JP2022021169A - Output device - Google Patents

Abstract

To improve accuracy of detecting a trend of user's cognitive function.SOLUTION: An output device includes: an acquisition unit 122 for acquiring a first feature amount relating to movement of a user; and an output unit 126 for outputting information in accordance with a trend of user's cognitive function that is detected in accordance with a relationship between the first feature amount and a second feature amount relating to movement of other users different from the user.SELECTED DRAWING: Figure 2

Description

The present disclosure relates to a technique for providing information according to a tendency of a user's cognitive function.

Technology for detecting trends in the cognitive function of users is known. For example, in Patent Document 1, when the value of the frequency of erroneous operations performed by the user using the portable information processing device is higher than the disease tendency determination value obtained from the average value of the frequencies of erroneous operations in the past, it is predetermined. Techniques for estimating disease trends are described. Patent Document 2 compares the schedule of the subject with the detection result of the behavior of the subject, and states that dementia is suspected when the number or rate of the subjects not acting according to the schedule increases. The technology for notifying is described.

Japanese Unexamined Patent Publication No. 2006-141804 Japanese Unexamined Patent Publication No. 2016-221088

For example, as in the technique described in Patent Document 2, when detecting a decrease in cognitive function according to a relationship between a predetermined action schedule and an actually performed action, the accuracy of detecting the tendency of cognitive function is high. May be low.
One of the purposes of the present disclosure is to improve the accuracy of detecting the tendency of the cognitive function of the user.

One form of the present disclosure is an acquisition unit that acquires a first feature amount related to the movement of a user, the first feature amount, and a second feature amount related to the movement of another user different from the user. Provided is an output device including an output unit that outputs information according to the tendency of the user's cognitive function detected according to the relationship.

The first feature amount includes the number of points where the user stayed, the similarity of the points, the number of new points where the user stayed, the number of visits to the points where the user frequently stays, and a plurality. It may include at least one of the number of divided regions passed by the user on the ground surface divided into the divided regions and the number of new divided regions passed by the user on the ground surface.

The first feature amount may include at least one of the maximum value, the average value, the median value, and the value indicating the variation of the movement speed of the user.

The first feature amount may include at least one of the length of time the user has gone out, the time zone of going out, and the number of times the user has gone out.

The output device further includes a detection unit that detects the tendency of the user's cognitive function depending on whether or not the first feature amount satisfies the condition indicating the tendency of the cognitive function to decrease. It may be determined according to the second feature amount.

The other user may include a person with reduced cognitive function.

The output device further includes a calculation unit that calculates an evaluation value according to whether or not the first feature amount satisfies the condition, and the detection unit is described when the evaluation value is equal to or more than a threshold value. A tendency of cognitive decline may be detected.

The acquisition unit acquires a plurality of first feature amounts related to the movement of the user, and the calculation unit evaluates that the number of the first feature amounts satisfying the above conditions among the plurality of first feature amounts increases. The evaluation value may be calculated so that the value becomes large.

According to the present disclosure, it is possible to improve the accuracy of detecting the tendency of the cognitive function of the user.

It is a figure which shows an example of the hardware composition of the system 100 which concerns on one Embodiment of this disclosure. It is a figure which shows an example of the functional structure of the system 100 which concerns on one Embodiment of this disclosure. It is a figure which shows an example of the contract information and the hobby taste information which concerns on one Embodiment of this disclosure. It is a figure which shows an example of the feature amount about the use of the user terminal 110 which concerns on one Embodiment of this disclosure. It is a figure which shows an example of the feature amount about the use of the user terminal 110 which concerns on one Embodiment of this disclosure. It is a figure which shows an example of the screen which is displayed on the user terminal 110 when the tendency of deterioration of a cognitive function is detected. It is a figure which shows an example of the hardware composition of the user terminal 110 which concerns on one Embodiment of this disclosure. It is a figure which shows an example of the hardware composition of the server apparatus 120 which concerns on one Embodiment of this disclosure. It is a sequence chart which shows an example of the operation of the system 100 which concerns on one Embodiment of this disclosure. It is a figure which shows an example of the radar chart which concerns on one modification of this disclosure.

1. 1. Configuration Figure 1 is a diagram showing an example of the hardware configuration of the system 100 according to the embodiment of the present disclosure. The system 100 provides services according to the tendency of the user's cognitive function. When cognitive function declines, for example, memory disorder, disorientation disorder, executive function disorder, comprehension or judgment ability disorder, and calculation ability disorder appear. In addition to these core symptoms, peripheral symptoms such as emotional disorders, depression, violence or abuse, hallucinations or auditory hallucinations may appear. Conditions with reduced cognitive function include dementia and mild cognitive impairment (MCI), which is the pre-stage of dementia. Mild cognitive impairment has decreased cognitive function, but the symptoms are still mild and do not cause difficulty in daily life. However, according to an estimate released by the Ministry of Health, Labor and Welfare in 2013, it is said that about 50% of people will develop dementia in 5 years if mild cognitive impairment is left untreated. It has been reported, and the probability of developing dementia after that is very high. In addition, once dementia develops, it can be delayed in progression, but it is basically difficult to cure. On the other hand, according to the Japanese Society of Neurology's Dementia Disease Practice Guidelines 2017, it is said that about 30% of people will be able to recover to healthy people if appropriate measures are taken at the stage of mild cognitive impairment. Therefore, it is important to detect the decline in cognitive function at the stage of mild cognitive impairment and take appropriate measures.

By the way, the feature amounts of various data obtained about the user terminal 110 that the user usually uses are different between the user with the normal cognitive function and the user with the deteriorated cognitive function. .. By using this difference, it is possible to detect the tendency of the user's cognitive function. Therefore, the system 100 detects the tendency of the cognitive function of the user by using the data obtained about the user terminal 110, and provides the information according to the tendency. By providing this information, the user can grasp the tendency of his / her cognitive function and take appropriate measures according to the tendency of his / her cognitive function at an appropriate time.

The system 100 includes a plurality of user terminals 110 and a server device 120. These devices are connected via the network 105. The user carries and uses the user terminal 110. As the user terminal 110, for example, a smartphone, a feature phone, or a wearable terminal is used. The network 105 includes at least one of a wired network and a wireless network.

FIG. 2 is a diagram showing an example of the functional configuration of the system 100 according to the embodiment of the present disclosure. The user terminal 110 has a function of providing the server device 120 with a usage history 114, which is a history of the user using the user terminal 110. The user terminal 110 is an example of the terminal device according to the present disclosure. The user terminal 110 functionally has a transmission unit 111, a reception unit 112, and a display control unit 113. Further, the usage history 114 is stored in the user terminal 110.

The usage history 114 includes, for example, a history of various operations, a sensor history showing measurement results of various sensors, a usage history of various application programs (hereinafter referred to as "apps"), and a call history.

The operation history includes, for example, the identifier of the operation, the content of the operation, and the start date and time and end date and time of the operation. The operation includes, for example, an operation of unlocking the screen, an operation of starting an application, and an operation of inputting characters. Screen lock is a function that restricts operations on the touch panel. When the screen is locked, the user terminal 110 does not accept the operation of the touch panel. To unlock the screen, special operations such as inputting a passcode and biometric authentication are required. When an operation for inputting characters is performed, the operation history includes the date and time when the operation for inputting, deleting, or converting characters is performed. This character contains the passcode used to unlock the screen.

The sensor history includes, for example, a history of position information indicating the position of the user, a history of acceleration of the user terminal 110, a history of angular velocity of the user terminal 110, a history of the number of steps of the user, and a history of atmospheric pressure around the user terminal 110. Is included.

The usage history of the application includes, for example, the identifier of the application, and the start date and time and end date and time of the application. This app includes, for example, a communication app, a pre-installed app, a mail app, an SMS (Short Message Service) app, a browser, a memo app, a calendar app, an alarm app, a help page display app, a clock app, and a map app. A communication app is an app that provides a function to communicate with others. Communication apps include, for example, LINE®. The pre-installed application is an application pre-installed on the user terminal 110. However, at least a part of the applications pre-installed on the user terminal 110 may be classified as an application other than the pre-installed application such as a communication application. The communication app and the pre-installed app are examples of specific programs related to this disclosure. When the mail application or SMS application is used, the usage history of the application includes the transmission date and time and reception date and time of the e-mail or short message, and the editing start date and time and editing end date and time of the e-mail or short message. When the browser is used, the usage history of the application includes the history of the URL (Uniform Resource Locator) accessed through the browser.

The call history includes, for example, the date and time of making and receiving a call, the call duration of the call, and the history of the volume of the voice of the user during the call.

The transmission unit 111 transmits the usage history 114 to the server device 120. The receiving unit 112 receives information from the server device 120 according to the detection result of the tendency of the user's cognitive function. The display control unit 113 controls the display of the screen according to the information received by the reception unit 112.

The server device 120 has a function of detecting a tendency of the user's cognitive function based on the usage history 114 of the user terminal 110 and outputting information according to the tendency. The server device 120 is an example of the output device according to the present disclosure. Functionally, the server device 120 includes a receiving unit 121, an acquisition unit 122, a determination unit 123, a calculation unit 124, a detection unit 125, and an output unit 126.

The receiving unit 121 receives the usage history 114 from the user terminal 110. The usage history 114 is stored in the server device 120 together with the usage history 114 of other users. Further, the receiving unit 121 receives the user's contract information and hobby / preference information from an external device (not shown). The server device 120 may store contract information and hobby / preference information of all users. In this case, the user's contract information and hobby / preference information are extracted from the contract information and hobby / preference information of all users.

FIG. 3 is a diagram showing an example of contract information and hobby / preference information according to an embodiment of the present disclosure. The contract information is information indicating the contents of the usage contract of the user terminal 110 made by the user. The contract information includes, for example, the date of birth, age, gender, address of the user, the period of use of the user terminal 110, and the type of the user terminal 110. The usage period may be expressed by dividing the period, for example, 0 to 3 months, 4 months to 7 months. Types of user terminals 110 include, for example, smartphones and feature phones. Hobby / preference information is information indicating a user's hobby or preference. Hobby / preference information includes information indicating paid services subscribed to by the user, category information of the menu of the portal site used by the user, and the user purchasing a product using a specific point or a specific credit card. Contains purchasing information that shows the history of purchases. Paid services include, for example, video distribution services. The purchase information includes, for example, the name of the store where the product was purchased, the date and time when the product was purchased, and the price of the product.

The acquisition unit 122 statistically analyzes the usage history 114 and acquires the feature amount of the user regarding the use of the user terminal 110. This feature amount is an example of the first feature amount according to the present disclosure. 4 and 5 are diagrams showing an example of a feature amount relating to the use of the user terminal 110 according to the embodiment of the present disclosure. This feature amount includes, for example, a feature amount related to screen unlock, a feature amount related to the movement of a user, a feature amount obtained from a sensor, a feature amount related to the use of an application, a feature amount related to character input, a feature amount related to a call, and an environment. Features are included. Further, the feature amount may include the above-mentioned contract information and hobby / preference information.

The feature amount related to screen unlock includes, for example, the number of times the screen is unlocked, the time required to unlock the screen, and the time from when the screen is unlocked until the application is started. The number of times the screen is unlocked means the number of times the screen is successfully unlocked. However, in addition to or instead of the number of successful screen unlocks, at least one of the number of failed screen unlocks and the number of attempts to unlock the screen may be used as the number of times related to unlocking the screen. .. The number of attempts to unlock the screen is the total number of times the screen unlock is successful and the number of times the screen unlock fails. The time required for unlocking the screen includes, for example, at least one of a representative value of the time required for unlocking the screen and a spraying value indicating a variation in the time. Representative values include, for example, at least one of maximum, mean, and median. The spray value includes, for example, at least one of variance, standard deviation, and standard error. Similarly, the time from the release of the screen lock to the start of the application is, for example, the representative value of the time from the release of the screen lock to the start of the application and the dispersion value indicating the variation of this time. At least one of them is included. The application is started according to the user's operation after the screen lock is released.

The feature amount related to screen unlock is generated based on, for example, at least one of the operation history of the operation for unlocking the screen and the usage history of the application. For example, the number of times the screen is unlocked and the time required to unlock the screen are counted based on the start date and time and the end date and time of the operation for unlocking the screen, respectively. The time from the release of the screen lock to the start of the application is counted based on, for example, the end date and time of the operation for releasing the screen lock and the start date and time of the application.

The frequency of screen unlock failures can be inferred from the number of screen unlocks. For example, if the number of times the screen is unlocked tends to increase, the frequency of failure to unlock the screen may increase. Further, the amount of use of the user terminal 110 by the user can be known from the number of times the screen is unlocked. For example, when the number of times the screen is unlocked is relatively small, it can be seen that the user does not use the user terminal 110 very much. From the time required to unlock the screen, you can see the frequency of incorrect entry of the passcode. For example, if the time required to unlock the screen is relatively long, it can be seen that there are many erroneous input of the passcode. From the time from when the screen lock is released until the application is started, it is possible to know whether or not the user remembers the application to be started. For example, if the time from when the screen lock is released until the application is started is relatively long, it can be seen that the user does not remember the application to be started very much.

The feature quantities related to the movement of the user include, for example, the number of points where the user stayed (hereinafter referred to as "stay points"), the similarity of the stay points, and the new points where the user stayed (hereinafter, "new stay"). Number of "points"), number of visits to points where users frequently stay, number of meshes passed by users, number of new meshes passed by users (hereinafter referred to as "new meshes") , The similarity of the mesh pattern passed by the user, the movement speed, the time when the user goes out, the number of times the user goes out, the time when the user stays at home, the number of times when the user enters the dangerous area, and the distance traveled per unit period. included. The mesh is a rectangular division area obtained by dividing the ground surface into a mesh shape. The moving speed includes, for example, at least one of a representative value of the moving speed and a spraying value indicating variation. Representative values include, for example, at least one of maximum, mean, and median. The spray value includes, for example, at least one of variance, standard deviation, and standard error. The user's outing time includes, for example, at least one of the length of time the user has gone out and the time zone in which the user has gone out. Similarly, the time spent at the user's home includes, for example, at least one of the length of time the user stayed at home and the time zone during which the user stayed at home. The travel distance per unit period includes, for example, at least one of a representative value of the travel distance per day or a week and a spray value indicating variation.

The feature amount related to the movement of the user is generated based on, for example, at least one of the history of position information, the history of acceleration, and the contract information. For example, the number of points of stay, the similarity of points of stay, the number of new points of stay, the number of visits to points where users frequently stay, the number of meshes passed by users, the number of new meshes passed by users, The similarity of the mesh pattern passed by the user, the time when the user goes out, the number of times the user goes out, the number of times when the user enters the dangerous area, and the distance traveled per unit period are counted based on the history of the location information. The moving speed is calculated based on, for example, the history of position information or the history of acceleration. The time spent at the user's home is counted based on, for example, the history of location information and the location of the user's home. The location of the user's home may be estimated, for example, by analyzing the history of location information, or may be determined from the address included in the contract information.

Number of points of stay, similarity of points of stay, number of new points of stay, number of visits to points where users frequently stay, number of meshes passed by users, number of new meshes passed by users, use The movement pattern and activity amount of the user can be known from at least one of the similarity of the mesh patterns passed by the user, the time when the user goes out, the number of times the user goes out, and the distance traveled per unit period. For example, the number of staying points, the number of new staying points, the number of visits to the points where the user frequently stays, the number of meshes passed by the user, the number of new meshes passed by the user, the time when the user goes out, etc. When at least one of the number of times the user goes out and the distance traveled per unit period is relatively small, it can be seen that the user does not go out much. Further, when at least one of the similarity of the mesh pattern passed by the user and the similarity of the staying point is relatively high, it can be seen that the user is only out of a specific place. From at least one of the representative value of the moving speed and the spraying value indicating the variation, it is possible to know the moving means used by the user and whether or not the user is out. For example, if the maximum value of the moving speed is relatively small, it can be seen that the vehicle is not used as the means of transportation. When the spray value indicating the variation in the moving speed is relatively small, it can be seen that only a specific moving means is used.

The feature amount obtained from the sensor includes, for example, the acceleration of the user terminal 110, the angular velocity of the user terminal 110, the number of steps of the user, and the recognition result of the moving means used by the user. The means of transportation used by the user include, for example, walking, buses, and trains.

The feature amount obtained from the sensor is generated based on, for example, the sensor history. For example, for acceleration, an acceleration history statistic is used. For the angular velocity, for example, a statistic of the history of the angular velocity is used. For the number of steps, for example, a statistic of the history of the number of steps is used. The means of transportation is recognized from the moving speed of the user using, for example, known techniques.

The amount of activity of the user can be known from at least one of the acceleration, the number of steps, and the recognition result of the means of transportation. For example, when the acceleration is relatively small, it is considered that the user does not go out on a vehicle such as a bus or a train, so that it can be seen that the user is not very active. For example, even when the recognition result of the means of transportation indicates walking, it is considered that the user does not go out on a vehicle such as a bus or a train, so that it can be seen that the user is not acting very actively. For example, when the number of steps is relatively small, it is considered that the user does not go out so much, so it can be seen that the user is not acting very actively. From the angular velocity, the amount of the user using the user terminal 110 can be known. For example, when the angular velocity is relatively low, it is considered that the user does not carry the user terminal 110 so much, so that it can be seen that the user terminal 110 is not used much.

The feature quantities related to the use of the app include, for example, the number of times the app has been used, the time the app has been used, the number of times the app has been used when staying at home, the time the app has been used when staying at home, the number of times the app has been installed, and the time required to start the app. The number of times the communication app has been used, the time the communication app has been used, the number of times the communication app has been used for the first time after unlocking the screen (hereinafter referred to as the "first time use"), the number of times the pre-installed app has been used, the time the pre-installed app has been used, First-time use of pre-installed app, number of times to send / receive e-mail, number of times to edit e-mail, number of times to send / receive short message, number of times to edit short message, number of times to start notepad, number of times to start calendar, number of times to start alarm, help page The number of times the application is displayed, the number of times the clock is started, the number of times the map is started, and the URL information of the browser are included. The application includes all applications used in the user terminal 110. The number of times the app, communication app, or pre-installed app has been used means the number of times the app, communication app, or pre-installed app has been used. The usage time of the app, communication app, or pre-installed app includes at least one of the length of time the app, the communication app, or the pre-installed app is used and the time zone when the app is used. Similarly, the usage time of the application during the stay at home includes at least one of the length of time the user has used the application at home and the time zone in which the application has been used. Home is an example of a predetermined location according to the present disclosure.

The feature amount related to the use of the application is generated based on at least one of the usage history, the operation history, the location information history, and the contract information of the application, for example. For example, the number of times and the usage time of an application, a communication application, or a pre-installed application are counted based on the start date and time and the end time of the application. The time required to start an application is counted based on, for example, the start date and time of the application and the start date and time of the operation of starting this application. The usage time of the application during the stay at home is counted based on, for example, the start date and time and end time of each application and the location of the user's home. As described above, the location of the user's home may be estimated, for example, by analyzing the history of location information, or may be determined from the address included in the contract information. The number of times the communication application or the pre-installed application is used for the first time is counted based on, for example, the end date and time of the operation for unlocking the screen and the activation date and time of the communication application or the pre-installed application. The number of times an email or short message is sent or received is counted, for example, based on the date and time when the email or short message was sent and received. The editing time of an e-mail or short message is counted based on, for example, the editing start date and time and the editing end date and time of the e-mail or short message. The number of times the memo pad is started, the number of times the calendar is started, the number of times the alarm is started, the number of times the help page is displayed, the number of times the clock is started, and the number of times the map is started are, for example, the memo application, the calendar application, the alarm application, the help page display application, and the clock. It is counted based on the start date and time of the application and map application. For the URL information of the browser, for example, the statistic of the history of the URL accessed via the browser is used.

The amount of use of the application by the user can be known from at least one of the number of times the application has been used and the time the application has been used. For example, when the number of times the application is used is relatively small or at least one of the cases where the application usage time is relatively short, it can be seen that the user does not use the application very much. From at least one of the number of times the communication application is used, the time the communication application is used, the number of times the e-mail is sent and received, and the number of times the short message is sent and received, the degree to which the user is communicating with another person can be known. For example, if at least one of the number of times the communication app has been used, the time the communication app has been used, the number of times emails have been sent and received, and the number of times short messages have been sent and received is relatively low, the user may not be communicating much with others. I understand. From at least one of the number of times Notepad is started, the number of times the calendar is started, the number of times the alarm is started, the number of times the help page is displayed, the number of times the clock is started, and the number of times the map is started, these are used to supplement the memory or judgment of the user. You can see how much you need the help of your app. For example, if at least one of the number of times Notepad is started, the number of times the calendar is started, the number of times the alarm is started, the number of times the help page is displayed, the number of times the clock is started, and the number of times the map is started is relatively large, the user has memory or memory. It turns out that we often need the help of these apps to supplement our judgment. From the URL information of the browser, the breadth and narrowness of the user's range of interest can be understood.

The feature amount related to character input includes, for example, the number of times a character is deleted, the number of times a character is converted, the number of input characters, and the number of times a passcode is erroneously input. The feature amount related to the character input is generated, for example, based on the operation history of the operation of inputting the character. For example, the number of times a character is deleted and the number of times a character is converted are counted based on the date and time when the operation of deleting and converting the character is performed. The number of input characters is counted, for example, based on the content of the operation of inputting characters. The number of times the passcode is erroneously entered is counted, for example, based on the date and time when the operation for entering the passcode is performed and the number of times the characters are deleted.

The degree of character input error can be known from at least one of the number of character deletions, the number of character conversions, the number of input characters, and the number of erroneous input of passcodes. For example, if at least one of the number of character deletions, the number of character conversions, and the number of erroneous passcode inputs is relatively large relative to the number of character inputs, it can be seen that there are many character input errors.

The feature amount related to the call includes, for example, the number of incoming and outgoing calls, the talk time of the phone, and the volume of the voice of the user during the call. The feature amount related to a call is generated based on, for example, a call history. For example, the number of incoming and outgoing calls and the talk time of a telephone are counted based on the date and time of the outgoing call and the date and time of the incoming call. For the volume of the voice of the user during a call, for example, a statistic of the history of the volume of the voice of the user during a call is used.

The amount of the user using the telephone can be known from at least one of the number of incoming and outgoing calls and the talk time of the telephone. For example, it can be seen that the user often uses the telephone when the number of incoming calls and outgoing calls is relatively large and at least one of the cases where the telephone talk time is relatively long. From the volume of the voice of the user during the call, emotions such as anger of the user during the call can be understood. For example, when the volume of the voice of the user during a call is relatively loud, it can be seen that the user is likely to get angry during the call.

Environmental features include, for example, atmospheric pressure. For barometric pressure, for example, a statistic of barometric pressure history is used. Fluctuations in barometric pressure are known to affect the peripheral symptoms of dementia. Therefore, the atmospheric pressure shows the risk that the user will develop peripheral symptoms of dementia.

Returning to FIG. 2, the determination unit 123 determines whether or not the feature amount acquired by the acquisition unit 122 satisfies the condition indicating the tendency of deterioration of the cognitive function. Conditions indicating a tendency of cognitive decline are predetermined for each feature amount. This condition is stored in the server device 120 in advance.

When cognitive function declines, there is a tendency peculiar to the user's screen unlocking method. The features related to screen unlocking are defined with conditions that show this peculiar tendency. For example, when the cognitive function deteriorates, the number of times the screen is unlocked may tend to increase. Therefore, for example, the number of times the screen is unlocked is determined to be equal to or greater than the corresponding reference value. In addition, when the cognitive function deteriorates, it may take time to unlock the screen or start the application without remembering the passcode used for unlocking the screen or the application to be started. Therefore, for example, the time required to unlock the screen and the time from the unlocking of the screen to the activation of the application are set to be equal to or higher than the corresponding reference values.

When cognitive function declines, there is a tendency peculiar to the movement pattern of the user. Conditions indicating this peculiar tendency are defined for the feature amount related to the movement of the user. For example, when cognitive function declines, users may not go out much. In particular, it may not be possible to go out or go out for a long time. Therefore, for example, the number of staying points, the number of new staying points by the user, the number of visits to the points where the user frequently stays, the number of meshes passed by the user, the number of new meshes passed by the user, and the use. The conditions that the person's outing time, the number of times the user goes out, the distance traveled per unit period, and the representative value of the travel speed and the spray value indicating the variation are equal to or less than the corresponding reference values are set. In addition, the similarity of the staying points, the similarity of the mesh pattern passed by the user, and the staying time at home are set on the condition that they are equal to or higher than the corresponding standard values. In addition, when cognitive function declines, it may accidentally invade a dangerous area such as a railroad crossing. Therefore, for example, the condition that the number of invasions into the dangerous area is equal to or higher than the corresponding reference value is set. Furthermore, when cognitive function declines, people may go out during times when they do not normally go out, such as in the middle of the night. Therefore, for example, the condition that the user's outing time zone is included in the time zone in which the user does not normally go out is defined.

When cognitive function declines, there is a tendency peculiar to the features obtained from the sensor. The features obtained from the sensor are defined with conditions that indicate this peculiar tendency. For example, when cognitive function declines, users may not go out much. Therefore, for example, the conditions that the acceleration, the angular velocity, and the number of steps are equal to or less than the corresponding reference values are set. In addition, the recognition result of the means of transportation defines, for example, a condition indicating that the vehicle is not used much. Further, when the cognitive function deteriorates, the user may not use the user terminal 110 very much. Therefore, for example, the angular velocity is defined as being equal to or less than the corresponding reference value.

When cognitive function declines, there is a tendency peculiar to how to use the app. The features related to the use of the application are defined with conditions that show this peculiar tendency. For example, when cognitive function declines, users may not use the app much. Therefore, for example, the number of times the app is used, the time the app is used, the number of times the app is used when staying at home, the time the app is used when staying at home, the number of installed apps, the number of times the communication app is used, the time the communication app is used, the communication app The number of times of initial use, the number of times of using the pre-installed application, the number of times of using the pre-installed application, the number of times of the first use of the pre-installed application, the number of times of sending and receiving e-mails, and the number of times of sending and receiving short messages are below the corresponding standard values. The condition that there is is set. In addition, when the cognitive function deteriorates, it may take time to operate the application. Therefore, for example, the time required to start the application, the editing time of the e-mail, and the editing time of the short message are set to be equal to or higher than the corresponding reference values. Furthermore, when cognitive function declines, apps that support memory or judgment may be frequently used. Therefore, for example, the number of times Notepad is started, the number of times the calendar is started, the number of times the alarm is started, the number of times the help page is displayed, the number of times the clock is started, and the number of times the map is started are required to be equal to or higher than the corresponding reference values. It is decided. In addition, cognitive decline may reduce interest in things around you. Therefore, for example, the URL information of the browser defines a condition indicating that the range of interest of the user is narrow.

When cognitive function declines, there is a tendency peculiar to the way of inputting characters. Conditions indicating this peculiar tendency are defined for the feature amount related to character input. For example, when the cognitive function deteriorates, the number of character input errors may increase. Therefore, for example, the number of times a character is deleted, the number of times a character is converted, and the number of times a passcode is erroneously entered are set to be equal to or higher than the corresponding reference values.

When cognitive function declines, there is a tendency peculiar to the way of calling. Conditions indicating this peculiar tendency are defined for the feature amount related to the call. For example, cognitive decline may lead to frequent phone calls. Therefore, for example, the number of incoming and outgoing telephone calls and the telephone talk time are set on the condition that they are equal to or higher than the corresponding reference values. In addition, when the cognitive function deteriorates, it becomes easy to get angry and the voice may become loud during a call. Therefore, for example, a condition is set that the volume of the voice of the user during a call is equal to or higher than the corresponding reference value.

As mentioned above, it is known that fluctuations in barometric pressure affect the peripheral symptoms of dementia. Therefore, for example, a condition is set for indicating that the atmospheric pressure has fluctuations that affect the peripheral symptoms of dementia.

The reference value included in the condition is predetermined based on at least one of the feature amount of another user in a state where the cognitive function is deteriorated, the feature amount of the user in the past, and the feature amount of all users. Other users with reduced cognitive function and all users include other users who are different from the users. These feature quantities are acquired and stored in advance based on the usage history 114, the contract information of the user or another user, and the hobby / preference information collected by the server device 120 from the user terminal 110 of the user or another user in advance. It may be stored in the server device 120, or may be input to the server device 120 according to the operation of the administrator. The feature amounts of other users and the feature amounts of all users in a state where the cognitive function is deteriorated are examples of the second feature amount according to the present disclosure.

For example, at the start of service provision, a standard value is set based on the user's past feature amount, and after a certain period of time such as several years has passed since the service was provided, the feature amount and use of a person with reduced cognitive function. The reference value may be set based on the past feature amount of the person and the feature amount of all users.

As a method of setting a reference value based on the feature amount of other users and the feature amount of all users in a state where the cognitive function is deteriorated, for example, in the normal distribution of the feature amount of all users, the cognitive function is deteriorated. A method of determining a reference value based on the position of a person's feature amount may be used. For example, when the average value of the feature amount of all users is m and the feature amount of a person with reduced cognitive function is included in the range of X or more or X or less, the reference value is set based on the feature amount X. It is decided. As a method of setting a reference value based on a user's past feature amount, for example, in a normal distribution of a user's past feature amount, a method of setting a reference value based on a value outside a predetermined standard deviation range is used. May be done. As a method of setting a reference value based on the feature amount of all users, for example, in a normal distribution of the feature amount of all users, a method of setting a reference value based on a value outside a predetermined standard deviation range is used. May be good. The reference value may be the reference value itself, or may be a value in which a margin is taken into consideration from the reference value.

Further, instead of the feature amount of all users, the feature amount of another user similar to the user may be used. Other users who are similar to the user include other users who have similar attributes or usage of the user terminal 110 to the user. This is because it may be difficult for a user whose attributes or usage of the user terminal 110 are different from those of the user to simply compare the features related to the use of the user terminal 110. User attributes include, for example, age or gender. For example, the operation speed of the user terminal 110 differs between the elderly and other users. Therefore, it may be difficult to detect the tendency of the recognition function of the user even if the feature amount of the elderly user and the feature amount of all the users are simply compared. Other users with similar attributes to the user are extracted from all users using, for example, contract information. The usage of the user terminal 110 includes, for example, a method of unlocking the screen. For example, as a method of unlocking the screen, there are a method using a passcode and a method using a fingerprint. The time required to unlock the screen differs between the case where the passcode is used and the case where the fingerprint is used. Therefore, even if the feature amount of the user who unlocks the screen by the method using the passcode and the feature amount of the user who unlocks the screen by the method using the fingerprint are simply compared, the recognition function of the user is performed. It may be difficult to detect the tendency of. Other users whose attributes are similar to those of the user are extracted from all users, for example, by normalizing each feature amount for each user.

If the reference value is set based on the features of other users with reduced cognitive function, the features of all users, or the features of other users similar to the user, the user's The tendency of the user's cognitive function is detected according to the relationship between the feature amount and the feature amount of another user. On the other hand, when the reference value is set based on the past feature amount of the user, the tendency of the cognitive function of the user is detected according to the temporal change of the feature amount of the user.

The calculation unit 124 calculates an evaluation value according to the determination result of the determination unit 123. For example, when the feature quantity satisfies the corresponding condition, the evaluation value becomes large. For example, for each feature amount shown in FIGS. 4 and 5, the evaluation value is added when the condition is satisfied, and the evaluation value is not added when the condition is not satisfied. The larger the number of features that satisfy the conditions, the larger the evaluation value. That is, the evaluation value is calculated so that the evaluation value increases as the number of feature quantities satisfying the condition increases.

The detection unit 125 detects the tendency of the user's cognitive function depending on whether or not the feature amount acquired by the acquisition unit 122 satisfies the condition indicating the tendency of the cognitive function to decline. For example, when the evaluation value calculated by the calculation unit 124 is equal to or greater than the threshold value, a tendency of deterioration of cognitive function is detected. On the other hand, when the evaluation value calculated by the calculation unit 124 is less than the threshold value, a normal tendency of the cognitive function is detected. For this threshold value, for example, a value at the end of a range of evaluation values indicating a tendency of cognitive decline is used.

The output unit 126 outputs information according to the tendency of the user's cognitive function detected by the detection unit 125 to the user terminal 110. For example, when a user's cognitive function is declining, this information includes information for notifying the user's cognitive declining tendency, information for providing a game for measuring the health condition of the brain, and cognitive decline. It contains at least one of information that guides the contact point where you can consult about, various information about cognitive decline, and information for providing a service to search for medical institutions with dementia. On the other hand, when the cognitive function of the user has a normal tendency, this information includes, for example, information notifying the normal tendency of the cognitive function of the user. These information may be created in advance and stored in the server device 120, for example. In this case, the user terminal 110 displays a screen corresponding to this information.

FIG. 6 is a diagram showing an example of a screen displayed on the user terminal 110 when a tendency of deterioration of cognitive function is detected. This screen includes at least one of a notification screen 200, a brain health diagnosis screen 210, a telephone consultation counter guidance screen 220, an information providing screen 230, and a search screen 240.

The notification screen 200 notifies the user that the cognitive function of the user is declining. For example, the notification screen 200 includes a message indicating that the cognitive function of the user is declining. Further, the notification screen 200 includes an operation button 201 used for an operation of displaying the brain health diagnosis screen 210. When the user presses the operation button 201, the brain health diagnosis screen 210 is displayed. In addition to the operation buttons 201, the notification screen 200 may include operation buttons used for operations for displaying the guidance screen 220, the information provision screen 230, and the search screen 240 of the telephone consultation counter.

The brain health diagnosis screen 210 provides a game for measuring the health condition of the brain. For this game, for example, a card game played on the screen of the user terminal 110 is used. When the user plays a game through the brain health diagnosis screen 210, the user's brain health state is measured, and the measurement result is displayed on the brain health diagnosis screen 210.

The guidance screen 220 of the telephone consultation counter guides the consultation counter to a specialist such as a nurse regarding the deterioration of cognitive function by telephone. The guidance screen 220 of the telephone consultation counter includes the telephone number of this counter.

The information providing screen 230 provides various information regarding the deterioration of cognitive function. Various types of information include information that introduces activities that contribute to the prevention of dementia and activities recommended by the authority of dementia, and information for preparing for life after the onset of dementia.

The search screen 240 provides a service for searching a medical institution for dementia in the area desired by the user. For example, when the user performs an operation of inputting a desired area, the search results of medical institutions with dementia in that area are displayed on the search screen 240.

The block diagram used in the above description shows blocks for functional units. These functional blocks (components) are realized by any combination of at least one of hardware and software. Further, the method of realizing each functional block is not particularly limited. That is, each functional block may be realized using one physically or logically coupled device, or two or more physically or logically separated devices can be directly or indirectly (eg, for example). , Wired, wireless, etc.) and may be realized using these plurality of devices. The functional block may be realized by combining the software with the one device or the plurality of devices.

Functions include judgment, decision, judgment, calculation, calculation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, solution, selection, selection, establishment, comparison, assumption, expectation, and assumption. There are broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, assigning, etc., but only these. I can't. For example, a functional block (component) that makes transmission function is called a transmitting unit or a transmitter. In each case, as described above, the realization method is not particularly limited.

For example, the user terminal 110, the server device 120, and the like in one embodiment of the present disclosure may function as a computer that performs the processing of the present disclosure. FIG. 7 is a diagram showing an example of the hardware configuration of the user terminal 110 according to the embodiment of the present disclosure. The user terminal 110 may be physically configured as a computer device including a processor 1101, a memory 1102, a storage 1103, a communication device 1104, an input device 1105, an output device 1106, a bus 1107, and the like.

In the following description, the word "device" can be read as a circuit, a device, a unit, or the like. The hardware configuration of the user terminal 110 may be configured to include one or more of the devices shown in the figure, or may be configured not to include some of the devices.

For each function in the user terminal 110, by loading predetermined software (program) on hardware such as the processor 1101 and the memory 1102, the processor 1101 performs an operation and controls communication by the communication device 1104, or the memory 1102. And by controlling at least one of reading and writing of data in the storage 1103.

Processor 1101 operates, for example, an operating system to control the entire computer. The processor 1101 may be configured by a central processing unit (CPU) including an interface with a peripheral device, a control device, an arithmetic unit, a register, and the like. For example, the display control unit 113 described above may be realized by the processor 1101.

Further, the processor 1101 reads a program (program code), a software module, data, etc. from at least one of the storage 1103 and the communication device 1104 into the memory 1102, and executes various processes according to these. As the program, a program that causes a computer to execute at least a part of the operation of the user terminal 110 is used. This program includes apps that run on the operating system. The processing performed by the user terminal 110 may be executed by one processor 1101 or may be executed simultaneously or sequentially by two or more processors 1101. Processor 1101 may be mounted by one or more chips. The program may be transmitted from the network via a telecommunication line.

The memory 1102 is a computer-readable recording medium, and is composed of at least one such as a ROM (Read Only Memory), an EPROM (Erasable Programmable ROM), an EEPROM (Electrically Erasable Programmable ROM), and a RAM (Random Access Memory). May be done. The memory 1102 may be referred to as a register, a cache, a main memory (main storage device), or the like. The memory 1102 can store a program (program code), a software module, or the like that can be executed to implement the wireless communication method according to the embodiment of the present disclosure.

The storage 1103 is a computer-readable recording medium, for example, an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, an optical magnetic disk (for example, a compact disk, a digital versatile disk, a Blu-ray). It may consist of at least one (registered trademark) disk), smart card, flash memory (eg, card, stick, key drive), floppy (registered trademark) disk, magnetic strip, and the like. The storage 1103 may be referred to as an auxiliary storage device. The storage medium described above may be, for example, a database, server or other suitable medium containing at least one of the memory 1102 and the storage 1103. The above-mentioned usage history 114 may be stored in at least one of the memory 1102 and the storage 1103, for example.

The communication device 1104 is hardware (transmission / reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, a communication module, or the like. The communication device 1104 includes, for example, a high frequency switch, a duplexer, a filter, a frequency synthesizer, and the like in order to realize at least one of FDD (Frequency Division Duplex) and Time Division Duplex (TDD). It may be composed of. For example, the transmission unit 111, the reception unit 112, and the like described above may be realized by the communication device 1104. The transmitting unit 111 and the receiving unit 112 may be physically or logically separated from each other.

The input device 1105 is an input device (for example, a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives an input from the outside. The input device 1105 includes operation units such as buttons and touch sensors. The user performs various operations on the user terminal 110 by using the operation unit. The various operations include, for example, an operation of unlocking the screen, an operation of starting an application, and an operation of inputting characters. The operation of releasing the screen lock includes, for example, an operation of inputting a passcode.

Further, the input device 1105 includes various sensors. Various sensors include a GSP (Global Positioning System) receiver, an accelerometer, a gyro sensor, a pedometer, and a barometer. The GPS receiver measures the current position of the user of the user terminal 110 based on the radio wave received from the artificial satellite at a predetermined time interval, and calculates the position information. The current position of the user may be measured by using a known technique using a base station or a wireless LAN (Local Area Network) without using a GPS receiver. The accelerometer measures the acceleration of the user terminal 110 at predetermined time intervals. The gyro sensor measures the angular velocity of the user terminal 110 at predetermined time intervals. The pedometer counts the number of steps of the user of the user terminal 110 per unit period. The barometer measures the atmospheric pressure around the user terminal 110 at predetermined time intervals. Further, the input device 1105 includes a microphone. Microphones are used for telephone calls. The microphone acquires the user's voice at the earpiece and converts it into a voice signal. The strength of this voice signal indicates the volume of the voice of the user during a call.

The output device 1106 is an output device (for example, a display, a speaker, an LED lamp, etc.) that outputs to the outside. The output device 1106 includes a display. The display displays various screens. Further, the output device 1106 includes a speaker. Speakers are used for calls. The speaker outputs audio according to the audio signal. The input device 1105 and the output device 1106 may have an integrated configuration (for example, a touch panel).

Further, each device such as the processor 1101 and the memory 1102 is connected by a bus 1107 for communicating information. The bus 1107 may be configured by using a single bus, or may be configured by using a different bus for each device.

Further, the user terminal 110 includes hardware such as a microprocessor, a digital signal processor (DSP: Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), and an FPGA (Field Programmable Gate Array). It may be configured, and some or all of each functional block may be realized by the hardware. For example, processor 1101 may be implemented using at least one of these hardware.

FIG. 8 is a diagram showing an example of the hardware configuration of the server device 120 according to the embodiment of the present disclosure. The server device 120 may be physically configured as a computer device including a processor 1201, a memory 1202, a storage 1203, a communication device 1204, a bus 1205, and the like. Similar to the hardware configuration of the user terminal 110, the hardware configuration of the server device 120 may be configured to include one or more of the devices shown in the figure, or may be configured without including some of the devices. May be done. Since the processor 1201, the memory 1202, the storage 1203, the communication device 1204, and the bus 1205 are the same as the processor 1101, the memory 1102, the storage 1103, the communication device 1104, and the bus 1107 described above, the description thereof will be omitted.

For each function in the server device 120, by loading predetermined software (program) on hardware such as the processor 1201 and the memory 1202, the processor 1201 performs an operation, controls communication by the communication device 1204, and the memory 1202. And by controlling at least one of reading and writing of data in the storage 1203. The above-mentioned acquisition unit 122, determination unit 123, calculation unit 124, detection unit 125, and the like may be realized by the processor 1201. The above-mentioned receiving unit 121, output unit 126, and the like may be realized by a communication device 1204. A predetermined condition for each of the above-mentioned feature quantities and a reference value included in this condition may be stored in at least one of the memory 1202 and the storage 1203, for example.

2. 2. Operation FIG. 9 is a sequence chart showing an example of the operation of the system 100 according to the embodiment of the present disclosure. This operation is started at predetermined time intervals, for example, once a week, a month, or every few months.

In step S11, the transmission unit 111 of the user terminal 110 transmits the usage history 114 stored in the memory 1102 or the storage 1103 to the server device 120. In step S12, the receiving unit 121 of the server device 120 receives the usage history 114. Further, the receiving unit 121 acquires the user's contract information and hobby / preference information from an external device (not shown). For example, the contract information and the hobby / preference information shown in FIG. 3 are acquired. The usage history 114, contract information, and hobby / preference information are stored in the server device 120.

In step S13, the acquisition unit 122 of the server device 120 acquires the feature amount of the user regarding the use of the user terminal 110 by statistically analyzing the usage history 114, the contract information, and the hobby / preference information. For example, the features shown in FIGS. 4 and 5 are acquired.

In step S14, the determination unit 123 of the server device 120 determines whether or not each feature amount satisfies the condition indicating the tendency of deterioration of the cognitive function. For example, with respect to each feature amount shown in FIGS. 4 and 5, it is determined whether or not the condition defined for the feature amount is satisfied.

In step S15, the calculation unit 124 calculates the evaluation value according to the determination result in step S14. Here, it is assumed that the initial value of the evaluation value is 0. For example, if the number of screen unlocks shown in FIG. 4 satisfies the condition, 1 is added to the evaluation value. On the other hand, if the number of times the screen is unlocked does not satisfy the condition, the evaluation value is not added. In this way, the evaluation value is calculated by repeating this process for all the feature quantities shown in FIGS. 4 and 5.

In step S16, the detection unit 125 of the server device 120 detects the tendency of the user's cognitive function according to this evaluation value. For example, when the evaluation value is equal to or higher than the threshold value, a tendency of cognitive decline is detected. On the other hand, when the evaluation value is less than the threshold value, a normal tendency of cognitive function is detected.

In step S17, the output unit 126 of the server device 120 transmits information according to the tendency of the user's cognitive function to the user terminal 110. For example, when a cognitive decline tendency is detected, information for notifying the user's cognitive decline tendency, information for providing a game for measuring the health condition of the brain, and a contact point where consultation regarding cognitive decline can be made. At least one of information for guiding the patient, various information regarding the deterioration of cognitive function, and information for providing a service for searching a medical institution for dementia is transmitted.

In step S18, the receiving unit 112 of the user terminal 110 receives this information from the server device 120. In step S19, the display control unit 113 of the user terminal 110 causes the display to display a screen corresponding to this information. For example, as shown in FIG. 6, the notification screen 200 is displayed first, and the brain health diagnosis screen 210, the telephone consultation counter guidance screen 220, the information provision screen 230, or the search screen 240 is displayed according to the user's operation. Is displayed.

The present inventors recognize the user by using the support vector machine with the feature amount of the user regarding the use of the user terminal 110 as an explanatory variable and whether or not the user is a person at risk of dementia as an objective variable. We constructed a classification model that divides users into two classes, those at risk of dementia and other users, and confirmed the classification accuracy rate when the users were classified using this classification model. A person at risk of dementia is a person who may have impaired cognitive function. As a result, the classification correct answer rate when the users were classified using this classification model was higher than the classification correct answer rate of 50% when the users were randomly classified. From this experiment, it was found that the accuracy of detecting a person at risk of dementia is improved by detecting a person at risk of dementia using a feature amount related to the use of the user terminal 110.

According to the embodiment described above, since the tendency of the user's cognitive function is detected by using the feature amount related to the movement of the user of the user terminal 110, the accuracy of detecting the tendency of the user's cognitive function is improved. .. In addition, an evaluation value is calculated according to whether or not this feature amount satisfies the condition, and a tendency of cognitive function is detected according to this evaluation value. Therefore, even when a large number of feature amounts exist, the user The tendency of cognitive function can be easily detected.

3. 3. Modifications The embodiments of the present disclosure are not limited to the embodiments described above. The above-described embodiment may be modified as in the following modification. Moreover, the following two or more modified examples may be carried out in combination.

3.1 Modification example 1
In the above-described embodiment, the conditions of each feature amount are not limited to the above-mentioned example. For example, it usually does not take much time to unlock the screen, and it does not take much time to start the application after unlocking the screen, but when the cognitive function deteriorates, it sometimes takes a very long time to unlock the screen. Therefore, for example, a condition may be set that the maximum value of the time required for unlocking the screen and the spraying value indicating the variation are equal to or higher than the corresponding reference values. In addition, a condition may be set that the maximum value of the time from the release of the screen lock to the start of the application and the spray value indicating the variation are equal to or less than the corresponding reference values.

Decreased cognitive function can complicate movement patterns. For example, while staying at different points depending on the day, the movement pattern may be such that the points where the person stays frequently are also visited and more points are passed when moving. In addition, you may be more likely to wander or get lost. Therefore, for example, the number of staying points, the number of new staying points by the user, the number of visits to the points where the user frequently stays, the number of meshes passed by the user, the number of new meshes passed by the user, and the unit. A condition may be set for the travel distance per period to be equal to or greater than the corresponding reference value. In addition, the similarity of the staying points may be stipulated as being equal to or less than the corresponding reference value. Also, when cognitive function declines, most do not move much, but sometimes they move quickly. Therefore, for example, a condition may be set that the maximum value, the average value, and the spray value indicating the variation of the moving speed are equal to or higher than the corresponding reference values. In addition, the median moving speed may be stipulated to be less than or equal to the corresponding reference value. In addition, cognitive decline may lead to frequent afternoon outings. Therefore, a condition indicating that the time zone when the user goes out may be within the time from 13:00 to 16:00 may be set.

Communication and pre-installed apps are often used when cognitive decline occurs. In particular, these apps may be used frequently during the day. In addition, these apps may often be used first after unlocking the screen. Therefore, for example, the number of times the communication application is used, the length of the communication application usage time, the number of times the communication application is used for the first time, the number of times the pre-installed application is used, the length of the pre-installed application usage time, and the number of times the pre-installed application is used for the first time. May be stipulated that the value is equal to or higher than the corresponding reference value. In addition, the usage time zone of the communication application and the usage time zone of the pre-installed application may be set with a condition indicating that the time is within the time from 6:00 to 18:00.

When cognitive decline occurs, apps may be used more often at home. Therefore, for example, the condition that the number of times the application is used when staying at home and the usage time of the application when staying at home are equal to or higher than the corresponding reference values may be set.

3.2 Modification 2
In the above-described embodiment, weighting may be performed when calculating the evaluation points. For example, when a feature amount having a high correlation with a decrease in cognitive function satisfies the condition, weighting may be performed so that a value larger than that when the other feature amounts satisfy the condition is added to the evaluation value. For example, when 1 is added to the evaluation value when another feature amount satisfies the condition, 2 may be added to the evaluation value when the feature amount having a high correlation with the deterioration of cognitive function satisfies the condition. Further, for example, when a combination of two or more specific features has a high correlation with deterioration of cognitive function and both of the two or more specific features satisfy the conditions, the same number of other features satisfy the conditions. Weighting may be performed so that a value larger than the time is added to the evaluation value. For example, when two specific feature quantities satisfy the condition, 4 may be added to the evaluation value instead of 2 which is added to the evaluation value when the two other feature quantities satisfy the condition.

This weighting may be performed according to a human operation or may be performed in machine learning. When weighting is performed according to human operation, for example, a dementia expert determines a weight to be attached to a feature amount that correlates with a decrease in cognitive function. This weight is input to the server device 120 and stored in the memory 1202 or the storage 1203. Then, the evaluation value is calculated using the weight attached to the feature amount. On the other hand, when weighting is performed in machine learning, for example, the feature quantities of all users regarding the use of the user terminal 110 are machine-learned, and the users are divided into two classes, a dementia risk person and other users. The features are weighted so that the classification accuracy rate is the highest. This weight is stored in memory 1202 or storage 1203. Then, the evaluation value is calculated using the weight attached to the feature amount.

3.3 Modification 3
In the above-described embodiment, the feature amount relating to the use of the user terminal 110 is not limited to the above-mentioned example. This feature amount may be any feature amount as long as it is a feature amount acquired based on the data obtained for the user terminal 110. For example, only a part of the feature quantities shown in FIGS. 3 to 5 may be used. Further, the feature amount related to the use of the user terminal 110 can be acquired by the number of times the user terminal 110 has fallen, information indicating the subject recognized from the image taken by the camera of the user terminal 110, and future technological advances. The feature amount other than the feature amount shown in FIGS. 3 to 5 may be included, such as the information that becomes. For example, the feature quantities related to the movement of users include positioning information using GPS, positioning information using base stations, positioning information using Wi-Fi (registered trademark), and positioning information using Bluetooth (registered trademark). May be included. The feature amount related to the use of the application may include the start date and time and end date and time of the installed application, the identifier of the application, the identifier of the screen, and the contents of the calendar (subject, date and time, place, etc.).

Further, the classification of the feature amount regarding the use of the user terminal 110 is not limited to the above example. For example, the time from when the screen lock is released until the application is started may be classified into the feature amount related to the use of the application in place of or together with the feature amount related to the screen unlocking. The number of erroneous input of the passcode may be classified into the feature amount related to screen unlocking instead of or together with the feature amount related to character input. The acceleration of the user terminal 110, the angular velocity of the user terminal 110, the number of steps of the user, and the recognition result of the moving means used by the user are the feature amounts related to the movement of the user in place of or together with the feature amount obtained from the sensor. It may be classified into.

3.4 Modification example 4
In the above-described embodiment, the method of detecting the tendency of the cognitive function of the user is not limited to the method of comparing the evaluation value and the threshold value. For example, a radar chart showing the magnitude of evaluation values may be created for a plurality of predetermined evaluation items, and the tendency of the user's cognitive function may be detected by the polygonal shape constituting the radar chart. This method may or may not be used in conjunction with the method of comparing the evaluation value and the threshold value described above.

In this modification, first, the evaluation values are subtotaled for each of a plurality of predetermined evaluation items. The plurality of evaluation items include, for example, "memory / judgment", "social activity", "orientation", "home", and "others".

The evaluation items "memory / judgment" include, for example, the number of times the screen is unlocked, the time required to unlock the screen, the time from when the screen lock is released until the application is started, the number of times the memo pad is started, and the calendar. The number of activations, the number of alarm activations, the number of help page displays, the number of clock activations, the number of map activations, the number of character deletions, the number of character conversions, and the number of input characters belong to it. The total of the evaluation values calculated according to these feature quantities is the evaluation value of this evaluation item.

The evaluation items of "social activity" include, for example, the number of incoming and outgoing calls, the talk time of the phone, the volume of the user's voice during the call, the number of times of sending and receiving e-mail, the time of editing e-mail, and the sending and receiving of short messages. Number of times, time to edit short message, number of times to use communication app, time to use communication app, acceleration of user terminal 110, angular velocity of user terminal 110, number of steps of user, recognition result of transportation means used by user, browser The URL information, the moving speed, the time when the user goes out, and the number of times the user goes out belong to this. The total of the evaluation values calculated according to these feature quantities is the evaluation value of this evaluation item.

The evaluation items of "orientation" include, for example, the number of staying points, the similarity of staying points, the number of new staying points, the number of visits to points where users frequently stay, and the number of meshes passed by users. And the number of new meshes passed by the user belongs. The total of the evaluation values calculated according to these feature quantities is the evaluation value of this evaluation item.

The evaluation item "home" includes, for example, the time spent at home, the number of times the app is used during the stay at home, and the time spent using the app during the stay at home. The total of the evaluation values calculated according to these feature quantities is the evaluation value of this evaluation item. For example, atmospheric pressure belongs to the evaluation item "others". The evaluation value calculated according to this feature amount becomes the evaluation value of this evaluation item.

Subsequently, a radar chart showing the magnitude of the evaluation value of these evaluation items is created. Then, the tendency of the user's cognitive function is detected by the polygonal shape constituting this radar chart. When cognitive function declines, there is a tendency peculiar to the shape of this polygon. For example, when this polygon has a large or small distorted shape in which only a part of a specific evaluation item of 1 or 2 or more is prominent, even if the total evaluation value is less than the threshold value, the user's A tendency for cognitive decline may be detected.

Further, this radar chart may have a three-dimensional shape that represents the magnitude of the evaluation value of the evaluation item along the time axis. In this case, the height direction of the solid indicates the time axis. For example, a radar chart has a pentagonal column, a pentagonal pyramid, or a twisted shape as shown in FIG. In this case, for example, the three-dimensional shape 310 or 320 of the user's radar chart is compared with the three-dimensional shape 315 or 325 of the radar chart of a person with reduced cognitive function. When the degree of approximation of these three-dimensional shapes 310 and 315 or 320 and 325 is equal to or higher than the threshold value, a tendency of deterioration of the user's cognitive function may be detected regardless of the total evaluation value.

3.5 Modification 5
In the above-described embodiment, the method of detecting the tendency of the cognitive function of the user is not limited to the method of comparing the evaluation value and the threshold value. For example, when the feature amount of the user correlates with the feature amount of the person in the state where the cognitive function is deteriorated, the tendency of the user's cognitive function to be lowered may be detected. In this case, for example, the correlation coefficient between the feature amount of the user and the feature amount of the person in a state where the cognitive function is deteriorated is calculated. When the correlation coefficient is equal to or higher than the threshold value, a tendency of deterioration of the user's recognition function is detected. For this threshold value, for example, a value at the end of the range of the correlation coefficient indicating that the recognition function tends to decrease is used.

Further, for example, a machine learning model may be used to detect a decrease in the cognitive function of the user. For example, by performing machine learning with the feature amount of all users regarding the use of the user terminal 110 as an explanatory variable and whether or not the user is a dementia risk person as an objective variable, the user can be regarded as a dementia risk person. A machine learning model that is divided into two classes with users other than the above is generated. By inputting the feature amount of the user into this machine learning model, it is determined whether or not the user is a person at risk of dementia. When the user is determined to be a person at risk of dementia, a tendency of deterioration of the user's cognitive function is detected. On the other hand, when it is determined that the user is not a person at risk of dementia, a normal tendency of the user's cognitive function is detected.

3.6 Modification 6
In the above-described embodiment, the condition of the feature amount regarding the use of the user terminal 110 may be changed by using the machine learning model. In this case, the machine learning model may change the condition of the feature amount by performing machine learning using the feature amount of the user who is actually diagnosed with the deterioration of the cognitive function as the teacher data in the medical institution or the like.

3.7 Modification 7
In the above-described embodiment, the output destination of the information according to the tendency of the cognitive function is not limited to the user terminal 110 of the user. For example, in addition to or instead of the user terminal 110 of the user, information according to the tendency of the cognitive function of the user may be output to the user terminal of a related person such as the family of the user. In this case, the communication address of the user terminal of the person concerned is stored in the memory 1202 or the storage 1203 in advance. Then, the information according to the tendency of the cognitive function of the user is transmitted from the server device 120 to this communication address. According to this modification, the person concerned can know the tendency of the cognitive function of the user. Further, for example, when a user invades a dangerous area, a user terminal of a person concerned may be notified to that effect. In this case, the process shown in FIG. 9 is preferably performed in real time.

In addition, the output of information according to the tendency of cognitive function does not necessarily have to be performed every time. Information may be output according to the tendency of cognitive function only when the tendency of cognitive function changes, for example, when the tendency of cognitive function changes from a normal tendency to a decreasing tendency. That is, when there is no change in the tendency of cognitive function, it is not necessary to output information according to the tendency of cognitive function. Furthermore, the information according to the tendency of cognitive function is not limited to the information shown in FIG. The information according to the tendency of cognitive function may be any information as long as it is at least partially different depending on the tendency of cognitive function. Further, in response to a request from the user terminal 110, information according to the tendency of the cognitive function may be transmitted from the server device 120 to the user terminal 110. In this case, the information according to the tendency of the cognitive function may include the detection result of the tendency of the cognitive function, the feature amount of the user, or the processed information thereof. As a result, the user can know the tendency of his / her cognitive function at a desired timing.

3.8 Modification 8
In the above-described embodiment, the configuration of the system 100 is an example, and the present invention is not limited thereto. For example, two or more devices may have the function of the server device 120. Further, the user terminal 110 may have at least a part of the functions of the server device 120. For example, the user terminal 110 may have an acquisition unit 122. When the user terminal 110 has all the functions of the server device 120, the server device 120 may not be provided.

3.9 Modification 9
Other embodiments of the present disclosure may provide a method comprising the steps of processing performed in the system 100, the user terminal 110, or the server device 120. Further, another aspect of the present disclosure may provide a program executed by the user terminal 110 or the server device 120. This program may be stored in a computer-readable recording medium and provided, or may be provided by downloading via the Internet or the like.

3.10 Other Modifications Information notification is not limited to the embodiments / embodiments described in the present disclosure, and may be performed by other methods. For example, information notification includes physical layer signaling (eg, DCI (Downlink Control Information), UCI (Uplink Control Information)), higher layer signaling (eg, RRC (Radio Resource Control) signaling, MAC (Medium Access Control) signaling, etc. It may be carried out by broadcast information (MIB (Master Information Block), SIB (System Information Block)), other signals, or a combination thereof. Further, the RRC signaling may be referred to as an RRC message, and may be, for example, an RRC Connection Setup message, an RRC Connection Reconfiguration message, or the like.

Each aspect / embodiment described in the present disclosure includes LTE (Long Term Evolution), LTE-A (LTE-Advanced), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), and 5G (5th generation mobile communication). system), FRA (Future Radio Access), NR (new Radio), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark)) )), LTE 802.16 (WiMAX®), IEEE 802.20, UWB (Ultra-WideBand), Bluetooth®, and other systems that utilize and extend based on these. It may be applied to at least one of the next generation systems. Further, a plurality of systems may be applied in combination (for example, a combination of at least one of LTE and LTE-A and 5G).

The order of the processing procedures, sequences, flowcharts, etc. of each aspect / embodiment described in the present disclosure may be changed as long as there is no contradiction. For example, the methods described in the present disclosure present elements of various steps using exemplary order, and are not limited to the particular order presented.

The input / output information and the like may be stored in a specific place (for example, a memory), or may be managed using a management table. Information to be input / output may be overwritten, updated, or added. The output information and the like may be deleted. The input information or the like may be transmitted to another device.

The determination may be made by a value represented by 1 bit (0 or 1), by a boolean value (Boolean: true or false), or by comparing numerical values (for example, a predetermined value). It may be done by comparison with the value).

Each aspect / embodiment described in the present disclosure may be used alone, in combination, or may be switched and used according to the execution. Further, the notification of predetermined information (for example, the notification of "being X") is not limited to the explicit one, but is performed implicitly (for example, the notification of the predetermined information is not performed). May be good.

Software, whether called software, firmware, middleware, microcode, hardware description language, or other names, instructions, instruction sets, codes, code segments, program codes, programs, subprograms, software modules. , Applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, procedures, features, etc. should be broadly interpreted.

Further, software, instructions, information and the like may be transmitted and received via a transmission medium. For example, a website that uses at least one of wired technology (coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), etc.) and wireless technology (infrared, microwave, etc.). When transmitted from a server or other remote source, at least one of these wired and wireless technologies is included within the definition of transmission medium.

The information, signals, etc. described in the present disclosure may be represented using any of a variety of different techniques. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description are voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, light fields or photons, or any of these. It may be represented by a combination of.

The terms "system" and "network" used in this disclosure are used interchangeably.

Further, the information, parameters, etc. described in the present disclosure may be expressed using absolute values, relative values from predetermined values, or using other corresponding information. It may be represented. For example, the radio resource may be one indicated by an index.

At least one of the server and the client may be referred to as a transmitting device, a receiving device, a communication device, and the like. At least one of the server and the client may be a device mounted on the mobile body, the mobile body itself, or the like. The moving body may be a vehicle (eg, car, airplane, etc.), an unmanned moving body (eg, drone, self-driving car, etc.), or a robot (manned or unmanned). ) May be. It should be noted that at least one of the server and the client includes a device that does not necessarily move during communication operation. For example, at least one of a base station and a mobile station may be an IoT (Internet of Things) device such as a sensor.

Further, the server in the present disclosure may be read as a client terminal. For example, a configuration in which communication between a server and a client terminal is replaced with communication between a plurality of user terminals (for example, may be referred to as D2D (Device-to-Device), V2X (Vehicle-to-Everything), etc.). , Each aspect / embodiment of the present disclosure may be applied. In this case, the user terminal 110 may have the functions of the server device 120 described above.

Similarly, the client terminal in the present disclosure may be read by the server. In this case, the server device 120 may have the functions of the user terminal 110 described above.

The terms "determining" and "determining" used in this disclosure may include a wide variety of actions. "Judgment" and "decision" are, for example, judgment (judging), calculation (calculating), calculation (computing), processing (processing), derivation (deriving), investigation (investigating), search (looking up, search, inquiry). It may include (eg, searching in a table, database or another data structure), ascertaining as "judgment" or "decision". Further, "judgment" and "decision" are receiving (for example, receiving information), transmitting (for example, transmitting information), input (input), output (output), and access. (Accessing) (for example, accessing data in memory) may be regarded as "judgment" or "decision". In addition, "judgment" and "decision" are considered to be "judgment" and "decision" when the things such as solving, selecting, selecting, establishing, and comparing are regarded as "judgment" and "decision". Can include. That is, "judgment" and "decision" may include considering some action as "judgment" and "decision". Further, "judgment (decision)" may be read as "assuming", "expecting", "considering" and the like.

The phrase "based on" as used in this disclosure does not mean "based on" unless otherwise stated. In other words, the statement "based on" means both "based only" and "at least based on".

Any reference to elements using designations such as "first" and "second" as used in this disclosure does not generally limit the quantity or order of those elements. These designations can be used in the present disclosure as a convenient way to distinguish between two or more elements. Therefore, references to the first and second elements do not mean that only two elements can be adopted, or that the first element must somehow precede the second element.

When "include", "including" and variations thereof are used in the present disclosure, these terms are as comprehensive as the term "comprising". Is intended. Moreover, the term "or" used in the present disclosure is intended not to be an exclusive OR.

In the present disclosure, if articles are added by translation, for example a, an and the in English, the disclosure may include the plural nouns following these articles.

In the present disclosure, the term "A and B are different" may mean "A and B are different from each other". The term may mean that "A and B are different from C". Terms such as "separate" and "combined" may be interpreted in the same way as "different".

Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described in the present disclosure. The present disclosure may be implemented as amendments and modifications without departing from the spirit and scope of the present disclosure, which is determined by the description of the scope of claims. Therefore, the description of this disclosure is for purposes of illustration and does not have any limiting meaning to this disclosure.

100: System, 110: User terminal, 111: Transmitter, 112: Receiver, 113: Display control unit, 114: Usage history, 120: Server device, 121: Receiver, 122: Acquisition unit, 123: Judgment unit, 124: Calculation unit, 125: Detection unit, 126: Output unit

Claims (8)

The acquisition unit that acquires the first feature amount related to the movement of the user,
Output that outputs information according to the tendency of the cognitive function of the user, which is detected according to the relationship between the first feature amount and the second feature amount related to the movement of another user different from the user. An output device equipped with a unit. The first feature amount includes the number of points where the user stayed, the similarity of the points, the number of new points where the user stayed, the number of visits to the points where the user frequently stays, and a plurality. The first aspect of the present invention includes at least one of the number of divided regions passed by the user on the ground surface divided into the divided regions and the number of new divided regions passed by the user on the ground surface. Output device. The output device according to claim 1 or 2, wherein the first feature amount includes at least one of a maximum value, an average value, a median value, and a value indicating variation in the movement speed of the user. The output device according to any one of claims 1 to 3, wherein the first feature amount includes at least one of the length of time the user has gone out, the time zone of going out, and the number of times the user has gone out. Further, a detection unit for detecting the tendency of the cognitive function of the user is further provided depending on whether or not the first feature amount satisfies the condition indicating the tendency of the cognitive function to decline.
The output device according to any one of claims 1 to 4, wherein the condition is determined according to the second feature amount. The output device according to claim 5, wherein the other user includes a person in a state in which the cognitive function is deteriorated. Further, a calculation unit for calculating an evaluation value according to whether or not the first feature amount satisfies the above condition is provided.
The output device according to claim 5 or 6, wherein the detection unit detects a tendency of deterioration of the cognitive function when the evaluation value is equal to or higher than a threshold value. The acquisition unit acquires a plurality of first feature quantities related to the movement of the user.
The output device according to claim 7, wherein the calculation unit calculates the evaluation value so that the evaluation value increases as the number of the first feature amounts satisfying the above conditions increases among the plurality of first feature amounts. ..

Images