,
    Wherein the processing unit,
    Based on the collected the personal biometric information, and extracts an action element data by discriminating the behavior of the individual,
    Wherein the action element data of a predetermined period, generates the habit behavior data of said individual,
    Wherein the action element data and the habit behavior data, based on the target index data of said individual, to produce an action guidelines of the individual,
    Based on the generated the action guidelines, performs an action proposed for the personal,
    Action the proposed method, characterized in that.
  12. A behavior proposed method of claim 11,
    Wherein the processing unit displays the action guidelines and the action proposed in the display unit,
    Action the proposed method, characterized in that.
  13. A behavior proposed method of claim 12,
    Wherein the processing unit,
    From the sensor corresponding to the individual, and collecting the biometric information,
    The action element data extracted from the collected the biological information stored in the storage unit,
    Action the proposed method, characterized in that.
  14. A behavior proposed method of claim 13,
    Wherein the processing unit,
    Based on said target index data and the action element data and the habit behavior data, to generate the action guidelines,
    To display the generated the Code of Conduct on the display unit,
    Action the proposed method, characterized in that.
  15. A behavior proposed method of claim 14,
    Wherein the processing unit,
    Storing the inputted action history data of the individuals were in the storage unit,
    Based on the memorized the action history data the action guidelines displayed on the display unit outputs the action proposal,
    Action the proposed method, characterized in that.
  16. A behavior proposed method of claim 14,
    Wherein the processing unit, based on said action element data of a predetermined period, generates the habit behavior data,
    Holds the generated the habit behavior data in the storage unit,
    Action the proposed method, characterized in that.
  17. A behavior proposed method of claim 16,
    The processing section may perform the said habit behavior data of a plurality of the predetermined period correlation analysis between the target index data, and displays the correlation analysis results on the display unit,
    Action the proposed method, characterized in that.
  18. A behavior proposed method of claim 17,
    The processing unit, the habit behavior data is highly correlated in the correlation analysis, in addition to the action guidelines displayed on the display unit,
    Action the proposed method, characterized in that.
  19. A behavior proposed method of claim 15,
    Wherein the processing unit,
    And input others action history data, and the stored the action history data, on the basis of the action guidelines, actions proposed method and outputting the action proposed.
  20. A behavior proposed method of claim 19,
    Wherein the processing unit,
    Consistent with the action guidelines, the others of action history data, or search the stored the action history data, actions proposed method and displaying on the display unit the matched action history as the action proposed.
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