JP2019153295A - Self-management support system - Google Patents

Abstract

To provide a self-management support system which notifies an object person himself/herself of deviation from a reference state in a daily activity pattern of the object pattern.SOLUTION: A system 1 executes processing for: creating and storing time-series data about the number of times of motion of an object person for each day in units of first unit time according to measurement data from a human sensor 21 installed inside a dwelling 20 of the object person; on the basis of the time-series data for a preprocessing period, creating confirmation data capable of specifying a point at which the object person is not in a reference state and then transmitting the same to a terminal of the object person; correcting the time-series data on the basis of confirmed data that the point at which the object person is not in a reference state has been confirmed with respect to the confirmation data and then deriving a reference behavior pattern which indicates a reference state of an activity pattern of the object person; and deriving an evaluated behavior pattern on the basis of the time-series data for an evaluation period and deriving a degree of deviation of the evaluated behavior pattern from the reference behavior pattern to notify the object person of the same.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a self-management support system that notifies a target person of a deviation from a standard state in a daily activity pattern of the target person, and more particularly to a self-management support system for a target person living alone.

  A monitoring system and monitoring service that remotely detects safety information such as the daily living conditions and health status of the target person such as the elderly, and notifies a family other than the target person, in particular a separate family, a nursing facility, a local government, etc. Have been proposed (for example, Patent Document 1 below).

JP 2017-168098 A

  In the monitoring system and the monitoring service described above, the elderly who have a chronic problem or are likely to occur suddenly or who are worried about their health condition, etc., in daily life For example, healthy young people in their teens to 50s and middle-aged people are not assumed as targets.

  However, even if you are a healthy young or middle-aged person, if you live alone, your daily life becomes irregular due to factors such as busy work, and you have enough sleep, meals, exercise etc. Otherwise, unhealthy life may be forced for a long time, and the person himself / herself may not readily notice the change in the living situation. Even if it is noticed, it is difficult to objectively grasp the degree. Furthermore, since there are no living people, there is no opportunity for the change to be pointed out by others, and there is a risk that the gradual deterioration of the health condition will become serious without knowing.

  The present invention has been made in view of the above-mentioned problems, and an object thereof is to provide a self-management support system that notifies the subject person of deviation from the standard state in the daily activity pattern of the subject person. It is in.

In order to achieve the above object, a self-management support system according to the present invention is a self-management support system that notifies the target person of a deviation from a standard state in the daily activity pattern of the target person, and includes a data transmission / reception unit , A data storage unit, and an arithmetic processing unit, the arithmetic processing unit,
Measurement data of the number of motions of the subject sensed by the motion sensor from a motion sensor that senses the motion of a person installed at one or more predetermined positions in the residence of the subject, the data transmission / reception unit A first data storage process for sequentially receiving at a predetermined reception timing via the first time series data of a predetermined first unit time step every day of the number of operations, and storing the first time series data in the data storage unit;
Based on the first time-series data of the preprocessing period over a plurality of days, first confirmation data is generated that can identify a place where the subject is judged not to be in a standard state, collectively or divided into a plurality of times. A first confirmation data transmission process for transmitting the first confirmation data to the predetermined confirmation terminal used by the subject via the data transmission / reception unit;
When receiving the input of the first confirmed data from the confirmation terminal via the data transmitter / receiver, the location where the subject determined that the subject is not in the standard state with respect to the first confirmation data is received, If the first time-series data is corrected based on 1 confirmed data, and the input of the first confirmed data is not received from the confirmation terminal based on the corrected first time-series data, A first standard action pattern indicating a first standard state of the activity pattern of the target person is derived based on the first time-series data of the preprocessing period that was initially created, and is stored in the data storage unit. 1 standard state derivation process;
Based on the first time-series data of a predetermined evaluation period of one day or a plurality of days, a first evaluated action pattern to be evaluated for the activity pattern of the target person is derived, and the first evaluated action pattern A first divergence generation process for deriving a predetermined first divergence from the first standard action pattern of
First output data including the first divergence degree is created, the first output data is transmitted to a predetermined first user terminal via the data transmission / reception unit, and the first divergence degree is determined as the target person. First output processing to notify to,
It is the first feature that it is configured to execute.

  According to the self-management support system of the first feature described above, the number of motions perceived by the subject per unit time within the perceivable range of human motion at the location where the motion sensor is installed is determined. As an index indicating the degree of activity, the deviation from the standard state in the daily activity pattern of the subject can be presented to the subject. Specifically, the arithmetic processing unit transmits the first confirmation data to the confirmation terminal by the first confirmation data transmission process, so that the first time-series data that is the basis of the first standard action pattern is transmitted. When there is a portion that is determined not to be in the standard state by the subject person, the first time-series data can be corrected based on the first confirmed data by receiving the input of the first confirmed data. Therefore, it is possible to accurately create the first standard action pattern indicating the standard state in the daily activity pattern of the subject by excluding the portion judged not to be the standard state by the subject himself, and for a predetermined evaluation period The target person can be notified of the deviation from the first standard action pattern of the first evaluated action pattern that indicates the activity pattern of the target person. Here, if there is no feedback by the subject person of the output of the first confirmation data and the input of the first confirmed data, in the pre-processing period over a plurality of days from which the first standard behavior pattern is derived, If the activity pattern has changed from the standard state, the subject does not accurately derive the divergence of the first evaluated behavior pattern from the first standard behavior pattern, and the subject accurately changes his / her activity pattern. However, according to the self-management support system of the first feature, the target can accurately recognize the change of his / her activity pattern because the configuration capable of the feedback is provided. Can do.

  Furthermore, in the self-management support system according to the first feature, the first standard action pattern is a human action at a location where the human sensor is installed in a predetermined time zone of one or more of each day of the preprocessing period. A first total activity time obtained by summing, within the pre-processing period, a first activity time in which the number of operations per unit time of the subject within the perceivable range is equal to or greater than a predetermined reference value, 1st average activity amount which remove | divided 1st total activity amount which is the sum total of the said operation | movement number in 1 total activity time, and the said 1st to-be-evaluated action pattern in the said 1 or more predetermined time slot | zone of the said evaluation period A second total activity that is a second activity time in which the number of operations per unit time of the subject within the perceivable range is equal to or greater than the reference value, and is a total of the number of operations in the second activity time. Including the second average activity amount minus the amount It is preferred.

  The first standard action pattern and the first evaluated action pattern are each represented by a statistical value called an average activity amount, so that it is easy to derive the comparison and the first divergence degree of both action patterns, and the target It becomes easy for the person to understand the comparison result of both behavior patterns.

  Furthermore, in the self-management support system according to the first feature, the first standard action pattern is within the perceivable range of human motion at the location where the human sensor is installed on each day of the preprocessing period. Including a predetermined first statistic value for the entire period of the pre-processing period with respect to a daily stay start time and a daily stay end time calculated based on the number of movements of the subject per first unit time, It is preferable that the evaluated behavior pattern includes the daily stay start time and the daily stay end time in the evaluation period.

  The first standard action pattern and the first evaluated action pattern are represented by a stay start time and a stay end time, respectively, thereby facilitating the comparison and first divergence of both action patterns, The target person can easily understand the comparison results of both behavior patterns.

  Furthermore, in the self-management support system according to the first feature, the first standard action pattern is within the perceivable range of human motion at the location where the human sensor is installed on each day of the preprocessing period. Including a predetermined second statistic value in the whole pre-processing period with respect to the number of daily usages calculated based on the number of operations per first unit time of the subject, and the first evaluated behavior pattern is It is preferable that the number of daily usages in the evaluation period is included.

  The first standard action pattern and the first evaluated action pattern are expressed based on the number of times of use, respectively, so that it becomes easy to derive the contrast and the first divergence degree of both action patterns, It becomes easier to understand the comparison results of both behavior patterns.

  Furthermore, the self-management support system of the first feature is a human sensor in which the human sensor is installed in at least one of a living room, a toilet, and a bedroom in the target person's residence. The first time series data is preferably created for each installation location of the human sensor. Thereby, the target person can objectively recognize the deviation from the standard state in his daily activity pattern for each location where the human sensor is installed.

  Specifically, when the human sensor is installed in the living room, the target person can objectively recognize the deviation from the standard state in the daily activity pattern in his / her living room. In addition, when the presence sensor is installed in the toilet, the subject objectively observes the deviation from the standard state in the daily activity pattern of his / her toilet, that is, the change in the health condition such as the frequency of the toilet. Can be recognized. When the human sensor is installed in the bedroom, the subject can objectively recognize the deviation from the standard state in the daily activity pattern related to his / her sleep, that is, the change in the sleep time.

  Furthermore, in the self-management support system of the first feature, it is preferable that the predetermined first unit time is 1 minute or more and 60 minutes or less.

  Furthermore, in the self-management support system according to the first feature, the first standard action pattern and the first evaluated action pattern are time series having a coarse or fine temporal granularity as the temporal granularity of the first time series data. Preferably it is data. Thereby, the target person can compare both action patterns in time series, and can grasp the degree of divergence (first divergence degree) of both action patterns on the time axis.

  Furthermore, in the self-management support system of the first feature, the arithmetic processing unit further includes action pattern comparison data for comparing and displaying the first standard action pattern and the first evaluated action pattern in a predetermined display format. Preferably, the first output data is generated as part or all of the first output data.

In addition to the first feature described above, the self-management support system according to the present invention further includes:
The human body information of the subject from a human body information sensor that can be worn on the human body to detect human body information including at least one of one or more biological information and acceleration information of the subject by being worn by the subject. At a predetermined reception timing via the data transmission / reception unit, and a predetermined value for one measurement value for each first unit time or a plurality of measurement values for each first unit time for each type of human body information. Based on the third statistic value, the second time series data of the measurement value or the third statistic value in the first unit time step for each day is created for each type of the human body information and stored in the data storage unit A second data storage process,
Based on the second time-series data of the pre-processing period, a second confirmation data is generated that can identify a place where the target person judges not to be in a standard state in a batch or a plurality of times, and the data A second confirmation data transmission process for transmitting the second confirmation data to the confirmation terminal via a transceiver;
When the second confirmed data is received from the confirmation terminal via the data transmitting / receiving unit, the second confirmed data can be identified where the subject has determined that the subject is not in the standard state. 2 If the second time series data is corrected based on the confirmed data, based on the corrected second time series data, and the input of the second confirmed data is not received from the confirmation terminal, A second standard action pattern indicating a second standard state of the activity pattern of the target person is derived based on the second time-series data of the preprocessing period that was initially created, and is stored in the data storage unit. 2 standard state derivation processing;
Based on the second time-series data of the evaluation period, a second evaluated action pattern that is an evaluation target of the activity pattern of the target person is derived, and the second standard action pattern of the second evaluated action pattern A second divergence creation process for deriving a predetermined second divergence from
The second output data including the second divergence degree is generated, the second output data is transmitted to the first user terminal via the data transmission / reception unit, and the second divergence degree is transmitted to the target person. A second output process to notify;
The second feature is that the configuration is executed.

  Furthermore, according to the self-management support system of the second feature, at least one human body of one or more biological information and acceleration information of the target person even in a place where no human sensor is installed, for example, outdoors. Use the measured value or third statistical value for each type of information as an index to indicate the degree of activity of the subject, and grasp the deviation from the standard state in the daily activity pattern of the subject be able to. Also, in the process of deriving the second standard action pattern, as with the self-management support system of the first feature, the target person himself / herself has a configuration capable of feedback, so that the target person By comparing the behavior pattern with the second evaluated behavior pattern, it is possible to accurately recognize the change in the own activity pattern.

Further, in the self-management support system according to the present invention, in addition to the first or second feature, the arithmetic processing unit further includes:
From the positioning sensor that can be worn on the human body to detect the geographical position information of the subject outside the residence by being worn by the subject, the geographical position information of the subject is sent to the data transmission / reception unit. The activity content outside the residence of the target person by calculating the movement distance for each first unit time based on the geographical position information, and identifying the activity content outside the residence A third data storage process for creating third time-series data in units of the first unit time every day and storing the data in the data storage unit;
Based on the third time-series data of the pre-processing period, a third confirmation data is generated that can identify a place where the subject is determined not to be in a standard state, collectively or divided into a plurality of times, and the data A third confirmation data transmission process for transmitting the third confirmation data to the confirmation terminal via a transceiver;
When receiving the input of the third confirmed data from the confirmation terminal via the data transmission / reception unit, the location where the subject determined that the subject is not in the standard state with respect to the third confirmation data is received. 3 If the third time series data is corrected based on the confirmed data, based on the corrected third time series data, and the input of the third confirmed data is not received from the confirmation terminal, A third standard action pattern indicating a third standard state of the activity pattern of the target person is derived based on the third time-series data of the preprocessing period that was initially created, and is stored in the data storage unit. 3 standard state derivation processing;
Based on the third time-series data of the evaluation period, a third evaluated action pattern to be evaluated for the activity pattern of the target person is derived, and the third standard action pattern of the third evaluated action pattern A third divergence creation process for deriving a predetermined third divergence from
The third output data including the third divergence degree is created, the third output data is transmitted to the first user terminal via the data transmission / reception unit, and the third divergence degree is transmitted to the target person. A third output process to notify;
The third feature is that the system is configured to execute.

  According to the self-management support system of the third feature, the degree of activity of the subject can be determined based on the distance traveled by the subject per first unit time even in places where human sensors are not installed, such as outdoors. It can be used as an index to indicate the deviation from the standard state in the daily activity pattern of the subject. Also, in the process of deriving the third standard action pattern, as in the self-management support system of the first feature, the target person himself / herself has a configuration capable of feedback. By comparing the behavior pattern with the third evaluated behavior pattern, it is possible to accurately recognize the change in the own activity pattern.

Further, in the self-management support system according to the present invention, in addition to any of the first to third features, the arithmetic processing unit further includes:
A use decomposition process is performed on the power consumption in the target person's residence, and the time transition of the power consumption of a plurality of electrical devices related to the activity pattern in the residence of the target person is specified for each device. A fourth data storage process for creating fourth time-series data in predetermined second unit time increments on a processing target day of power consumption and power consumption by each electrical device, and storing the fourth time-series data in the data storage unit;
Based on the first time-series data and the fourth time-series data, activity contents in the subject person's residence on the processing target date are decomposed into time series for each activity type, and activity log data is created, Activity log data creation processing to be stored in the data storage unit;
The activity log data is transmitted to at least one of the first user terminal and a pre-registered second user terminal via the data transmission / reception unit, and the activity log data is pre-registered with the target person. A fourth output process for notifying at least one of the related parties of the target person;
The fourth feature is that the system is configured to execute the above.

Furthermore, a self-management support system according to the present invention is a self-management support system that notifies the subject of daily activity patterns of the subject, and includes a data transmission / reception unit, a data storage unit, and an arithmetic processing unit. The arithmetic processing unit is
Measurement data of the number of motions of the subject sensed by the motion sensor from a motion sensor that senses the motion of a person installed at one or more predetermined positions in the residence of the subject, the data transmission / reception unit A first data storage process in which the first time-series data is generated at a predetermined first unit time interval on the processing target date of the number of operations, and is stored in the data storage unit. ,
A use decomposition process is performed on the power consumption in the target person's residence, and the time transition of the power consumption of a plurality of electrical devices related to the activity pattern in the residence of the target person is specified for each device. A fourth data storage process for creating fourth time-series data in predetermined second unit time increments on a processing target day of power consumption and power consumption by each electrical device, and storing the fourth time-series data in the data storage unit;
Based on the first time-series data and the fourth time-series data, activity contents in the subject person's residence on the processing target date are decomposed into time series for each activity type, and activity log data is created, Activity log data creation processing to be stored in the data storage unit;
The activity log data is transmitted to at least one of the first user terminal and a pre-registered second user terminal via the data transmission / reception unit, and the activity log data is pre-registered with the target person. A fourth output process for notifying at least one of the related parties of the target person;
The fifth feature is that the system is configured to execute.

  According to the self-management support system of the fourth or fifth feature described above, the daily activity pattern of the subject is not limited to the number of operations at the location where the human sensor is installed, but also a plurality of electricity related to the activity pattern. In consideration of the operation status of each device, the activity content can be disassembled by activity type and presented to the target person or the person concerned. Thereby, the subject person or the related person can grasp the daily activity pattern of the subject person more specifically and in detail.

  Further, in the self-management support system according to the fourth or fifth feature, in the activity log data creation process, the arithmetic processing unit may start from the start of the processing target day before the end of the processing target day to an intermediate point. About the activity content in the subject person's residence, or the activity content in the subject person's residence on the processing date after the processing date ends, there is an error in the activity type decomposed in time series In some cases, the target person creates fourth confirmation data in which the activity type and the activity time zone can be corrected, and the fourth confirmation data is used by the subject person through the data transmission / reception unit. To the terminal for confirmation, and input of the fourth confirmed data in which the subject corrects the activity type or the activity time zone with respect to the fourth confirmation data from the confirmation terminal via the data transmission / reception unit. The If only attached, based on the fourth confirmed data, it is preferable to modify the activity log data during or after creation created.

  According to the preferred embodiment, the estimation accuracy of the activity log data is improved. Furthermore, the accuracy of the estimation logic or rule is improved by learning the estimation logic or rule used in the activity log data creation process by feedback on the fourth confirmation data by the target person, and as a result, the estimation of the activity log data is performed. Accuracy is improved.

  Further, in the self-management support system according to the fourth or fifth feature, the calculation processing unit, and further the calculation processing unit, in the activity log data creation process, the installation location of the human sensor and the number of operations. Is extracted from the activity type for each activity type on the processing target date based on the time period of the predetermined number or more and the operation time for each electrical device, and decomposed by the activity type of the activity content It is preferable.

Further, in the self-management support system according to the present invention, in addition to the fourth or fifth feature, the arithmetic processing unit further includes:
Based on the activity log data over a plurality of days, a standard activity time zone for each activity type is derived, and standard activity log data indicating standard activity contents in the residence of the subject is created. , Standard activity log data creation processing to be stored in the data storage unit,
A divergence state in which the standard activity log data is compared with the activity log data on the processing target date to report a divergence state from a standard activity content of the activity content in the subject person's residence on the processing target date Creating divergence state report data to create report data and storing it in the data storage unit;
The divergence state report data is transmitted to at least one of the first user terminal and the second user terminal via the data transmitting / receiving unit, and the divergence state report data is transmitted to the target person and the related parties. A fifth output process for notifying at least one of them;
The sixth feature is that the system is configured to execute the above.

  According to the self-management support system of the sixth feature described above, the deviation from the standard state in the daily activity pattern of the target person is decomposed by the activity type of the activity content, and more specifically, the target person or the target person Can be presented to

  Furthermore, in addition to the sixth feature, the self-management support system according to the present invention is configured so that the calculation processing unit is classified according to the activity type recorded in the standard activity log data in the deviation state report data creation process. The standard activity time zone of the activity time and the activity time zone by the activity type on the processing target date are compared, and the difference in the length of the activity time zone or the start time or end time of the activity time zone When the difference exceeds a predetermined threshold, it is preferable to include the activity type and the activity time zone exceeding the threshold in the deviation state report data.

Further, in the self-management support system according to the present invention, in addition to any of the fourth to sixth features, the arithmetic processing unit includes:
In the activity log data creation process, without waiting for the end of the processing target day, the activity contents in the residence of the target person from the start to the midpoint of the processing target day are decomposed into time series by activity type. Intermediate activity log data is created, and the intermediate activity log data is sequentially updated,
In the fourth output process, each time the intermediate activity log data is updated, the intermediate activity log data is transmitted to at least one of the first user terminal and a pre-registered second user terminal. Is preferred.

  According to the above-described preferred embodiment, the subject person or the person concerned can determine the status of the activity in the subject's residence in almost real time by the intermediate activity log data that is sequentially updated. I can grasp it. For this reason, for example, when the target person is an elderly person and the related person is a relative or the like, the related person can successively watch the activity contents of the target person who is an elderly person.

  According to the self-management support system according to the present invention, the subject person can be notified of the deviation from the standard state in the daily activity pattern of the subject person in a recognizable manner. As a result, the target person who has received the notification can objectively know the changes in his / her living condition and health condition.

1 is a block diagram schematically showing a configuration example of a self-management support system according to a first embodiment. The figure which shows an example of the time series data of the measurement result of the human sensor with respect to three types of scenario play. The flowchart which shows the outline of an example of the processing content of the arithmetic processing part of the self-management assistance system which concerns on 1st Embodiment. The figure which shows typically an example of the 1st confirmation data produced by the 1st confirmation data transmission process shown in FIG. The figure which shows typically another example of the 1st confirmation data produced by the 1st confirmation data transmission process shown in FIG. The figure which shows typically an example of the 1st output data produced by the 1st output process shown in FIG. The block diagram which shows typically the example of 1 structure of the self-management assistance system which concerns on 2nd and 3rd embodiment. The flowchart which shows the outline of an example of the processing content of the arithmetic processing part of the self-management assistance system which concerns on 2nd Embodiment. The flowchart which shows the outline of an example of the processing content of the arithmetic processing part of the self-management assistance system which concerns on 3rd Embodiment. The block diagram which shows typically the example of 1 structure of the self-management assistance system which concerns on 4th Embodiment. The flowchart which shows the outline of an example of the processing content of the arithmetic processing part of the self-management assistance system which concerns on 4th Embodiment. The table | surface which shows the outline of the content of 1st time series data and 4th time series data used for the estimation of the activity classification in activity log data creation processing according to activity classification. The figure which shows the example of a screen display of activity log data typically.

  Embodiments of a self-management support system according to the present invention (hereinafter abbreviated as “this system” where appropriate) will be described below in detail with reference to the drawings.

[First Embodiment]
As shown in FIG. 1, the system 1 according to the first embodiment includes a data transmission / reception unit 11, a data storage unit 12, and an arithmetic processing unit 13. The system 1 is a self-management support system that notifies the subject person of deviation from the standard state in the daily activity pattern of the subject, and is located at one or more predetermined positions in the subject's residence 20. One or a plurality of human sensors 21 for detecting human motion are installed. Further, in the residence 20, there is a data relay device 22 that collects measurement data of human motion detected by the human sensor 21 and transmits it to the system 1 via a data communication network N such as the Internet. is set up.

  In the present embodiment, the system 1 is configured to be able to provide the self-management support service (hereinafter, abbreviated as “this service” as appropriate) individually to a plurality of target persons A1 to An. The transmission / reception unit 11 is separately connected to the data relay device 22 in the residence 20 of each target person A1 to An so as to be able to transmit and receive data via a data communication network such as the Internet. In the present embodiment, each target person is a person who lives substantially alone in the residence 10 as an example, and may be a complete living alone. For example, most of the day lives alone. The person who becomes.

  The data transmission / reception unit 11 includes, for example, an existing communication device that transmits / receives data to / from each of the data relay devices 22 installed in the target persons A1 to An via a predetermined data communication network N such as the Internet. Is done.

  The data storage unit 12 includes, for example, a recording device that can record a large amount of data in a nonvolatile manner such as an HDD (hard disk drive) and an SSD (solid state disk) and the like. It is configured to function as a database so that writing, reading, searching, and the like are possible.

  The arithmetic processing unit 13 is configured as a computer including an arithmetic device such as a CPU (Central Processing Unit) and a storage device such as a semiconductor memory, for example.

  In one embodiment, the data transmission / reception unit 11, the data storage unit 12, and the arithmetic processing unit 13 of the system 1 are configured as a WEB server system or a cloud computing system that provides a kind of cloud computing service, and are registered in advance. The target subjects A1 to An are configured to be accessible by designating a predetermined URL (uniform resource locator) via the Internet.

  The form of the target person's residence 20 does not need to be the same among the plurality of target persons A <b> 1 to An, and a detached house, a single residential section in an apartment house, and the like are assumed.

  As an example, the human sensor 21 is configured by using a commercially available human sensor using a pyroelectric infrared sensor. For example, the human sensor 21 has an interval of about 1 second to 10 seconds. Changes in the intensity of infrared rays emitted from the human body within the sensing area are detected. Thereby, the motion of the subject within the sensing area (movement of at least a part of the human body) is sensed as a change in infrared intensity. In the present embodiment, as an example, the presence / absence of the movement of the subject detected at intervals of 1 second by each human sensor 21 is counted every predetermined first unit time (for example, 1 minute), and the movement for the 1 minute is performed. The number of times is transmitted as the first measurement data to the data relay device 22 every minute. In this case, the number of operations indicated by the first measurement data per minute is an integer value of 0-60. The first unit time for counting the number of movements of the target person is preferably 1 minute or more and 60 minutes or less, but it is better to set as short as possible the characteristics of the target person's series of actions (activity, duration, number of times, etc.) Can be accurately grasped, which is preferable. The human sensor 21 is not limited to the pyroelectric infrared sensor type.

  Further, the necessary number of human sensors 21 are installed in predetermined locations in the residence 20 suitable for derivation of the daily activity pattern of the subject person, for example, a living room, a bedroom, and a toilet. For example, when the main living space of the subject person is a living room, the necessary number is set so that the sensing area of each human sensor 21 can cover the entire range in which the subject person moves in the living room. In addition, when it is necessary to cover one detection target range with a plurality of human sensors 21, an area where each detection area overlaps is a place where the target person stays for a long time (for example, a chair, a desk, a table, It is preferable to avoid a place where a sofa or the like is placed, and it is preferable to adjust the installation position of each human sensor 21, the width of the detection area, or both so that the overlap area is as narrow as possible.

  In FIG. 2, a commercially available human sensor using a pyroelectric infrared sensor was installed in a living room / dining room with a size of about 12 tatami mats as a trial, and three types of scenario play (1. Move around in the living room (PLAY1) 2. Sit on the sofa and watch TV (PLAY2) 3. Sit on the sofa and read newspapers, magazines, etc. (PLAY3)) for 10 minutes each (on the time axis in Fig. 2) 1 to 10 minutes, 11 to 20 minutes, and 31 to 40 minutes), and shows the measurement data obtained by counting the motion sensing data of 1 second granularity every minute. As shown in FIG. 2, the human sensor 21 used in the present embodiment shows that the more the subject's motion is active, the more the number of operations per minute detected by the human sensor increases. It can be seen that the activity level of a typical activity pattern and its change can be captured.

  The data relay device 22 receives, from each human sensor 21 via the predetermined communication path C, the first communication device 22a that receives the first measurement data generated by the human sensor 21 every minute, From the measurement data recording unit 22b that records the first measurement data received from the sensor 21 every minute for a certain period (for example, one day to one month), and from each human sensor 21 recorded in the measurement data recording unit 22b. First identification information that can identify the target person and the human sensor, and the start date and time and the length of the certain time (for example, 1 to 24 hours) of the received measurement data every minute. Or the first time information capable of identifying the end date and time) to generate second measurement data for each human sensor 21, and via the predetermined data communication network N such as the Internet at the predetermined time intervals, Data transmission / reception unit 11 of the system 1 Configured with a second communication device 22c to be transmitted. In the above description, the presence / absence of the motion of the subject detected at 1-second intervals is tabulated on the human sensor 21 side, but may be configured to perform the tabulation processing on the data relay device 22 side. .

  The communication path C between the human sensor 21 and the first communication device 22a may be either a wired communication path or a wireless communication path. However, if the degree of freedom in selecting the installation location of the human sensor 21 is considered, the wireless communication path For example, a wireless communication path using a wireless communication system such as a specific low power wireless, Wi-Fi (IEEE802.11 standard wireless LAN), or Bluetooth (registered trademark) can be used.

  Although the data relay device 22 is illustrated as one device in FIG. 1, the first communication device 22a is configured as a communication master unit of the human sensor 21, and the measurement data recording unit 22b and the second communication device are configured. 22c is configured as a part of a personal computer that can be connected to the Internet or the like used in the residence 20, and the personal computer and the first communication device 22a are installed in the home LAN (wired). It may be an embodiment in which data communication is possible via a LAN or Wi-Fi).

  Next, processing contents executed by the system 1 to provide the target person with the service will be described. In the following description, the processing content for one target person will be described, but the same applies to other target persons.

  In the system 1, the arithmetic processing unit 13 performs five processes: a first data storage process, a first confirmation data transmission process, a first standard state derivation process, a first divergence creation process, and a first output process. . The relationship between the processes is as shown in FIG. Note that the five processes are such that the program code of the computer program describing each specific processing content is stored in the storage area of the storage device of the arithmetic processing unit 13, and the arithmetic device executes the program, Executed.

  The arithmetic processing unit 13 performs the first data storage process for each installation location (for example, living room, bedroom, toilet, etc.) of the human sensor 21 in the following manner. In the first data storage process, when the arithmetic processing unit 13 receives the second measurement data for each human sensor 21 from the data relay device 22 through the data transmission / reception unit 2 at regular time intervals (for example, one hour). The target person and the human sensor 21 are temporarily stored in the data storage unit 12 so that they can be identified. When the second measurement data for one day is stored in the data storage unit 12, if only one human sensor 21 is installed at the installation site of the human sensor 21, for example, 60 1 Twenty-four second measurement data for one hour consisting of the first measurement data for one minute (first unit time) are read from the data storage unit 12 and arranged in order, and the second measurement data for one day (24 hours) Create 1 time series data. Note that the first measurement data, which is a constituent unit of the first time series data in 1 minute increments, may be referred to as “unit time data” for convenience.

  Here, when two or more human sensors 21 are installed at one installation location of the human sensor 21, first, similarly to the above, each human sensor 21 has the same 24 hours as the first time-series data. One-minute sensor-specific time-series data is created for each human sensor 21, and the number of movements per minute for the same hour of each sensor-based time-series data is totaled for one day (24 hours). First time-series data in increments of 1 minute is created. In the latter case, if the subject is moving in the body while remaining in the overlap area of the sensing areas of the two human sensors 21, the same motion may be detected by the two human sensors 21 in duplicate. As described above, when the number of operations is simply summed, the number of operations per minute of the first time-series data may exceed 60. Furthermore, even if there is no overlap region, the value of the first measurement data of each time sensor can be 60 if the operation of reciprocating between two sensing areas, for example, every second is repeated for one minute. However, when the same reciprocating operation per second is performed in one sensing area, only one first measurement data value corresponding to the sensing area is 60. Therefore, except for very special cases, it is assumed that it is rare that the total number of operations per minute of the same hour of two or more sensor-specific time series data exceeds 60, and the upper limit after the sum is limited. Some correction processing limited to 60 may be performed. As an example of the correction process, the number of operations exceeding 60 is simply set to 60 (first correction process), and the maximum number of operations per minute for the same hour of two or more sensor-specific time-series data, A value obtained by multiplying the number of operations with the next largest value by a predetermined coefficient (for example, 0.1 to 0.5) and adding 60 to 60 after the addition (second correction process) or the like. Conceivable. Further, instead of the above summing process, the first time series data may be created by selecting the maximum value of the number of operations per minute for the same hour of two or more sensor time series data. The first time-series data for each installation location of the human sensor 21 created in any of the manners described above is stored in the data storage unit 12 so that the target person and the installation location of the human sensor 21 can be identified. The first data storage process is continuously executed every day for a target person who continues to provide the service.

  The arithmetic processing unit 13 performs a first confirmation data transmission process in the following manner. The first time-series data in units of one day for each installation location of the human sensor 21 is a pre-processing period over a plurality of days before starting the operation of this service (for example, about 2 to 6 weeks before the start of operation). The first confirmation data created in the following manner is collected from the data transmitting / receiving unit 11 in a lump after being created, or divided into multiple times in the middle of creation (for example, every 1 to 7 days), It transmits toward the predetermined | prescribed confirmation terminal which an object person uses via data communication networks N, such as the internet. Here, a personal computer, a smartphone, a tablet terminal, or the like that can be connected to a data communication network N such as the Internet is assumed as the confirmation terminal used by the target person.

  In the present embodiment, as an example, the process of transmitting the first confirmation data to the confirmation terminal transmits a confirmation request email of the first confirmation data to the email address registered in advance of the subject, and the subject confirms the confirmation. The request mail is received by the confirmation terminal, and is loaded in advance on the confirmation terminal on the WEB page of the system 1 specified by the URL for confirmation of the first confirmation data described in the confirmation request mail. When the browser is activated and accessed via the data communication network N, the first confirmation data is transmitted from the data transmitting / receiving unit 11 to the confirmation terminal via the data communication network N, and the browser of the confirmation terminal The first confirmation data is displayed on the WEB page displayed on the display screen.

  For example, as shown in FIGS. 4 and 5, the first confirmation data includes first time-series data for each installation location (living room, bedroom, toilet) for each day so that the difference between the month and date can be understood. Two input fields 23 and 24 are provided on the right side of each graph, which are integrated as one graph, displayed in order, and a place where the subject is judged not to be in the standard state. In the input field 23, either “normal” indicating “standard state” or “special” indicating “not standard state” can be selected and input. In the input field 24, “special” It is configured to be able to select and input up to five time zones that are considered (not in the standard state). The default is 0 o'clock to 24 o'clock. For the three days from December 1 to December 3 shown in FIG. 4, the subject is out on a trip for 3 days and 2 nights, and the three days are judged as “special” (not in the standard state) and excluded. ing. In the example shown in FIG. 4, in the three days from December 1 to December 3, the entire range from 0:00 to 24:00 is determined to be “special” (not in the standard state) in all three installation locations. Yes. For three days from December 4 to December 6 shown in FIG. 5, the subject determines “normal” (in the standard state).

  In the illustrations of FIGS. 4 and 5, the first confirmation data is displayed by integrating the first time-series data for each of the three installation locations (living room, bedroom, toilet) of the human sensor 21 in one graph. However, the first time-series data to be displayed may be selected for each installation location. Then, for each installation location, a time zone that is considered “special”, “normal”, and “special” (not in a standard state) may be designated. For example, it is possible to determine “special” (not a standard state) such as “entertainment in the living room”, “remodeling of the bedroom”, “toilet cleaning”, and the time zone can be excluded.

  The arithmetic processing unit 13 performs a first standard state derivation process in the following manner. For the first confirmation data displayed on the display screen of the browser of the predetermined confirmation terminal, the target person considers that month or day to be considered “special” (not standard) on the screen, When a time zone is specified and a predetermined “send” button (not shown) is clicked (or touched), the content is sent as first confirmed data to the system 1 via the data communication network N. Is done. When the arithmetic processing unit 13 receives the first confirmed data via the data transmission / reception unit 11, the arithmetic processing unit 13 temporarily stores it in the data storage unit 12. In the case where the first confirmation data is transmitted to the confirmation terminal in a batch in the first confirmation data transmission process, the first confirmation data is received once, and the first confirmation data is confirmed in multiple times. In the case of being transmitted to the service terminal, the first confirmed data is received a plurality of times. The arithmetic processing unit 13 receives the first confirmed data corresponding to all the first confirmation data transmitted to the confirmation terminal, and then performs the first data storage process based on the received first confirmed data. For the first time-series data within the created pre-processing period, the date / month / day and time zone data specified as “special” (not standard) in the first confirmed data will be processed later. It is modified to invalidate it so that it will not be used (in a state where no data exists). Receive the first confirmed data from the target person when there is no month or date and time zone designated as “special” (not standard) in the first confirmed data, or by the predetermined deadline If not, the correction is not performed on the first time series data in the preprocessing period created in the first data storage process, and the first time series data after correction is used as it is. And the arithmetic processing part 13 shows the 1st standard state of the activity pattern in each installation place (a living room, a bedroom, a toilet) of the subject person's human sensitive sensor 21 based on the 1st time series data after correction. A first standard action pattern is derived and stored in the data storage unit 12.

  The first standard action pattern is calculated according to the following procedure for each installation location. The first standard action pattern in the living room is the first time-series data after the living room is corrected within the pre-processing period, and the number of unit time data whose number of operations is 1 or more is the total stay time (minutes) in the living room. It is calculated as the average activity amount obtained by dividing the total number of movements in the pre-processing period as the total activity amount and dividing the total activity amount by the total stay time.

  The first standard action pattern in the bedroom is, for example, the bedroom stay start time and the bedroom stay end time calculated in the following manner. In the example shown below, the first time series data after the correction of the bedroom in the preprocessing period in which the data is not invalidated between 10 pm and 6 am is used. The first hour of the unit time data whose number of operations from 10:00 to 6:00 am is 1 or more as a temporary stay disclosure time, and the number of operations at the temporary stay disclosure time is a predetermined reference value (for example, 40) If there is no unit time data for which the number of operations is 1 or more within a predetermined time (for example, 2 hours) immediately before that, the time is set as the daily stay start time of the month and day. There is unit time data with the number of movements of 1 or more within the predetermined time (for example, 2 hours) immediately before that, and the number of movements at the stay disclosure time is less than the reference value. The same processing is repeated as the disclosure time, and the daily stay start time of the month and day is searched. If the daily stay start time is not determined even after repeating a predetermined number of times (for example, twice), the daily stay start time is not determined.

  Next, with the last hour and minute of the unit time data whose number of operations from 10:00 to 6:00 am being one or more as the temporary stay end time, the number of operations at the temporary stay end time is a predetermined reference value. (For example, 40) or more, and if there is no unit time data whose number of operations is 1 or more within a predetermined time (for example, 2 hours) immediately after that, the time of day staying for the day of the month If the number of operations at the temporary stay end time is less than the reference value and there is unit time data with the number of operations of 1 or more within a predetermined time (for example, 2 hours) immediately after that, the last hour and minute are The same processing is repeated as the temporary stay disclosure time, and the daily stay end time of the month and day is searched. If the daily stay end time is not determined even after being repeated a predetermined number of times (for example, twice), the daily stay end time is not determined.

  With respect to the daily stay start time and daily stay end time within the preprocessing period determined in the above manner, for example, the respective average value or median value is calculated, and the bedroom stay start time and bedroom stay end time are calculated. To do. If the parameters of the daily stay start time and the daily stay end time are large, the mode value may be calculated instead of the average value or the median value. In this case, the mode value is obtained by grouping the daily stay start time and the daily stay end time, for example, in units of 10 minutes, and the average value or median value in the mode group is obtained. You may make it calculate.

  Further, the first standard action pattern in the toilet is, for example, the standard number of toilets calculated in the following manner using the first time series data after the toilet is corrected within the preprocessing period. For each first time-series data after daily correction, there is unit time data in which the number of operations is equal to or greater than a reference value (for example, 30) in a group in which one or more unit time data having the number of operations is one or more. In some cases, it is determined that the toilet is used once, and the number of toilets used per day is counted. However, the total number of times invalidated in the first time-series data of any one installation location after correction is, for example, that of a toilet on a day when the predetermined time (for example, 6 to 12 hours) or more is exceeded. The first time series data after correction is excluded. And the average value of the number of times of toilet use on the 1st calculated with respect to each effective 1st time series data after correction is calculated as a standard number of toilets.

  The arithmetic processing unit 13 performs the first divergence creation process in the following manner. The arithmetic processing unit 13 first reads out the first time-series data of a predetermined evaluation period for one day or a plurality of days after the pre-processing period from the data storage unit 12, and reads the first time-series data of the predetermined evaluation period read out. Based on the above, for each installation location, the daily first evaluated action pattern is calculated and stored in the data storage unit 12 in the following manner. When the evaluation period spans multiple days, the first evaluated behavior pattern for the multiple days is calculated. The evaluation period is a cycle in which the daily first evaluated behavior pattern is calculated, and is, for example, 1 to 7 days. Hereinafter, the case where the evaluation period is one day will be described as an example. However, when the evaluation period is a plurality of days, the same processing is repeated a plurality of times.

  The first evaluated behavior pattern in the living room is the first time-series data of the living room on the first day in the evaluation period, and the number of unit time data whose number of operations is 1 or more is the total stay time (minutes) in the living room. It is calculated as an average activity amount obtained by dividing the total number of operations of the first time-series data of the living room for the day as a total activity amount and dividing the total activity amount by the total stay time.

  In addition, the first evaluated behavior pattern in the bedroom is based on the first time series data of the bedroom on the first day, the previous day and the next day in the evaluation period, in the same manner as the first standard behavior pattern in the bedroom, The calculated daily stay start time and daily stay end time. If at least one of the daily stay start time and the daily stay end time is not determined, that point is also included in the first evaluated behavior pattern in the bedroom. In addition, since the determination method of the daily stay start time and the daily stay end time is the same as the determination method of the daily stay start time and the daily stay end time when calculating the first standard action pattern in the bedroom, Duplicate explanations are omitted.

  Moreover, the 1st to-be-evaluated action pattern in a toilet is taken as the number of times of toilet use per day calculated in the following manner using the first time series data of the toilet in a day in the evaluation period. With respect to the first time series data of the toilet of the day, there is unit time data in which the number of movements is a reference value (for example, 30) or more in a group in which one or more unit time data of the number of movements is one or more. In this case, it is determined that the toilet is used once, and the number of toilets used per day is counted.

  Subsequently, the arithmetic processing unit 13 compares each first evaluated behavior pattern for each installation location of the calculated evaluation period for each day with each first standard behavior pattern for each installation location, which is already calculated, for each installation location. Is calculated and stored in the data storage unit 12. The first divergence degree in the living room is given as an example of the difference in average activity amount obtained by subtracting the first standard action pattern (average activity amount) in the living room from the first evaluated behavior pattern (average activity amount) in the living room. It is done.

  As an example of the first divergence degree in the bedroom, two types of first divergence degrees are calculated: a stay start time and a stay end time. The first divergence degree (stay start time) is, for example, the stay start time obtained by subtracting the first standard action pattern (bedroom stay start time) of the bedroom from the first evaluated behavior pattern of the bedroom (daily stay start time). The difference is given as a ratio obtained by dividing the difference by the difference between the maximum value and the minimum value of the daily stay start time within the preprocessing period obtained in the calculation process of the first standard action pattern in the bedroom. The first divergence degree (stay end time) is, for example, a stay end time obtained by subtracting the first standard action pattern (bedroom stay end time) of the bedroom from the first evaluated behavior pattern of the bedroom (daily stay end time). The difference is given as a ratio obtained by dividing the difference by the difference between the maximum value and the minimum value of the daily stay end time within the preprocessing period obtained in the calculation process of the first standard action pattern in the bedroom. One or both of the first evaluated behavior pattern (daily stay start time) and the first evaluated behavior pattern (daily stay end time) in the bedroom may not be calculated. The two types of first divergence include that the related first divergence cannot be calculated.

  As an example, the first divergence degree in the toilet is given as a ratio obtained by dividing the first evaluated behavior pattern in the toilet (the number of toilets used per day) by the first standard action pattern in the toilet (the number of standard toilets). .

  The arithmetic processing unit 13 performs the first output process in the following manner. The arithmetic processing unit 13 creates first output data for displaying each first divergence degree for each installation location of the calculated evaluation period in a predetermined display format in a predetermined display format. An electronic mail message including the first output data is transmitted to the target person's pre-registered mail address via the network N. The subject can view the first output data on the display screen of the first user terminal by receiving the electronic mail message at a predetermined first user terminal used by the subject. As the first user terminal, a personal computer, a smartphone, a tablet terminal, or the like that can be connected to a data communication network N such as the Internet is assumed, and may be the same as the above-described confirmation terminal or a different terminal.

  By viewing the first output data, the target person confirms whether or not the activity pattern has changed from the standard state in the living room and the degree thereof, and whether or not the bedtime rhythm has changed from the standard state in the bedroom. And the presence or absence of the change from the standard state of the use frequency of the toilet and the degree thereof can be objectively confirmed.

  FIG. 6 shows an example of the display format of the first output data. In the example shown in FIG. 6, each of the first standard action pattern, the first evaluated action pattern, and the first degree of divergence is summarized in a table form for each installation location, and is simply displayed. In addition, the numerical value of each calculation result is displayed in the location currently displayed with the symbol (alphabet) or numerical formula in FIG.

  In addition to the first output process described above, it is also a preferred embodiment to provide the subject with a viewing option of the first evaluated behavior pattern and the first divergence described below. Specifically, a URL for accessing the browsing option service is added to the e-mail message transmitted to the subject in the first output process, and the subject is displayed on the display screen of the first user terminal. When the URL in the e-mail message is clicked (or touched), a browser preinstalled in the first user terminal is activated, and a browsing option service WEB page is displayed on the display screen. In the browsing option service, as an example, the calculation processing unit 13 performs a predetermined calculation process and provides the first evaluated action pattern and the first divergence degree over a plurality of days provided to the target person in the first output process in the past. Presents the transition of the daily unit in a graph or table format, or displays the transition of the average value of the first evaluated behavior pattern and the first divergence degree for each week and month in a graph format or a table format Present.

[Second Embodiment]
Next, the system 2 according to the second embodiment will be described with reference to FIGS. As in the first embodiment, the system 2 includes a data transmission / reception unit 11, a data storage unit 12, and an arithmetic processing unit 13. In the system 2, the processing content described below is added to the processing content described in the first embodiment as the processing content to be executed for providing the service to the target person.

  In this system 2, at least a part of a plurality of subjects A1 to An can be attached to a human body that detects human body information including at least one of a plurality of biological information (heart rate, respiratory rate, etc.) and acceleration information. Assume that the human body information sensor 31, for example, a wristwatch-type wearable sensor is attached. In the present embodiment, it is assumed that the human body information sensor 31 includes at least one of a motion sensor (acceleration sensor) and a heart rate sensor.

  When the human body information sensor 31 includes a motion sensor (acceleration sensor), for example, it is possible to detect an operation accompanied by a change in the speed of the wrist when the human body information sensor 31 is attached to the wrist of the subject. Accordingly, as in the case of the human sensor 21 of the first embodiment, when the number of operations involving the speed change is counted for each first unit time (1 minute), for example, the human sensor 21 installed in the living room Similarly, it is possible to grasp the characteristics (activity, duration, number of times, etc.) of a series of actions of the subject. However, in the case of a watch-type wearable sensor, the movement is limited to the movement of the wrist. Therefore, even if the movement is performed while sitting on a chair, the movement of the wrist frequently is recognized as a very active movement. Is done. For this reason, in this embodiment, the measurement of the daily activity pattern of the subject by the human body information sensor 31 is used as a supplement to the measurement by the human sensor 21. In the case of the human sensor 21, the grasp of the characteristics of a series of movements of the target person is based on the premise that the target person exists within the sensing range of the human sensor 21, but in the case of the human body information sensor 31, It is assumed that the subject is wearing the human body information sensor 31. Therefore, in the case of the human body information sensor 31, the measurement by the human sensor 21 is supplemented in that the daily activity pattern of the subject can be measured without being limited to the location of the subject.

  When the human body information sensor 31 includes a heart rate sensor, an increase in the exercise load on the subject appears as an increase in the heart rate, so that an operation with a certain amount of exercise load on the subject can be detected. In the present embodiment, as an example, the heart rate is measured every first unit time (1 minute).

  Aggregated data (motion data) per minute measured by the human body information sensor 31 and heart rate per minute (heart rate data) are once taken into the data relay device 32 installed in the residence 20 and then newly added. The data taken in is collectively transmitted to the system 1 via a data communication network N such as the Internet. Specifically, when the target person removes the human body information sensor 31 and connects to the data relay device 32 so as to be able to perform data communication, the respective data are taken into a predetermined storage area in the data relay device 32. When the data relay device 32 is connected to the human body information sensor 31, the data relay device 32 is connected to the system 1 via the data communication network N. When the data is captured, the data relay device 32 transfers the data to the system 1. In the motion data and the heart rate data, in addition to the date and time information added at the time of measurement by the human body information sensor 31, the data relay device 32 can identify the target person and the sensor type of the human body information sensor 31. Is added. As an example, the data relay device 32 is configured using a personal computer that can be connected to the Internet or the like. Further, as the data relay device 32, the first user terminal used by the subject described in the first embodiment may be used. Incorporation of data from the human body information sensor 31 to the data relay device 32 is performed by, for example, wireless communication such as Wi-Fi or Bluetooth, or wired serial data communication via a USB cable or the like.

  Next, processing contents that are executed in addition to the processing contents described in the first embodiment in order for the system 2 to provide the service to the subject will be described. In the following description, the processing content for one target person will be described, but the same applies to other target persons.

  In the system 2, the arithmetic processing unit 13 performs five processes: a second data storage process, a second confirmation data transmission process, a second standard state derivation process, a second divergence degree creation process, and a second output process. . The relationship between the processes is as shown in FIG. Note that the five processes are such that the program code of the computer program describing each specific processing content is stored in the storage area of the storage device of the arithmetic processing unit 13, and the arithmetic device executes the program, Executed.

  The arithmetic processing unit 13 performs the second data storage process in the following manner. In the second data storage process, the arithmetic processing unit 13 receives the motion data and the heart rate data from the data relay device 22 each time the motion data and the heart rate data are newly received. (Motion sensor, heart rate sensor) are temporarily stored in the data storage unit 12 so that they can be identified. When the motion data and heart rate data for one day are stored in the data storage unit 12, each unit time data of 1 minute (first unit time), which is a constituent unit of the motion data and heart rate data, is stored in the data storage unit 12. Are read out and arranged in order to create second time-series data in 1 minute increments for one day (24 hours). Here, since the motion data and heart rate data received from the data relay device 22 include only data for the time actually measured by the human body information sensor 31, data of the time not measured by the human body information sensor 31 is included. The value is distinguished from the data value 0 and inserted into the second time series data as NUL (blank), that is, in a state where there is no data. Note that the structural unit of the second time series data in increments of 1 minute may be referred to as “unit time data” for convenience.

  The arithmetic processing unit 13 performs a second confirmation data transmission process in the following manner. The second time-series data in units of one day for each sensor type of the human body information sensor 31 is a pre-processing period (for example, about 2 to 6 weeks before the start of operation) before starting the operation of this service. ) The second confirmation data created in the following manner is sent from the data transmitting / receiving unit 11 in a lump after being created, or divided into a plurality of times (for example, every 1 to 7 days) in the middle of creation. Then, the data is transmitted to a confirmation terminal used by the subject via a data communication network N such as the Internet.

  In the present embodiment, as an example, the process of transmitting the second confirmation data to the confirmation terminal transmits a confirmation request email of the second confirmation data to the email address registered in advance of the subject, and the subject confirms the confirmation. The request mail is received by the confirmation terminal, and is pre-installed in the confirmation terminal on the WEB page of the system 1 specified by the URL for confirmation of the second confirmation data described in the confirmation request mail. When the browser is started and accessed via the data communication network N, the second confirmation data is transmitted from the data transmitter / receiver 11 to the confirmation terminal via the data communication network N, and the browser of the confirmation terminal The second confirmation data is displayed on the WEB page displayed on the display screen. As an example, the second confirmation data is displayed in a display format in the same manner as the first confirmation data described in the first embodiment.

  The arithmetic processing unit 13 performs the second standard state derivation process in the following manner. For the second confirmation data displayed on the display screen of the browser of the predetermined confirmation terminal, the target person considers the date or the date that is considered “special” (not in the standard state) on the screen. When a time zone is specified and a predetermined “send” button is clicked (or touched), the content is sent as second confirmed data to the system 1 via the data communication network N. When the arithmetic processing unit 13 receives the second confirmed data via the data transmission / reception unit 11, the arithmetic processing unit 13 temporarily stores it in the data storage unit 12. In the case where the second confirmation data is sent to the confirmation terminal in a batch in the second confirmation data transmission process, the second confirmation data is received once, and the second confirmation data is confirmed in multiple times. In the case of being transmitted to the service terminal, the second confirmed data is received the same multiple times. The arithmetic processing unit 13 receives the second confirmed data corresponding to all the second confirmed data transmitted to the confirmation terminal, and then performs a second data storage process based on the received second confirmed data. For the second time-series data within the created pre-processing period, the data for the date or time and the time zone specified as “special” (not standard) in the second confirmed data will be processed later. It is modified to invalidate it so that it will not be used (in a state where no data exists). If there is no month or date and time zone designated as “special” (not standard) in the second confirmed data, or the second confirmed data is received from the subject by the specified deadline If not, the second time-series data within the pre-processing period created in the second data storage process is not corrected, and the corrected second time-series data is used as it is. And the arithmetic processing part 13 derives the 2nd standard action pattern which shows the 2nd standard state based on the measurement result of the human body information sensor 31 of a subject's activity pattern based on the 2nd time series data after correction. The data is stored in the data storage unit 12.

  The second standard action pattern is calculated in the following manner for each sensor type of the human body information sensor 31. The second standard action pattern of motion data is the second time-series data after correction of the motion data within the pre-processing period, and the number of unit time data whose number of operations is 1 or more is the total activity time (minutes). It is calculated as the average activity amount obtained by dividing the total number of operations of the unit time data within the period as the total activity amount and dividing the total activity amount by the total activity time.

  The second standard behavior pattern of the heart rate data is calculated as an average value (average heart rate) of the heart rate of each unit time data of the second time series data after correction of the heart rate data within the preprocessing period as an example. The

  The arithmetic processing unit 13 performs the second divergence creation process in the following manner. First, the arithmetic processing unit 13 reads out the second time-series data of a predetermined evaluation period for one day or a plurality of days after the pre-processing period from the data storage unit 12, and reads the second time-series data of the predetermined evaluation period read out. Based on the above, for each type of sensor of the human body information sensor 31, the second second behavior pattern to be evaluated is calculated and stored in the data storage unit 12 in the following manner. If the evaluation period spans multiple days, the second evaluated behavior pattern for the multiple days is calculated. The evaluation period is a cycle for calculating the second second evaluated behavior pattern for each day, and is, for example, 1 to 7 days. Hereinafter, the case where the evaluation period is one day will be described as an example. However, when the evaluation period is a plurality of days, the same processing is repeated a plurality of times.

  The second action pattern of motion data is the second time-series data after modification of the motion data for one day within the evaluation period, and the total number of unit time data whose number of operations is 1 or more is the total activity time (minutes). The total number of operations of the unit time data per day is defined as the total activity amount, and the total activity amount is calculated as the average activity amount divided by the total activity time.

  In addition, as an example, the second evaluated behavior pattern of the heart rate data is an average value (average heart rate) of heart rates of each unit time data of the second time series data after correction of the daily heart rate data within the evaluation period. Is calculated as

  Subsequently, the arithmetic processing unit 13 determines each second evaluated behavior pattern for each sensor type of the human body information sensor 31 on the 1st day of the calculated evaluation period and each second standard behavior pattern for each sensor type that has already been calculated. And the second divergence degree for each type of the sensor is calculated and stored in the data storage unit 12. As an example, the second divergence degree of the motion data is given as a ratio of the average activity amount obtained by dividing the second evaluated behavior pattern (average activity amount) of the motion data by the second standard action pattern (average activity amount).

  The second divergence degree of the heart rate data is given as, for example, a ratio of the average heart rate obtained by dividing the second evaluated behavior pattern (average heart rate) of the heart rate data by the second standard behavior pattern (average heart rate). It is done.

  The arithmetic processing unit 13 performs the second output process as follows. The arithmetic processing unit 13 creates second output data for displaying each second divergence degree for each sensor type of the human body information sensor 31 in the calculated evaluation period in a predetermined display format, and a data transmitting / receiving unit The electronic mail message including the second output data is transmitted from 11 to a pre-registered mail address via the predetermined data communication network N. The subject can view the second output data on the display screen of the first user terminal by receiving the electronic mail message at a predetermined first user terminal used by the subject. As an example, the second output data can be simply displayed in a tabular form in the same manner as the first output data described in the first embodiment. Furthermore, as with the browsing option described in the first embodiment, it is also a preferable embodiment to provide a browsing option of the second evaluated behavior pattern and the second degree of divergence.

  The target person objectively confirms whether or not the activity pattern (the number of operations and the heart rate) measured by the human body information sensor 31 has changed from the standard state and its extent by browsing the second output data. Can do.

[Third Embodiment]
Next, the system 3 according to the third embodiment will be described with reference to FIGS. As in the first embodiment, the system 3 includes a data transmission / reception unit 11, a data storage unit 12, and an arithmetic processing unit 13. In the system 3, the processing content described below is added to the processing content described in the first embodiment or the second embodiment as the processing content executed to provide the service to the target person.

  In this system 3, at least a part of the plurality of target persons A <b> 1 to An measures the movement amount and movement speed (activity amount) of the target person by detecting the geographical position information outside the target person's residence 20. Assume that a positioning sensor 33 that can be worn on a possible human body, for example, a GPS activity sensor is worn.

  For example, when the positioning sensor 33 detects geographical position information (latitude and longitude) with a granularity of 1 second, it can calculate a moving distance per second, and the moving distance per second is calculated by, for example, a first unit time ( When totaling every 1 minute), it is possible to measure the movement amount (average movement speed (activity amount) for 1 minute) of the subject for each first unit time (1 minute). As a result, for example, similar to the motion sensor 21 of the human sensor 21 or the human body information sensor 31 installed in the living room, it is possible to grasp the characteristics (activity, duration, number of times, etc.) of a series of operations of the target person.

  Aggregated data (movement amount data) every minute measured by the positioning sensor 33 is once taken into the data relay device 32 installed in the residence 20, and then the newly taken data is collected and the Internet or the like is collected. The data is transmitted toward the system 1 via the data communication network N. Specifically, when the target person removes the positioning sensor 33 and connects to the data relay device 32 so as to be able to perform data communication, the data is taken into a predetermined storage area in the data relay device 32. When the data relay device 32 is connected to the positioning sensor 33, the data relay device 32 is connected to the system 1 via the data communication network N. When the movement amount data is captured, the data relay device 32 transfers the data to the system 1. In addition to the date and time information added at the time of measuring the movement amount data, the data relay device 32 adds third identification information that can identify that the movement amount data is the movement amount data to the movement amount data. Data acquisition from the positioning sensor 33 to the data relay device 32 is performed by, for example, wireless communication such as Wi-Fi or Bluetooth, or wired serial data communication via a USB cable or the like.

  Next, in order to provide this service to a target person, the processing contents executed in addition to the processing contents described in the first or second embodiment will be briefly described. In the following description, the processing content for one target person will be described, but the same applies to other target persons.

  In the system 3, the arithmetic processing unit 13 performs five processes: a third data storage process, a third confirmation data transmission process, a third standard state derivation process, a third divergence creation process, and a third output process. . The relationship between the processes is as shown in FIG. Note that the five processes are such that the program code of the computer program describing each specific processing content is stored in the storage area of the storage device of the arithmetic processing unit 13, and the arithmetic device executes the program, Executed.

  The system 3 includes five data storage processes, third confirmation data transmission processes, third standard state derivation processes, third divergence creation processes, and third output processes performed on the movement amount data. The processing includes second data storage processing, second confirmation data transmission processing, second standard state derivation processing, second divergence creation processing, and second output processing performed on the motion data described in the second embodiment. This is basically the same as the above five processes.

  The arithmetic processing unit 13 performs a third data storage process in the following manner. In the third data storage process, each time the movement processing unit 13 newly receives movement amount data from the data relay device 22, the arithmetic processing unit 13 can identify that the movement amount data is the movement amount data from the target person. The data is stored in the data storage unit 12. When the movement amount data for one day is stored in the data storage unit 12, each unit time data of 1 minute (first unit time) which is a unit of movement amount data is read from the data storage unit 12, The third time-series data for 1 day (24 hours) in 1 minute increments is created. Here, since the movement amount data received from the data relay device 22 includes only data for the time actually measured by the positioning sensor 33, the data value of the time not measured by the positioning sensor 33 is the data It is inserted into the third time series data as NUL (blank) in distinction from the value 0, that is, in a state where there is no data. Note that the structural unit of the third time series data in increments of 1 minute may be referred to as “unit time data” for convenience.

  The arithmetic processing unit 13 performs a third confirmation data transmission process in the following manner. After the third time-series data in daily units are created for the pre-processing period (for example, about 2 to 6 weeks before the start of operation) for a plurality of days before the operation of this service is started, Alternatively, the third confirmation data created in the following manner is divided into a plurality of times (for example, every 1 to 7 days) in the middle of the creation from the data transmission / reception unit 11 via the data communication network N such as the Internet. To the terminal for confirmation used by the target person.

  In the present embodiment, the transmission process of the third confirmation data to the confirmation terminal is the same as the transmission process of the first confirmation data described in the first embodiment and the second confirmation data described in the second embodiment. Do. Therefore, the overlapping description is omitted.

  The arithmetic processing unit 13 performs the third standard state derivation process as follows. For the third confirmation data displayed on the display screen of the browser of the predetermined confirmation terminal, the target person will consider the date or the date that is considered “special” (not standard) on the screen. When a time zone is specified and a predetermined “send” button is clicked (or touched), the content is transmitted as third confirmed data to the system 1 via the data communication network N. When the arithmetic processing unit 13 receives the third confirmed data via the data transmission / reception unit 11, the arithmetic processing unit 13 temporarily stores it in the data storage unit 12. In the case where the third confirmation data is transmitted to the confirmation terminal in a batch in the third confirmation data transmission process, the third confirmation data is received once and the third confirmation data is confirmed in multiple times. In the case where the data is transmitted to the service terminal, the third confirmed data is received a plurality of times. The arithmetic processing unit 13 receives the third confirmed data corresponding to all the third confirmation data transmitted to the confirmation terminal, and then performs a third data storage process based on the received third confirmed data. For the third time series data within the created pre-processing period, the data for the date or time and the time zone specified as “special” (not standard) in the third confirmed data will be processed later. It is modified to invalidate it so that it will not be used (in a state where no data exists). If there is no month or date and time zone specified as “special” (not standard) in the third confirmed data, or the third confirmed data is received from the target person by the specified deadline If not, the above-mentioned correction is not performed on the third time series data within the preprocessing period created in the third data storage process, and the corrected third time series data is used as it is. And the arithmetic processing part 13 derive | leads out the 3rd standard action pattern which shows the 3rd standard state based on the measurement result of the positioning sensor 33 of a subject's activity pattern based on the corrected 3rd time series data, The data is stored in the data storage unit 12.

  The third standard action pattern is the third time-series data after correction of the movement amount data within the preprocessing period. The number of unit time data whose movement amount is not 0 or NUL is the total movement time (minutes), and the preprocessing period. The total amount of movement of the unit time data is defined as a total movement amount, and the total movement amount is calculated as an average movement speed divided by the total movement time.

  The arithmetic processing unit 13 performs the third divergence creation process in the following manner. First, the arithmetic processing unit 13 reads out the third time-series data of a predetermined evaluation period of one day or a plurality of days after the pre-processing period from the data storage unit 12 and reads the read third time-series data of the predetermined evaluation period. Based on the above, the daily third evaluated action pattern is calculated and stored in the data storage unit 12 in the following manner. When the evaluation period extends over a plurality of days, a third evaluated action pattern for the plurality of days is calculated. The evaluation period is a cycle in which the daily third action pattern to be evaluated is calculated, and is, for example, 1 to 7 days. Hereinafter, the case where the evaluation period is one day will be described as an example. However, when the evaluation period is a plurality of days, the same processing is repeated a plurality of times.

  The third evaluated behavior pattern is the third time-series data after the correction of the day within the evaluation period, and the number of unit time data whose movement amount is not 0 or NUL is defined as the total movement time (minutes). The total movement amount of the unit time data is defined as the total movement amount, and the average movement speed is calculated by dividing the total movement amount by the total movement time.

  Subsequently, the arithmetic processing unit 13 compares the third evaluated action pattern of the calculated evaluation period on the 1st with the already calculated third standard action pattern, calculates the third divergence degree, and the data storage unit 12 Save to. As an example, the third divergence degree is given as a ratio of the average moving speed obtained by dividing the third evaluated action pattern (average moving speed) by the third standard action pattern (average moving speed).

  The arithmetic processing unit 13 performs the third output process as follows. The arithmetic processing unit 13 creates third output data for displaying the third divergence degree of the calculated evaluation period in a predetermined display format from the data transmitting / receiving unit 11 via the predetermined data communication network N. The e-mail message including the third output data is transmitted to the e-mail address registered in advance of the subject. The subject can view the third output data on the display screen of the first user terminal by receiving the electronic mail message at a predetermined first user terminal used by the subject. As an example, the third output data can be simply displayed in a tabular format in the same manner as the first output data described in the first embodiment. Furthermore, as with the browsing option described in the first embodiment, it is also a preferable embodiment to provide a browsing option of the third evaluated behavior pattern and the third divergence degree.

  By viewing the third output data, the subject can objectively check whether or not the activity pattern (movement speed) measured by the positioning sensor 33 has changed from the standard state and the extent thereof.

[Fourth Embodiment]
Next, the system 4 according to the fourth embodiment will be described with reference to FIGS. As in the first embodiment, the system 4 includes a data transmission / reception unit 11, a data storage unit 12, and an arithmetic processing unit 13. In the system 4, the processing content described below is added to the processing content described in the first, second, or third embodiment as the processing content executed to provide the service to the target person.

  In this system 4, each residence 20 includes a power meter 34 that measures a temporal change (power waveform) of an instantaneous value of total power consumption in the residence 20 in at least a part of the plurality of subjects A1 to An. As an example, when the power drawn from the grid power in each residence 20 is a single-layer three-wire AC power, the power meter 34 is connected to the secondary side of the limiter in the distribution board or the secondary side of the main breaker. Each voltage line is provided with an ammeter, and a voltmeter is provided between one voltage line and a neutral line. Further, when the power waveform or current waveform measured by the power meter 34 is sampled at a predetermined timing and cycle according to requirements such as time resolution required for the power waveform or current waveform used in the application decomposition process described later. A waveform conversion unit 35 for converting into digital data (first power consumption data) of a series is connected to the power meter 34.

  As an example, the first power consumption data generated by the waveform converter 35 is collected for a second unit time (for example, 1 to 60 minutes), and is stored in the data relay device 22 for communication with the waveform converter 35. The fourth identification information that can be temporarily recorded in the measurement data recording unit 22b of the data relay device 22 through the separate first communication device 22a provided separately, and that can identify the subject, and the second unit time 4th time information indicating the start time (date and time minutes) is added, and the second power consumption data is obtained every second unit time via the second communication device 22c of the data relay device 22 and the data communication network N. It is transmitted toward the system 4. When the waveform conversion unit 35 includes a storage device and a communication device equivalent to the measurement data recording unit 22b and the second communication device 22c, the second power consumption data is transmitted via the data communication network N. Alternatively, it may be transmitted directly from the waveform conversion unit 35 to the system 4 every second unit time.

  In the present system 4, the human sensor 21 counts the presence / absence of the movement of the subject detected at intervals of 1 second every predetermined first unit time (for example, 1 minute) as described in the first embodiment. The number of operations per minute is configured to be transmitted as first measurement data to the data relay device 22 every minute, and in the residence 20 suitable for deriving the daily activity pattern of the target person. Necessary numbers are installed in predetermined places such as a living room, a bedroom, and a toilet.

  In the first embodiment, after the first measurement data is recorded in the measurement data recording unit 22b, a predetermined time (for example, 1 to 24 hours) is collected, and the first identification information and the first time information are added. Assuming that the second measurement data is transmitted to the system 4 at regular intervals via the second communication device 22c and the data communication network N as regular measurement data. However, in the fourth embodiment, as an example, the predetermined time is not less than the first unit time and not more than the second unit time equal to the transmission interval of the second power consumption data, and the first data performed by the arithmetic processing unit 13 described later. It is preferable to set the second unit time, which is a repetition cycle of the storage process, the fourth data storage process, the activity log data creation process, and the fourth output process.

  Next, in order to provide this service to a target person, the processing contents executed in addition to the processing contents described in the first, second, or third embodiment will be briefly described. In the following description, the processing content for one target person will be described, but the same applies to other target persons.

  In the present system 4, the arithmetic processing unit 13 includes a first data storage process, a fourth data storage process, an activity log data creation process, a standard activity log data creation process, a deviation state report data creation process, a fourth output process, Seven processes of the fifth output process are performed. The first data storage process, the fourth data storage process, the activity log data creation process, and the fourth output process are repeatedly executed every second unit time, and the standard activity log data creation process, the divergence state report data creation process, The fifth output process is executed once a day. The relationship between the processes is as shown in FIG. In the seven processes, the program code of the computer program describing each specific processing content is stored in the storage area of the storage device of the arithmetic processing unit 13, and the arithmetic device executes the program, Executed.

  The arithmetic processing unit 13 performs the first data storage process for each installation location (for example, living room, bedroom, toilet, etc.) of the human sensor 21 in the following manner. In the first data storage process, when the arithmetic processing unit 13 receives the second measurement data for each human sensor 21 from the data relay device 22 via the data transmission / reception unit 2 for each second unit time, It is temporarily stored in the data storage unit 12 so that the human sensor 21 can be identified. Each time the second measurement data is received, the second measurement data is read from the data storage unit 12, and the first measurement data on the processing target date is arranged in time series according to the installation location of the human sensor 21. First time-series data in increments is created and stored in the data storage unit 12. After the second time, the first measurement data in the second measurement data newly received is added to the first time-series data already created on the processing target day every second unit time, and the first time The series data is updated and overwritten and saved in the data storage unit 12.

  The arithmetic processing unit 13 performs the fourth data storage process as follows. In the fourth data storage process, the arithmetic processing unit 13 receives the second power consumption data for each second unit time from the data relay device 22 or the waveform conversion unit 35 via the data transmission / reception unit 2, Is temporarily stored in the data storage unit 12. And every time 2nd power consumption data is received, the 3rd power consumption data which arranged the 1st power consumption data in the 2nd power consumption data for every 2nd unit time for the processing object day in order in time series is created. The data is stored in the data storage unit 12. From the second time onward, for each second unit time, the first power consumption data in the newly received second power consumption data is added to the already created third power consumption data on the processing target day, 3 Updates the power consumption data (corresponding to a part of the fourth time series data) and overwrites and saves it in the data storage unit 12.

  In the fourth data storage process, the arithmetic processing unit 13 performs a predetermined application decomposition process on the third power consumption data on the processing target day that is overwritten and stored in the data storage unit 12 every second unit time. A plurality of electrical devices (for example, an air conditioner, a washing machine, a microwave oven, and a rice cooker) associated with a preset activity pattern in the residence 20 of the target person from the third power consumption data at the time of the application decomposition process on the processing target day Equipment, TV, vacuum cleaner, IH cooking equipment, electric kettle, dryer, electric heater, etc.) 4th power consumption data (corresponding to the other part of the 4th time series data) by equipment Then, the data storage unit 12 overwrites the data.

  Several techniques have already been put into practical use for the application decomposition process, and as an example, an apparatus separation estimation technique provided by Infometis Corporation can be used. The application decomposition process is not limited to the device separation estimation technique as long as it can be applied to the creation of the activity log data in the fourth embodiment.

  The arithmetic processing unit 13 performs activity log data creation processing in the following manner. In the activity log data creation process, the arithmetic processing unit 13 is based on the first time series data, the third power consumption data of the total power consumption, and the fourth power consumption data for each device for each second unit time. Activity log data is created by decomposing the activity content of the subject person's residence 20 on the processing target date into time series for each activity type, and stored in the data storage unit 12. Examples of activity types include, but are not limited to, sleep (from sleeping to waking up), meals (breakfast, lunch, dinner), bathing, toilets, laundry, cleaning, going out, and other homes. Is assumed. Note that activity log data created at an intermediate time point before the end of the processing target day, that is, from the start of the processing target day to an intermediate point in time, corresponds to the intermediate activity log data. In the following description, the intermediate activity log data is referred to as activity log data, as is the activity log data for one day after the end of the processing target day.

  The arithmetic processing unit 13 extracts, from the first time series data, a time zone in which the number of operations per unit time of the human sensor 21 installed at a location related to the activity type is greater than or less than a predetermined number. From the third power consumption data, a time zone in which the total power consumption related to the activity type is small is extracted, and the time zone in which the electrical equipment related to the activity type is operating or the time not operating from the fourth power consumption data Extract the time zone, combine the time zones extracted for each activity type, estimate the activity time zone for each activity type, and create the activity log data by arranging the estimated activity time zones for each activity type in time series To do. FIG. 12 shows an example in which the installation location and judgment criteria of the human sensor 21 used for estimating the activity time zone of the activity type, the judgment criteria of the total power consumption, and the judgment criteria of whether or not the electric device is in operation are arranged according to the activity type. Show.

  The arithmetic processing unit 13 performs the fourth output process as follows. In the fourth output process, the arithmetic processing unit 13 transmits the created activity log data to the first user terminal used by the subject via the data communication network N from the data transmission / reception unit 11 every second unit time. It transmits toward at least any one of the 2nd user terminal registered beforehand used by the subject concerned. As in the first output process described in the first embodiment, the activity log data transmission method transmits an e-mail message including the activity log data to pre-registered e-mail addresses of the target person and related parties. In addition, instead of transmitting the activity log data itself, an email message including the URL of a server on the Internet where the activity log data can be viewed is transmitted, and the target person or related person displays the first or second user terminal. When the URL in the e-mail message is clicked (or touched) on the screen, a browser preinstalled in the first or second user terminal is activated, and a web page for browsing activity log data on the display screen May be displayed. FIG. 13 schematically shows a screen display example of activity log data displayed on the display screen of the first or second user terminal. Note that the screen display example shown in FIG. 13 schematically shows an outline of the activity log data for one day after the processing target day ends.

  Accordingly, the activity log data is notified to at least one of the target person and the related person of the target every second unit time. As a result, the target person can grasp the content of the activity unconsciously in the residence 20 objectively in almost real time, and the target person concerned (such as the guardian of the target person) It is possible to confirm the details of the activities in the house 20 and the health and safety of the subject in almost real time.

  The arithmetic processing unit 13 performs standard activity log data creation processing in the following manner. In the standard activity log data creation processing, the arithmetic processing unit 13 is based on already created activity log data for a predetermined number of days (for example, 5 to 30 days) immediately before the processing target date immediately before the start of the processing target date. The standard activity time zone for each activity type and the number of times if applicable are extracted to create standard activity log data indicating the standard activity contents in the residence 20 of the target person, and the data storage unit 12 To store. Standard activity log data includes, for example, average sleep time, average bedtime, average wake-up time, average mealtime (breakfast, lunch, dinner), average number of meals per day, average mealtime (breakfast, lunch, dinner) , Average bathing time, average number of baths per day, average bathing time zone, average stool time (average toilet usage time), average daily stool frequency (average toilet usage time), average number of washings per day, The average number of cleanings per day, the average number of outings per day, the average outing time, the average outing time zone, and other average at-home time are calculated by a predetermined calculation formula.

  The arithmetic processing unit 13 performs a divergence state report data creation process in the following manner. In the divergence state report data creation process, the arithmetic processing unit 13 performs the activity time zone of each operation type in the activity log data on the processing target day after the processing target day, and the start time, the end time, and the number of times if applicable. Are compared with the corresponding items of the standard activity log data, and the divergence state (difference between the value of each item of the processing target date and the value of the corresponding item of the standard activity log data) is predetermined for each item. When the threshold value is exceeded, the activity type items with a large divergence state are collected in a list, and the divergence state report is reported as the divergence state from the standard activity content of the activity content in the subject's residence 20 on the processing date. Data is created and stored in the data storage unit 12.

  The arithmetic processing unit 13 performs the fifth output process as follows. In the fifth output process, the arithmetic processing unit 13 transmits / receives the divergence state report data generated after the end of the processing target day at a predetermined time (for example, a time preset by the target person) the day after the processing target day. The data is transmitted from the unit 11 to at least one of the first user terminal and the second user terminal via the data communication network N. The transmission method of the deviation state report data uses the same method as the above-described fourth output process. Thereby, the deviation state report data is notified once a day to at least one of the target person and the related person of the target person. As a result, the target person and the related person can objectively grasp to what extent the activity type deviates from the standard activity contents in the activity contents on the previous day of the target person.

[Another embodiment]
Next, modified examples of the above embodiments will be described.

  <1> In the first to third embodiments, the human sensor 21, the human body information sensor 31, and the positioning sensor 33 are used in order to evaluate the activity pattern of the target person. The first standard behavior pattern and the first evaluated behavior pattern for each installation location according to the type of sensor, the second standard behavior pattern and the second evaluated behavior pattern for each type of sensor (motion sensor, heart rate sensor) Although the third standard action pattern and the third evaluated action pattern have been described in detail, the prescribed contents of the standard action pattern and the evaluated action pattern are not limited to the above-described contents.

  For example, the standard action pattern and the evaluated action pattern are basically calculated based on one day, but one day (24 hours) is divided into a plurality of time zones, for example, 0:00 to 6:00, 6:00 to It is divided into four time zones of 12:00, 12:00 to 18:00, and 18:00 to 24:00, and the standard behavior pattern and the evaluated behavior pattern are calculated for each time zone, and the corresponding first to third divergence degrees are also calculated. The calculation may be performed for each time period.

  Furthermore, the first standard behavior pattern and the first evaluated behavior pattern of the living room were calculated as the average activity amount obtained by dividing the total activity amount on the entire day in the pre-processing period and one day in the evaluation period by the total stay time. For example, the number of operations of unit time data is divided into a plurality of levels (for example, 1 to 20, 21 to 40, 41 or more), and the number of unit time data corresponding to each level is set as the stay time for each level. It may be a ratio obtained by dividing the stay time by the total stay time.

  Further, the first standard action pattern and the first evaluated action pattern of the bedroom are obtained from the daily stay start time and the daily stay end time in addition to or instead of the daily stay start time and the daily stay end time. It is good also as the calculated daily stay time. In this case, the first degree of divergence (daily stay time) is, for example, the first evaluated behavior pattern of the bedroom (the daily stay end time) and the first evaluated behavior pattern of the bedroom on the previous day or the previous day. The stay time between (daily stay start time) is the first evaluated action pattern (daily stay time), and the first standard action pattern of the bedroom from the first standard action pattern of the bedroom (bedroom stay start time) ( The stay time until the bedroom stay end time) is defined as a first standard action pattern (daily stay time), which is given as a ratio obtained by dividing the former by the latter, or a difference obtained by subtracting the latter from the former.

  Moreover, the reference | standard which judges that it is one use of the toilet at the time of calculating the 1st standard action pattern and 1st to-be-evaluated action pattern of a toilet is not limited to the reference | standard demonstrated above.

  Furthermore, the second standard action pattern and the second evaluated action pattern of the motion data were calculated as the average activity amount obtained by dividing the total activity amount on the entire day in the pre-processing period and one day in the evaluation period by the total activity time. For example, the number of operations of unit time data may be divided into a plurality of levels, the number of unit time data corresponding to each level may be the activity time for each level, and the ratio obtained by dividing the activity time of each level by the total activity time may be used. .

  Further, the third standard action pattern and the third evaluated action pattern are calculated as the average moving speed obtained by dividing the total moving amount in the entire day in the preprocessing period and one day in the evaluation period by the total moving time. The movement amount of the unit time data may be divided into a plurality of levels, the number of unit time data corresponding to each level may be set as the movement amount time for each level, and the movement amount time of each level may be divided by the total activity time.

  Further, the calculation method of the first to third divergence degrees has also been described for the case where the difference or ratio between the first to third evaluated action patterns and the first to third standard action patterns is calculated. Instead, the ratio may be calculated or vice versa.

  <2> Further, the first standard action pattern and the first evaluated action pattern may be the first unit time (in addition to or instead of the contents defined in the first embodiment and the other embodiment <1>). 1 to 60 minutes) or more time series data (eg, 30 minutes or 1 hour) may be used.

  In this case, for example, the time series data of the first standard action pattern is obtained by dividing the first time series data after correction of each day in the preprocessing period by the above time granularity and averaging the number of operations within each granularity. Further, the average value is averaged over the pretreatment period. Similarly, the time-series data of the first evaluated behavior pattern is calculated by dividing the first time-series data of one day in the evaluation period with the above time granularity and averaging the number of operations within each granularity. The first degree of divergence is the time series data of the difference obtained by subtracting the average number of operations of the first standard action pattern from the average number of operations of the first evaluated action pattern within each granularity, or the first evaluated action Time-series data of a ratio obtained by dividing the average number of movements of the pattern by the average number of movements of the first standard action pattern.

  <3> In the first to third embodiments, the human sensor 21, the human body information sensor 31, and the positioning sensor 33 are used to evaluate the activity pattern of the target person. Other sensors may be used in addition to or instead of each sensor.

  In the second and third embodiments, the human body information sensor 31 and the positioning sensor 33 are treated as separate sensors. However, the human body information sensor 31 and the positioning sensor 33 are mounted as one wearable sensor by the subject. May be. Moreover, the attachment location to the subject of the human body information sensor 31 and the positioning sensor 33 is not necessarily limited to the wrist.

  For example, a measuring instrument that measures the amount of energy used such as electric power or city gas in the residence 20 is provided, and time series data on the amount of energy used is analyzed to analyze a subject's specific activity (for example, cooking , Bathing), the standard action pattern, the evaluated action pattern, and the degree of divergence thereof may be calculated and notified to the subject person.

  Further, a thermo-hygrometer that measures the temperature and humidity of the place where the human sensor 21 in the residence 20 is installed is installed, and the relationship between the first standard action pattern and the first evaluated action pattern, and the temperature and humidity is determined. It is also possible to analyze and notify the subject of the analysis.

  <4> In the first to fourth embodiments, the present system 1 targets a plurality of subjects A1 to An, and each subject can be accessed via a data communication network N such as the Internet. However, as a system for individual subjects, the data transmission / reception unit 11, the data storage unit 12, and the arithmetic processing unit 13 are provided in the confirmation terminal or the first user terminal used by each subject. Also good. In this case, communication via the data communication network N such as the Internet between the system 1 and the confirmation terminal or the first user terminal used by the subject is not necessary.

  <5> In the fourth embodiment, the arithmetic processing unit 13 is configured to execute not only the processing content described in the fourth embodiment but also the processing content described in the first, second, or third embodiment. However, only the processing contents described in the fourth embodiment may be executed.

  <6> In the activity log data creation process of the fourth embodiment and the modification <5>, before the created activity log data is transmitted to the first or second user terminal by the fourth output process, If there is an error in the activity type (estimated activity type or its activity time zone) decomposed in time series in the activity log data with respect to the created activity log data, the error location in the activity log data is indicated. The fourth confirmation data that can be corrected by the subject person is created, and the created fourth confirmation data is transmitted from the data transmission / reception unit 11 to the predetermined confirmation terminal used by the subject person via the data communication network N. This is also a preferred embodiment. In this case, the fourth confirmation data transmission process may be performed in the same manner as the first confirmation data transmission process described in the first embodiment.

  After the fourth confirmation data transmission process, when the fourth confirmation data received by the confirmation terminal is displayed on the display screen of the confirmation terminal, the error part can be corrected or deleted by manual operation of the subject. It becomes. Specifically, as an example, the fourth confirmation data has a screen configuration in which activity types similar to the screen display example of the activity log data schematically shown in FIG. 13 are arranged in time series. When the activity type of the error part is selected by clicking or tapping with a mouse or a finger, for example, the name of the selected activity type, the start time (hour / minute) and end time ( Hour and minute) are displayed. If you want to delete the selected activity type, click or tap the delete button, and if you want to modify either the name of the selected activity type, the start time or end time of the activity time zone, The correct part can be corrected by inputting a correct name or time directly or by operating a pull-down menu or the like to the correction part.

  In this modification <6>, the fourth confirmation data that has been corrected due to the presence of an error location, or the fourth confirmation data that has been confirmed to have no error location is used as the fourth confirmed data. Is transmitted from the confirmation terminal to the system 4 through the data communication network N.

  On the system 4 side that has received the fourth confirmed data, if at least one of the activity types decomposed in time series has been modified or deleted in the fourth confirmed data, the modification or deletion is performed. The created activity log data is modified based on the contents, and if the modification or deletion is not performed, the created activity log data is not modified and is used as the activity log data for the fourth output process.

  By adding a series of processes of creation and transmission of the fourth confirmation data, reception of the fourth confirmed data, and modification of the activity log data in the modification <6> to the activity log data creation process, Data estimation accuracy is improved. Furthermore, the accuracy of the estimation logic or rule is improved by learning the estimation logic or rule used in the activity log data creation process by feedback on the fourth confirmation data by the target person, and as a result, the estimation of the activity log data is performed. Accuracy is improved.

  <7> In the fourth embodiment and the modification <5>, the case where the standard activity log data creation process, the deviation state report data creation process, and the fifth output process are executed once a day has been described. The number of times of the three series of processes does not necessarily have to be once a day, and may be a plurality of times a day, for example, every second unit time, It may be once a day, or may be an embodiment that is not performed at all.

  <8> In the fourth embodiment and the modified example <5>, the first data storage process, the fourth data storage process, the activity log data creation process, and the fourth output process are performed on the processing target day. Although the case where the processing is repeatedly executed every unit time has been described, the number of processing times of the four series of processing is preferably a plurality of times per day, but is not necessarily a plurality of times per day. Alternatively, it may be once every multiple days.

  <9> In the fourth embodiment and the modified example <5>, the arithmetic processing unit 13 performs first time-series data, third power consumption data of total power consumption, The case where activity log data is created based on the fourth power consumption data has been described. However, it is also preferable that the arithmetic processing unit 13 uses other data in addition to the first time series data, the third power consumption data, and the fourth power consumption data for estimating the activity type and the activity time zone. . By adding the other data, it is expected to improve the estimation accuracy of the activity type and the activity time zone.

As an example, a temperature / humidity sensor, an illuminance sensor, a CO ₂ sensor, a sound pressure or noise sensor are installed at a place where the human sensor 21 is installed in the house 20 or a place where the human sensor 21 is not installed. At least one of the detection data of the sensors is used as the other data.

  The detection data of the temperature / humidity sensor can be used to estimate the operating state of a heating device other than the electric heater. Further, when it is difficult to extract the fourth power consumption data of the electric heater, it can be used to estimate the operating state of the electric heater. For example, when an increase in room temperature in a kitchen, living room, or the like is detected in the morning wake-up time period in winter, the detected content can be used for estimating the wake-up time. Furthermore, in the winter season, for subjects who are in the habit of heating the bedroom during sleep, if a decrease in the temperature of the bedroom is detected during the morning wake-up period, the detected content is estimated as the wake-up time. Available to:

  The detection data of the illuminance sensor can be used for estimation of lighting on / off, shutter opening / closing, and the like. In other words, since it is possible to estimate that the target person has turned on / off the lighting or opening / closing the shutter from the detection data of the illuminance sensor, the illuminance sensor is temporarily installed in a place where the human sensor 21 is not installed. If it is, it can be used to estimate the presence of the subject at the place where the illuminance sensor is installed.

Detecting data of CO ₂ sensor, the subject's breath reaction in the installation location of the CO ₂ sensor, and can be used to estimate the increase in CO ₂ concentration by the use or the like of the gas appliances or kerosene equipment. That is, the detection data of CO ₂ sensors can be used to estimate the presence of the subject at approximately the location of the CO ₂ sensor.

  The detection data of the sound pressure or noise sensor is based on the presence of the subject at the place where the sound pressure or noise sensor is installed It can be used to estimate the situation and the viewing situation of a television or audio equipment.

  Furthermore, as another example, in addition to or instead of installing any one of the sensors other than the human sensor 21 in the residence 20, a unit time (for example, 1 to 15) of the total gas consumption in the residence 20 The gas meter which measures the time change for every minute) is provided in the residence 20, or the processing unit 13 uses the function of the gas meter built in the water heater or the like to measure the gas meter. Predetermined use decomposition processing for the gas consumption is performed on the total gas consumption data on the target day, and the preset residence 20 of the target person is calculated from the total gas consumption data at the time of the use decomposition processing on the processing target day. Gas consumption data for each device that is consumed by multiple gas appliances (eg gas cooking appliances, hot water bath tubs, heating appliances, bathroom dryers, etc.) related to activity patterns And total Consumption data and device-specific gas consumption data are stored in the data storage unit 12, and together with the first time series data, the third power consumption data, and the fourth power consumption data, the total gas consumption data and the device-specific data are stored. It is also a preferred embodiment to use the gas consumption data to estimate the activity type and its activity time zone.

  This system includes a self-management support system that notifies the target person of deviations from the standard state in the daily activity pattern of the target person, and the target person's daily activity pattern It can be used for a self-management support system that notifies

1-3: Self-management support system 11: Data transmission / reception unit 12: Data storage unit 13: Arithmetic processing unit 20: Subject's residence 21: Human sensor 22: Data relay device 22a: First communication device 22b: Measurement data recording Unit 22c: Second communication device 23, 24: First confirmation data input field 31: Human body information sensor 32: Data relay device 33: Positioning sensor 34: Power meter 35: Waveform conversion unit A1 to An: Target person C: Communication Route N: Data communication network (Internet)

Claims (17)

A self-management support system for notifying the subject of deviations from the standard state in the daily activity pattern of the subject, comprising a data transmission / reception unit, a data storage unit, and an arithmetic processing unit, wherein the arithmetic processing unit is ,
Measurement data of the number of motions of the subject sensed by the motion sensor from a motion sensor that senses the motion of a person installed at one or more predetermined positions in the residence of the subject, the data transmission / reception unit A first data storage process for sequentially receiving at a predetermined reception timing via the first time series data of a predetermined first unit time step every day of the number of operations, and storing the first time series data in the data storage unit;
Based on the first time-series data of the preprocessing period over a plurality of days, first confirmation data is generated that can identify a place where the subject is judged not to be in a standard state, collectively or divided into a plurality of times. A first confirmation data transmission process for transmitting the first confirmation data to the predetermined confirmation terminal used by the subject via the data transmission / reception unit;
When receiving the input of the first confirmed data from the confirmation terminal via the data transmitter / receiver, the location where the subject determined that the subject is not in the standard state with respect to the first confirmation data is received, If the first time-series data is corrected based on 1 confirmed data, and the input of the first confirmed data is not received from the confirmation terminal based on the corrected first time-series data, A first standard action pattern indicating a first standard state of the activity pattern of the target person is derived based on the first time-series data of the preprocessing period that was initially created, and is stored in the data storage unit. 1 standard state derivation process;
Based on the first time-series data of a predetermined evaluation period of one day or a plurality of days, a first evaluated action pattern to be evaluated for the activity pattern of the target person is derived, and the first evaluated action pattern A first divergence generation process for deriving a predetermined first divergence from the first standard action pattern of
First output data including the first divergence degree is created, the first output data is transmitted to a predetermined first user terminal via the data transmission / reception unit, and the first divergence degree is determined as the target person. First output processing to notify to,
A self-management support system characterized by being configured to execute. The first standard behavior pattern is the first of the subject within a perceivable range of human motion at a location where the human sensor is installed in a predetermined time zone of one or more of each day of the pre-processing period. The first total activity time in which the first activity time in which the number of operations per unit time is equal to or greater than a predetermined reference value is totaled within the preprocessing period, and is the sum of the number of operations in the first total activity time. Including the first average activity amount minus the total activity amount,
In the first evaluated behavior pattern, the number of movements of the subject per first unit time within the perceivable range in the one or more predetermined time zones of the evaluation period is greater than or equal to the reference value. 2. The self-management support system according to claim 1, further comprising a second average activity amount obtained by dividing a second total activity amount, which is a total of the number of operations in the second activity time, in two activity hours. The first standard behavior pattern is based on the number of movements of the target person per the first unit time within a perceivable range of human movements at the location where the human sensor is installed on each day of the preprocessing period. A predetermined first statistic value in the whole period of the pre-processing period with respect to the daily stay start time and the daily stay end time calculated as follows:
The self-management support system according to claim 1, wherein the first evaluated behavior pattern includes the daily stay start time and the daily stay end time in the evaluation period. The first standard behavior pattern is based on the number of movements of the target person per the first unit time within a perceivable range of human movements at the location where the human sensor is installed on each day of the preprocessing period. A predetermined second statistic value in the whole preprocessing period with respect to the daily usage count calculated in
The self-management support system according to any one of claims 1 to 3, wherein the first evaluated behavior pattern includes the number of daily usages during the evaluation period. The human sensor is a human sensor installed in at least one of a living room, a toilet, and a bedroom in the subject's residence,
The self-management support system according to any one of claims 1 to 4, wherein the first time-series data is created for each installation location of the human sensor.   The self-management support system according to any one of claims 1 to 5, wherein the predetermined first unit time is 1 minute or more and 60 minutes or less.   The first standard action pattern and the first evaluated action pattern each include time-series data having a temporal granularity that is the same as or coarser than the temporal granularity of the first time-series data. 7. The self-management support system according to any one of items 6.   The arithmetic processing unit further generates action pattern comparison data for comparing and displaying the first standard action pattern and the first evaluated action pattern in a predetermined display format as part or all of the first output data. The self-management support system according to any one of claims 1 to 7, wherein the system is configured as described above. The arithmetic processing unit further includes:
The human body information of the subject from a human body information sensor that can be worn on the human body to detect human body information including at least one of one or more biological information and acceleration information of the subject by being worn by the subject. At a predetermined reception timing via the data transmission / reception unit, and a predetermined value for one measurement value for each first unit time or a plurality of measurement values for each first unit time for each type of human body information. Based on the third statistic value, the second time series data of the measurement value or the third statistic value in the first unit time step for each day is created for each type of the human body information and stored in the data storage unit A second data storage process,
Based on the second time-series data of the pre-processing period, a second confirmation data is generated that can identify a place where the target person judges not to be in a standard state in a batch or a plurality of times, and the data A second confirmation data transmission process for transmitting the second confirmation data to the confirmation terminal via a transceiver;
When the second confirmed data is received from the confirmation terminal via the data transmitting / receiving unit, the second confirmed data can be identified where the subject has determined that the subject is not in the standard state. 2 If the second time series data is corrected based on the confirmed data, based on the corrected second time series data, and the input of the second confirmed data is not received from the confirmation terminal, A second standard action pattern indicating a second standard state of the activity pattern of the target person is derived based on the second time-series data of the preprocessing period that was initially created, and is stored in the data storage unit. 2 standard state derivation processing;
Based on the second time-series data of the evaluation period, a second evaluated action pattern that is an evaluation target of the activity pattern of the target person is derived, and the second standard action pattern of the second evaluated action pattern A second divergence creation process for deriving a predetermined second divergence from
The second output data including the second divergence degree is generated, the second output data is transmitted to the first user terminal via the data transmission / reception unit, and the second divergence degree is transmitted to the target person. A second output process to notify;
The self-management support system according to claim 1, wherein the self-management support system is configured to execute the following. The arithmetic processing unit further includes:
From the positioning sensor that can be worn on the human body to detect the geographical position information of the subject outside the residence by being worn by the subject, the geographical position information of the subject is sent to the data transmission / reception unit. The activity content outside the residence of the target person by calculating the movement distance for each first unit time based on the geographical position information, and identifying the activity content outside the residence A third data storage process for creating third time-series data in units of the first unit time every day and storing the data in the data storage unit;
Based on the third time-series data of the pre-processing period, a third confirmation data is generated that can identify a place where the subject is determined not to be in a standard state, collectively or divided into a plurality of times, and the data A third confirmation data transmission process for transmitting the third confirmation data to the confirmation terminal via a transceiver;
When receiving the input of the third confirmed data from the confirmation terminal via the data transmission / reception unit, the location where the subject determined that the subject is not in the standard state with respect to the third confirmation data is received. 3 If the third time series data is corrected based on the confirmed data, based on the corrected third time series data, and the input of the third confirmed data is not received from the confirmation terminal, A third standard action pattern indicating a third standard state of the activity pattern of the target person is derived based on the third time-series data of the preprocessing period that was initially created, and is stored in the data storage unit. 3 standard state derivation processing;
Based on the third time-series data of the evaluation period, a third evaluated action pattern to be evaluated for the activity pattern of the target person is derived, and the third standard action pattern of the third evaluated action pattern A third divergence creation process for deriving a predetermined third divergence from
The third output data including the third divergence degree is created, the third output data is transmitted to the first user terminal via the data transmission / reception unit, and the third divergence degree is transmitted to the target person. A third output process to notify;
The self-management support system according to claim 1, wherein the self-management support system is configured to execute. The arithmetic processing unit further includes:
A use decomposition process is performed on the power consumption in the target person's residence, and the time transition of the power consumption of a plurality of electrical devices related to the activity pattern in the residence of the target person is specified for each device. A fourth data storage process for creating fourth time-series data in predetermined second unit time increments on a processing target day of power consumption and power consumption by each electrical device, and storing the fourth time-series data in the data storage unit;
Based on the first time-series data and the fourth time-series data, activity contents in the subject person's residence on the processing target date are decomposed into time series for each activity type, and activity log data is created, Activity log data creation processing to be stored in the data storage unit;
The activity log data is transmitted to at least one of the first user terminal and a pre-registered second user terminal via the data transmission / reception unit, and the activity log data is pre-registered with the target person. A fourth output process for notifying at least one of the related parties of the target person;
The self-management support system according to claim 1, wherein the self-management support system is configured to execute the following. A self-management support system for notifying the subject of daily activity patterns of the subject, comprising a data transmission / reception unit, a data storage unit, and an arithmetic processing unit, the arithmetic processing unit,
Measurement data of the number of motions of the subject sensed by the motion sensor from a motion sensor that senses the motion of a person installed at one or more predetermined positions in the residence of the subject, the data transmission / reception unit A first data storage process in which the first time-series data is generated at a predetermined first unit time interval on the processing target date of the number of operations, and is stored in the data storage unit. ,
A use decomposition process is performed on the power consumption in the target person's residence, and the time transition of the power consumption of a plurality of electrical devices related to the activity pattern in the residence of the target person is specified for each device. A fourth data storage process for creating fourth time-series data in predetermined second unit time increments on a processing target day of power consumption and power consumption by each electrical device, and storing the fourth time-series data in the data storage unit;
Based on the first time-series data and the fourth time-series data, activity contents in the subject person's residence on the processing target date are decomposed into time series for each activity type, and activity log data is created, Activity log data creation processing to be stored in the data storage unit;
The activity log data is transmitted to at least one of the first user terminal and a pre-registered second user terminal via the data transmission / reception unit, and the activity log data is pre-registered with the target person. A fourth output process for notifying at least one of the related parties of the target person;
A self-management support system characterized by being configured to execute.   In the activity log data creation process, the arithmetic processing unit is the activity content in the residence of the target person from the start to the midpoint of the processing target date before the end of the processing target date, or the processing target date When there is an error in the activity type decomposed in time series with respect to the activity content in the subject person's residence on the processing target date after the end of the subject, the subject person determines the activity type and its activity time zone. The fourth confirmation data that can be corrected is created, and the fourth confirmation data is transmitted to the predetermined confirmation terminal used by the subject via the data transmitting / receiving unit, and the fourth confirmation data is transmitted to the fourth confirmation data. When the target person receives the input of the fourth confirmed data obtained by correcting the activity type or the activity time zone from the confirmation terminal via the data transmission / reception unit, based on the fourth confirmed data, Self-management support system according to claim 11 or 12 other is characterized by modifying the activity log data after creation.   In the activity log data creation process, the arithmetic processing unit is configured to perform the process based on an installation location of the human sensor and a time zone in which the number of operations is equal to or more than a predetermined number and an operation time for each electric device. The self-management support system according to any one of claims 11 to 13, wherein an activity time zone for each activity type on a target date is extracted and decomposed for each activity type of the activity content. The arithmetic processing unit further includes:
Based on the activity log data over a plurality of days, a standard activity time zone for each activity type is derived, and standard activity log data indicating standard activity contents in the residence of the subject is created. , Standard activity log data creation processing to be stored in the data storage unit,
A divergence state in which the standard activity log data is compared with the activity log data on the processing target date to report a divergence state from a standard activity content of the activity content in the subject person's residence on the processing target date Creating divergence state report data to create report data and storing it in the data storage unit;
The divergence state report data is transmitted to at least one of the first user terminal and the second user terminal via the data transmitting / receiving unit, and the divergence state report data is transmitted to the target person and the related parties. A fifth output process for notifying at least one of them;
The self-management support system according to claim 11, wherein the self-management support system is configured to execute the following.   In the divergence state report data creation process, the arithmetic processing unit performs a standard activity time zone for each activity type recorded in the standard activity log data, and an activity time for each activity type on the processing target date. If the difference in the length of the activity time zone, or the difference in the start time or end time of the activity time zone exceeds a predetermined threshold, the divergence state report data includes 16. The self-management support system according to claim 15, including the activity type exceeding the threshold and the activity time zone. The arithmetic processing unit is
In the activity log data creation process, without waiting for the end of the processing target day, the activity contents in the residence of the target person from the start to the midpoint of the processing target day are decomposed into time series by activity type. Intermediate activity log data is created, and the intermediate activity log data is sequentially updated,
In the fourth output process, each time the intermediate activity log data is updated, the intermediate activity log data is transmitted to at least one of the first user terminal and a pre-registered second user terminal. The self-management support system according to any one of claims 11 to 16.

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