JP6899111B2 - Server system, methods and programs executed by the server system - Google Patents

Description

The present invention relates to server systems that help prevent dementia, methods and programs performed by the server systems.

In the medical field, various systems have been developed to support the diagnostic work of doctors. For example, in the system of Patent Document 1, the MRI brain image of the patient is image-analyzed to detect abnormal shadow candidates, the results are stored in a database, and the predicted value of the future onset possibility of the unaffected patient is obtained. I'm calculating. Further, in the system of Patent Document 2, a cerebrovascular image is extracted from an MRI brain image to detect an abnormal part of the cerebrovascular, and the onset tendency due to the abnormal part is predicted based on the spatial position information of the abnormal part. .. Patent Document 3 discloses a system called VSRAD (registered trademark) equipped with image processing / statistical analysis software that reads the degree of atrophy in the vicinity of the parahippocampal gyrus from an MRI brain image. All of these conventional systems have in common that they analyze captured MRI brain images to detect abnormalities and atrophy sites in the brain.

Dementia is one of the brain diseases. There are several types of diseases that cause dementia, and the typical one is Alzheimer's type degenerative disease. When dementia is diagnosed, even if treatment is given from that point on, it is often difficult to control the progression. Therefore, early detection and early treatment of dementia are especially important. However, dementia can be difficult to distinguish from mere forgetfulness, and it is difficult to notice the symptoms of dementia.

Dementia can be prevented by taking appropriate measures such as improving lifestyle habits. Fortunately, recent studies have shown that the hippocampus begins to shrink about five years before the symptoms of dementia clearly appear, and about 15 years ago, substances that are already harmful to the brain. It is becoming known that the accumulation begins (see, for example, page 45 of Non-Patent Document 1). It is effective to prevent dementia if lifestyle-related habits are improved or treated when it is known in advance that there is a risk of dementia.

JP-A-2007-135683 Japanese Unexamined Patent Publication No. 2008-29735 Japanese Unexamined Patent Publication No. 2013-66632 "How to make a'lifelong healthy brain'that you can do yourself" (Takarajimasha, First Edition, 2016)

The problem is that patients themselves cannot easily tell if they are at risk for dementia. A physician may be able to use, for example, the system of Patent Document 3 to read the degree of atrophy near the parahippocampal gyrus of the brain and predict the patient's future risk of dementia. However, the patient does not have such a system. Also, even if a doctor could use such a system to inform a patient of the risk of dementia, the patient would first have to go to the hospital to have an MRI brain image taken, which would be significant for the patient. It is costly and time-consuming.

Therefore, an object of the present invention is to provide a technique that allows a user to easily know the risk of dementia and contribute to the prevention of dementia.

The method executed by the server system according to one aspect of the present invention is to acquire the user's exercise information by communicating with the user's information communication terminal via a network, and the user based on the acquired exercise information. Estimating the brain image of the user, evaluating the user's dementia risk by performing a statistical test with a data group in which the exercise information and the dementia risk are associated with the acquired exercise information, and dementia risk It includes providing the evaluation result to the information communication terminal.

The server system according to one aspect of the present invention captures the user's motion information by communicating with the user's information communication terminal via a network, and obtains the user's brain image based on the acquired motion information. The brain image estimation unit to be estimated, the evaluation unit to evaluate the user's dementia risk by performing a statistical test with the data group in which the exercise information and the dementia risk are associated with the acquired exercise information, and the dementia risk It is provided with a providing unit that provides the evaluation result to the information communication terminal.

The program according to one aspect of the present invention acquires the user's exercise information by (1) communicating with the information communication terminal to a server system that is communicably connected to the user's information communication terminal via a network. And (2) estimating the brain image of the user based on the acquired exercise information, and performing a statistical test on the acquired exercise information with a data group in which the exercise information and the dementia risk are associated with each other, and the user. The purpose is to evaluate the risk of dementia and (3) to provide the evaluation result of the risk of dementia to the information and communication terminal.

The program according to another aspect of the present invention uses (1) a device mounted on the information communication terminal to the user's information communication terminal connected to the server system via a network so as to exercise the user. From the server system that acquires information, (2) transmits the acquired exercise information from the information communication terminal to the server system, and (3) estimates the brain image of the user based on the transmitted exercise information. , A server that evaluates the user's dementia risk by receiving information about the estimated brain image and performing a statistical test with a data group in which the exercise information and the dementia risk are associated with each other for the transmitted exercise information. It receives the evaluation result of the dementia risk from the system and executes it.

According to the present invention, the user can easily know the risk of dementia and can contribute to the prevention of dementia.

It is the schematic of the information processing system including the server system and the information processing terminal of the user which concerns on embodiment. Among the information processing terminals of FIG. 1, it is a block diagram which shows the hardware configuration of a mobile terminal. It is a block diagram which shows the hardware composition of the wearable device among the information processing terminal of FIG. It is a block diagram which shows the hardware configuration of the server system of FIG. It is a figure which shows an example of the subject DB in which exercise information and dementia risk etc. are associated with each other in the server system of FIG. It is a figure which shows an example of a plurality of brain images of a subject. In the server system of FIG. 1, it is a figure which shows an example of the brain atrophy part DB in which the brain atrophy part and the information about the brain atrophy part are associated. In the server system of FIG. 1, it is a figure which shows an example of the advice DB in which the brain atrophy part and the advice of the lifestyle are associated. It is a figure which shows the screen example displayed on the information processing terminal of FIG. It is a figure which shows the screen example displayed on the information processing terminal of FIG. It is a figure which shows the screen example displayed on the information processing terminal of FIG. It is a figure which shows the screen example displayed on the information processing terminal of FIG. It is a figure which shows the screen example displayed on the information processing terminal of FIG. It is a figure which shows the screen example displayed on the information processing terminal of FIG. It is a figure which shows the screen example displayed on the information processing terminal of FIG. It is a figure which shows another example of the screen example displayed on the information processing terminal of FIG. It is a figure which shows another example of the screen example displayed on the information processing terminal of FIG. It is a flow chart which shows an example of the processing in the information processing terminal of FIG. It is a flow chart which shows an example of the processing in the server system of FIG.

Preferred embodiments of the present invention will be described with reference to the accompanying drawings above.

As shown in FIG. 1, the information processing system 100 has information communication terminals 110-1, 110-2, 110-3 ... (hereinafter, collectively referred to as "110") of a plurality of users 1, 2, 3 ... In some cases) and the server system 120 is configured to be connectable to the network 130. The server system 120 is an information processing device that provides an information communication terminal 110 with an evaluation result of a dementia risk, and is composed of one or a plurality of computers. The server system 120 receives or acquires predetermined information such as user's motion information from the information communication terminal 110 by communicating with the information communication terminal 110 via the network 130. In addition, the server system 120 evaluates the user's risk of dementia and determines lifestyle-related advice to the user. Further, the server system 120 transmits or provides evaluation results such as dementia risk and lifestyle advice to the information communication terminal 110 by communicating with the information communication terminal 110 via the network 130. The network 130 is composed of a LAN, a WAN, a wired or wireless network, the Internet, or the like.

The information communication terminal 110 of each user includes a mobile terminal 200, a wearable device 210, or both. For example, the information communication terminal 110-1 of the user 1 includes a mobile terminal 200 and a wearable device 210, and the wearable device 210 is associated with the mobile terminal 200. The information communication terminal 110-2 of the user 2 includes the mobile terminal 200, but does not include the wearable device associated thereto. The information communication terminal 110-3 of the user 3 includes the wearable device 210, but does not include the mobile terminal 200 associated thereto.

The mobile terminal 200 can be configured by a computer having a communication function, a display function, and the like. For example, the mobile terminal 200 is composed of a mobile phone, a smartphone, a PDA, or a tablet-type computer. As an example, the mobile terminal 200 is an iPhone (registered trademark) brand smartphone.

The wearable device 210 is an information communication terminal with a communication function that can be worn and used by a user. The wearable device 210 can take a mode according to the wearing form thereof. For example, in addition to glasses, goggles, watches, wristbands, headsets, earphones, accessories such as necklaces, rings and bracelets, and clothing such as underwear, gloves and socks can be taken. An example of the wearable device 210 is an Apple Watch® brand watch-type device.

The wearable device 210 can be roughly classified into two types, a type associated with the mobile terminal 200 and a type not associated with the mobile terminal 200. In the former type, the wearable device 210 cooperates with the mobile terminal 200 to perform various functions. For example, the wearable device 210 can display information received by the mobile terminal 200 (for example, an incoming mail) on the screen of the wearable device 210, and can transmit information from the mobile terminal 200 by operating the wearable device 210. it can. Further, the wearable device 210 can acquire the exercise information of the user by using the device mounted on the wearable device 210 or the mobile terminal 200. For example, the user's motion information is acquired by linking the information acquired by the motion sensor built in the wearable device 210 with the position information acquired by the GPS device (Global Positioning System) built in the mobile terminal 200. be able to. The wearable device 210 communicates with the mobile terminal 200 and also communicates with the server system 120 via the network 130.

In the latter type, the wearable device 210 performs a predetermined function without coordinating with the mobile terminal 200. For example, the wearable device 210 incorporates devices such as a motion sensor and a GPS device to acquire user motion information. The wearable device 210 also communicates with the server system 120 via the network 130. Then, the wearable device 210 displays the user's exercise information acquired by itself and the information received from the server system 120 on its own screen.

FIG. 2 is a block diagram showing a hardware configuration of the mobile terminal 200. The mobile terminal 200 includes a communication interface 300, a user interface 310, an arithmetic processing unit 320, a storage unit 330, a motion sensor 340, and a GPS device 350. The communication interface 300 has a mobile communication antenna 301 and a wireless antenna 302. The mobile terminal 200 is connected to the network 130 through the mobile communication antenna 301 and performs data communication with the server system 120. Further, the mobile terminal 200 is connected to the wearable device 210 through the wireless antenna 302 and performs data communication with the wearable device 210. As the wireless antenna 302, for example, one corresponding to a predetermined standard such as Bluetooth (registered trademark) or NFC can be used.

The user interface 310 includes a touch panel 311 and a microphone 312. The touch panel 311 has the functions of both a display device and an input device. The display function of the touch panel 311 is composed of a display such as a liquid crystal display, and the evaluation result of the dementia risk, a brain image, and the like are displayed on the screen of the display. The input function of the touch panel 311 is composed of a touch sensor, and detects a user's finger touch operation (operation such as tapping or swiping) on the screen of the display. The microphone 312 functions as a voice input device. In addition, as is well known, hard keys, buttons, speakers, and the like can be included in the user interface 310.

The arithmetic processing unit 320 is composed of a CPU, an MPU, and the like. The arithmetic processing unit 320 operates various functional units by executing a program stored in the storage unit 330 based on various inputs. This program is installed in the mobile terminal 200 by being stored in a storage medium such as a CD-ROM or a USB memory, or being downloaded via the network 130. The arithmetic processing unit 320 has a receiving unit 321 and a transmitting unit 322 as various functional units. The receiving unit 321 receives various information from the server system 120 and the wearable device 210 via the communication interface 300. Similarly, the transmission unit 322 transmits various information to the server system 120 and the wearable device 210 via the communication interface 300.

The storage unit 330 is composed of storage devices such as a hard disk drive, SSD, and RAM, and stores various programs necessary for executing processing in the arithmetic processing unit 320, data necessary for executing various programs, and the like. The storage unit 330 stores software (for example, a web browser or application) for using the dementia risk assessment provided by the server system 120. In addition, the storage unit 330 stores information input by the user via the user interface 310. For example, the storage unit 330 stores various information such as the user's date of birth, age, gender, height, weight, address, occupation, occupation, and regular holidays. Further, the storage unit 330 temporarily stores various information transmitted from the server system 120. Further, the storage unit 330 stores information regarding the amount of exercise of the user calculated by the arithmetic processing unit 320.

The motion sensor 340 detects the movement of the mobile terminal 200, and is composed of, for example, an acceleration sensor. The motion sensor 340 is, for example, a three-axis acceleration sensor, which detects motion in the vertical, horizontal, and rotational directions of the mobile terminal 200. Further, the motion sensor 340 can be a 3-axis acceleration sensor, a 3-axis angular velocity sensor, or a 6-axis sensor. The motion sensor 340 converts the detected movement of the mobile terminal 200 into digital measurement data, and outputs the measurement data to the arithmetic processing unit 320. When the mobile terminal 200 is owned by the user, the movement of the mobile terminal 200 reflects the movement of the user (number of steps, speed, acceleration, etc.). In addition, in order to provide another kind of activity data, another device such as a sensor such as a heart rate monitoring device may be built in the mobile terminal 200.

The GPS device 350 is a position measuring system that measures the position of the mobile terminal 200, and acquires GPS data indicating the position of the mobile terminal 200. When the mobile terminal 200 is owned by the user, the position of the mobile terminal 200 reflects the position of the user. The GPS device 350 outputs the acquired GPS data to the arithmetic processing unit 320. If GPS is not available, the position can be determined using the cellular triangulation method.

By using both the motion sensor 340 and the GPS device 350, the mobile terminal 200 can record a plurality of user motions. For example, when the user exercises from the same place with almost no movement, such as when the user runs on a treadmill, the arithmetic processing unit 320 of the mobile terminal 200 determines the number of steps of the user based on the measurement data from the exercise sensor 340. The amount of exercise of the user is calculated by judging the speed and acceleration (pace). On the other hand, when the user moves outdoors from one place to another, the arithmetic processing unit 320 of the mobile terminal 200 determines the movement speed and movement time of the user based on the position data from the GPS device 350. Then, the amount of exercise of the user is calculated. Of course, in order to improve the accuracy of the user's momentum to be calculated, data from both the motion sensor 340 and the GPS device 350 can also be used. The calculated amount of exercise of the user is, for example, the amount of calories burned by exercise. This information is stored in the storage unit 330. A known method can be used to convert the amount of exercise into the amount of calories burned.

FIG. 3 is a block diagram showing a hardware configuration of the wearable device 210. The wearable device 210 includes a communication interface 400, a user interface 410, an arithmetic processing unit 420, a storage unit 430, a motion sensor 440, and a GPS device 450. Each of these components 400 to 450 is the same as the corresponding components 300 to 350 of the mobile terminal 200, and the same reference numerals are given here, and detailed description thereof will be omitted. The contents of the components of the wearable device 210 can be changed depending on the type of the wearable device 210. For example, when the wearable device 210 is of a type associated with the mobile terminal 200, some of the components of the wearable device 210 can be omitted. For example, the display of the touch panel 411 and the GPS device 450 can be omitted.

FIG. 4 is a block diagram showing a hardware configuration of the server system 120. The server system 120 includes a communication interface 510, an arithmetic processing unit 520, and a storage unit 530. The communication interface 510 connects the server system 120 to the network 130. The arithmetic processing unit 520 is composed of a CPU, an MPU, and the like. The arithmetic processing unit 520 operates various functional units by executing a program stored in the storage unit 530 based on various inputs. This program is installed in a computer by being stored in a storage medium such as a CD-ROM or a USB memory, or by being downloaded via a network 130.

The storage unit 530 is composed of storage devices such as a hard disk drive, SSD, and RAM, and stores various programs necessary for executing processing in the arithmetic processing unit 520, data necessary for executing various programs, and the like. The storage unit 530 stores software (for example, a web browser or an application) for using the method related to the dementia risk assessment executed by the server system 120. In addition, the storage unit 530 stores the subject DB531, the brain atrophy site DB532, and the advice DB533.

As shown in FIG. 5, the subject DB531 stores information on the subject's age, gender, daily exercise amount average, dementia risk, assumed hippocampal volume, and brain image in association with the subject ID. The information stored in the subject DB 531 is data collected in advance from a huge number of subjects. For example, a subject with a subject ID of "1" is calculated to have an assumed hippocampal volume of 24 ml. This is calculated by taking a brain image of a subject with a device such as MRI at a medical institution and analyzing the image. The assumed hippocampal volume is recorded with a plurality of brain images (see: FIG. 6) taken by the subject used to calculate this. In addition, subjects with a subject ID of "1" are recorded to have a "small" risk of dementia. The presence or absence of the onset of dementia and the degree of risk of the onset of dementia recorded are determined by a computer or a doctor from the captured brain image. In addition, the recorded information on the subject's age, gender, and daily physical activity average is obtained after the subject's response to the questionnaire and the like, and the information acquired by the subject's mobile terminal or wearable device. The subject DB531 configured as described above can be said to be a data group in which exercise information and dementia risk are associated with each other, and is a data group in which exercise information, dementia risk, age and gender are associated with each other. It can be said that there is. Further, it can be said that the subject DB 531 is a data group in which the motor information and the brain image are associated with each other. In the example shown in FIG. 5, the one corresponding to the exercise information is the average daily exercise amount, but the present invention is not limited to this. For example, the exercise information in the subject DB531 can be the average amount of exercise for a predetermined period (1 week, 2 weeks, 1 month, etc.).

As shown in FIG. 7, the brain atrophy site DB532 corresponds to the atrophy site of the brain and stores information about the atrophy site. Information about the atrophic site of the brain is, for example, the function of the brain region where the atrophied site is located, the brain symptoms caused by the atrophied site, and the risk of future disease.

As shown in FIG. 8, the advice DB 533 stores information on lifestyle advice in association with the atrophied part of the brain. Lifestyle-related advice can cover a wide range of topics such as exercise, interpersonal communication, intellectual curiosity, sleep, and eating habits. For example, exercise advice is "Let's take a walk for about 30 minutes a day." Similarly, interpersonal communication advice is "more interaction, conversation, eating or spending with people", and intellectual curiosity advice is "enjoy your hobbies, read books, diary".・ Let's write a letter, get in touch with art, learn new things at a cultural school, watch sports, go on a trip, and do cognitive training such as calculation. " In addition, sleep advice is said to be ideal from the viewpoint of brain science, "Let's sleep for about 7 hours", and eating habits advice is "Don't overeat, breakfast is better than bread". Let's eat rice too. " It should be noted that which advice is effective for which brain atrophy site is disclosed in Non-Patent Document 4.

To explain again with reference to FIG. 4, the arithmetic processing unit 520 has various functional units such as an acquisition unit 521, an evaluation unit 522, a brain image estimation unit 523, a brain atrophy site identification unit 524, an advice determination unit 525, and a providing unit. It is equipped with 526. The acquisition unit 521 receives or acquires various information from the information communication terminal 110 via the communication interface 510. For example, the acquisition unit 521 acquires the user's exercise information, age information, and gender information from at least one of the mobile terminal 200 and the wearable device 210 by communication. Various information acquired by the acquisition unit 521 is temporarily stored in the storage unit 530.

The evaluation unit 522 performs a statistical test on the exercise information acquired by the acquisition unit 521 mainly for multivariate analysis such as a data group in which the exercise information and the dementia risk are associated with each other and multiple regression analysis, and the user's dementia. Assess risk. This data group is a subset of the data stored in the subject DB531. Such statistical tests can be used to assess a user's risk of dementia because recent studies have shown that there is a correlation between exercise and dementia. In the statistical test performed by the evaluation unit 522, the acquired exercise information of the user is compared with the enormous amount of exercise information group in the subject DB531 to perform the statistical test. As the statistical test, for example, tests such as t-test, analysis of covariance, and multivariate analysis can be used. For example, by comparing exercise information with a t-test, the degree of exercise of each individual in the group is evaluated. Further, in the statistical test, it is preferable to use, for example, the exercise amount average (calorie consumption average) of a predetermined period (1 week, 2 weeks, 1 month, etc.) among the exercise information of the user acquired by the acquisition unit 521. The predetermined period is preferably one week or more. This is because if short-term data such as less than one week is used, there is a high possibility that a large error will occur in the result when the user happens to have a small amount of exercise due to an event or illness.

The evaluation unit 522 evaluates the user's risk of dementia from the results of the statistical test. This evaluation may, for example, indicate the presence or absence of the risk of dementia, or may indicate the score of the risk of dementia. The dementia risk score can be scaled, for example, in the range of 0 to 100% (1% or more is evaluated as having a dementia risk). When evaluating the dementia risk, the evaluation unit 522 considers at least one of the age information and the gender information acquired by the acquisition unit 521, and considers a data group (a subset of data consisting of exercise information, dementia risk, age and gender). ) And statistical tests can be used to evaluate the user's risk of dementia. This is because, as described above, in the subject DB531, the age and gender are also associated with the motor information and the risk of dementia. By considering age and gender when assessing the risk of dementia, the accuracy of the assessment can be further improved. For example, age- and gender-corrected analysis of covariance may be used to assess the degree of individual activity within a group. The evaluation result of the dementia risk made by the evaluation unit 522 is temporarily stored in the storage unit 530.

The brain image estimation unit 523 estimates the user's brain image based on the motion information acquired by the acquisition unit 521. This estimation can be made using subject DB531, which has a subset of data in which motor information and brain images are associated. For example, since it is possible to formulate what kind of brain image is obtained at what amount of exercise from the subject DB531, by applying the exercise information of the user acquired by the acquisition unit 521 to this, the user Brain image can be estimated. The brain image estimation unit 523 generates data for visualizing the estimated brain image on at least one screen of the user's mobile terminal 200 and the wearable device 210. The generated data of the brain image for visualization is temporarily stored in the storage unit 530.

The brain atrophy site identification unit 524 identifies the brain atrophy site associated with the dementia risk when the evaluation unit 522 evaluates the risk of dementia. For example, the brain atrophy site identification unit 524 identifies the user's brain atrophy site by image analysis of the brain image estimated by the brain image estimation unit 523. The identification result by the brain atrophy site identification unit 524 is temporarily stored in the storage unit 530.

The advice determination unit 525 determines lifestyle-related advice to the user based on the evaluation result of the dementia risk. For example, if the evaluation department 522 evaluates that there is no risk of dementia, general advice such as "Let's keep living as it is" can be decided. On the other hand, when the evaluation unit 522 evaluates that there is a risk of dementia, the advice can be determined by referring to the specific result by the brain atrophy site identification unit 524 in the advice DB 533. For example, if the site of brain atrophy is identified as the prefrontal cortex, the advice is "Let's go out more with interest in various things. I think traveling is also good." ( See also: FIG. 8). This makes it possible to determine effective advice corresponding to the site of brain atrophy.

The content of the advice given by the advice decision unit 525 should be changed based on the exercise information acquired by the acquisition unit 521, regardless of whether it is evaluated that there is a risk of dementia or that there is no risk of dementia. Can be done. For example, when the acquired user's amount of exercise is small, it is possible to encourage them to exercise more. In addition, the content of the advice given by the advice determination unit 525 can be changed according to the dementia risk score. For example, when the score is high (high risk of dementia), the amount of exercise to be advised (walking time, etc.) may be increased as compared with the case where the score is low (low risk of dementia). The information of the advice decided by the advice determination unit 525 is temporarily stored in the storage unit 530.

The providing unit 526 provides the results made by the evaluation unit 522, the brain image estimation unit 523, the brain atrophy site identification unit 524, and the advice determination unit 525 to at least one of the user's mobile terminal 200 and the wearable device 210. For example, the providing unit 526 transmits the evaluation result of the dementia risk by the evaluation unit 522 to the user's mobile terminal 200 and / or the wearable device 210 via the network 130. Other data is similarly transmitted by the provider 526. As a result, the estimated user brain image is visually displayed on the screens of the user's mobile terminal 200 and the wearable device 210 (see, for example, FIGS. 9B, 9C, 10A and 10B). In addition, lifestyle-related advice is displayed on the same screen (see, for example, FIGS. 9G and 10B). Further, on the same screen, information about the brain atrophy site of the specified user, specifically, the information shown in the brain atrophy site DB532 of FIG. 7 is displayed (see, for example, FIGS. 9D, 9F, 10A). At this time, the identified brain atrophy site may be represented in a manner different from that of other sites in the brain (see, for example, FIGS. 9D, 9E, 10A, 10B). For example, for a identified brain atrophy site, it may be expressed in a different manner from other parts of the brain by setting an index indicating the place or coloring it differently from other parts of the brain. Can be done.

The server system 120 is not particularly limited as long as it has the above functions, and may be cloud computing or the like. When the server system 120 is composed of a plurality of computers, for example, it can be divided into a computer for each functional unit of the arithmetic processing unit 520 and a computer for each database (531-533) of the storage unit 530. it can. Further, the computer can be separated for each functional unit of the arithmetic processing unit 520. For example, a computer for the acquisition unit 521 and the provision unit 526 (which serves a direct interface with the user), and a computer for the evaluation unit 522, the brain image estimation unit 523, the brain atrophy site identification unit 524, and the advice determination unit 525. It can be divided into (the former computer and the one that acts as an intermediary between the computer for the storage unit 530).

9A-9G show an example of a screen displayed when a user uses the above-mentioned dementia risk assessment software. In this screen example, the server system 120 acquires exercise information and the like from the user, evaluates the above-mentioned dementia risk, and is provided to the user's information communication terminal 110. Here, a screen example displayed on the mobile terminal 200 of the user's information communication terminal 110 will be described, but the same applies even when the screen is displayed on the wearable device 210.

FIG. 9A shows a screen (initial screen) after the evaluation result of the dementia risk is provided by the server system 120. On this screen, four fields 810, 811, 812 and 813 that accept input from the user are displayed. When the user inputs (tap) any of the fields 810 to 813, the screen transitions to the corresponding screen. The fields 810 to 813 can be, for example, an icon, a box, a link, or the like.

FIG. 9B shows the screen displayed when the user taps field 810 “Your brain image”. On this screen, a plurality of sagittal sections of the user's brain image estimated by the brain image estimation unit 523 are visually displayed. In addition, the field 840 "View 3D stereoscopic image" is also displayed on this screen, and when the user taps this, the screen transitions to the screen shown in FIG. 9C. As shown in FIG. 9C, the body axis cross-sectional image 850 and the volume-rendered stereoscopic image 851 appear as the estimated user brain image. A slide bar 852 is displayed in the vicinity of the body axis cross-sectional image 850. When the user moves the slide bar 852 up and down, the body axis cross-sectional image 850 corresponding to the vertical position of the slide bar 852 is displayed. Similarly, a slide bar 853 is displayed in the vicinity of the stereoscopic image 851. The user can change the angle of the stereoscopic image 851 by moving the slide bar 853 up and down.

FIG. 9D shows the screen displayed when the user taps field 811 “Your healthy brain level”. This screen includes a field 861 showing the user's brain atrophy site 860 identified by the brain atrophy site identification unit 524 with a brain image, and a field 863 showing information 862 about the brain atrophy site 860. The display of the brain atrophy site 860 in the field 861 is different from the other parts of the brain (coloring) in order to differentiate from the other parts of the brain. When the user taps the brain atrophy site 860 in the field 861, the screen transitions to the screen shown in FIG. 9E. The screen shown in FIG. 9E includes a field 870 showing the brain atrophy site 860 with a brain image and a field 872 showing the graph 871 with respect to the degree of brain atrophy. Graph 871 is a normal distribution created based on the subject data (data in the subject DB531) shown in FIG. 5 for the volume of the brain region where the brain atrophy site 860 is located, and is a normal distribution of the user having the brain atrophy site 860 there. It shows the position 873. This allows the user to visually grasp the degree of atrophy of his / her brain in the group. The data of the subjects used to create the graph 871 may be of the same age and gender as the user, or both.

FIG. 9F shows the screen displayed when the user taps the field 812 “View overall rating”. This screen includes a field 880 showing the evaluation result of the dementia risk by the evaluation unit 522 and a field 881 showing the brain image. Here, it is assumed that there is a risk of dementia, and the field 880 is a comparison with the brain region (here, “frontal lobe”) where the brain atrophy site related to the risk of dementia exists and the population. Explanations such as the result (here, "bottom 20%") are displayed. Further, the brain image shown in the field 881 can take various modes, for example, a stereoscopic image (stereoscopic image 851 shown in FIG. 9C), a known stereoscopic image of the brain that has not been estimated, a two-dimensional image, and the like. Can be taken. Further, the brain image in the field 881 may display the brain region or the brain atrophy site referred to in the field 880 in a mode (coloring) different from that of the other sites.

FIG. 9G shows the screen that is displayed when the user taps field 813 “Get advice”. This screen includes a field 890 showing advice determined by the advice determination unit 525 and a field 891 showing a brain image. The field 891 can be configured in the same manner as the field 881 described above.

10A and 10B show another screen example displayed when the user uses the above dementia risk assessment software. Here, an example of a screen displayed on the mobile terminal 200 of the user's information communication terminal 110 will be described, but the same applies even when the screen is displayed on the wearable device 210.

FIG. 10A shows another screen example that is displayed when the user taps field 811 “Your healthy brain level” in FIG. 9A. This screen includes a field 901 showing a brain image 900, a field 902 showing an evaluation result of dementia risk, and a "next" field 903. The brain image 900 can take various forms like the brain image of FIG. 9F, but here it is a stereoscopic image. In addition, the brain image 900 displays the user's brain atrophy site identified by the brain atrophy site identification unit 524 in a mode (coloring) different from that of other sites. In the field 901, a slide bar 905 and an index 906 indicating the degree of atrophy are displayed in the vicinity of the brain image 900. Similar to the slide bar 854 of FIG. 9C, the slide bar 905 has a function of changing the angle of the brain image 900 by a vertical movement operation by the user. The index 906 consists of bars and is used to indicate the degree of atrophy of the user's brain using, for example, color differences or grayscale shades. Here, it is assumed that the user's brain atrophy site identified by the brain atrophy site identification part 524 is the frontal lobe, and the frontal lobe or the brain atrophy site is represented by a color close to "large atrophy" in the index 906 with respect to the brain image 900. , Other parts are shown in colorless. In the field 902, the same evaluation result as the evaluation result shown in the field 880 of FIG. 9F and the information related to the brain atrophy site similar to the information shown in the field 863 of FIG. 9D (information about the frontal lobe which is the brain atrophy site) are displayed. To.

FIG. 10B shows the screen displayed when the user taps the field 903 “Next” on the screen shown in FIG. 10A. On this screen, instead of the field 902 shown in FIG. 10A, a field 910 showing lifestyle advice is displayed. The field 910 can be configured in the same manner as the field 890 shown in FIG. 9G.

The above screen is provided to the user. By recording the daily amount of exercise in at least one of the mobile terminal 200 and the wearable device 210, the user can evaluate his / her dementia risk through at least one of the mobile terminal 200 and the wearable device 210. You can know. Therefore, the user does not have to go to the hospital to have the brain image taken. In addition to the evaluation results of their own dementia risk, users can also provide lifestyle advice, their own estimated brain images, and brain atrophy sites related to dementia risk on the mobile terminal 200 and. It can be known through at least one of the wearable devices 210.

FIG. 11 is a flow chart showing an example of processing in the information communication terminal 110 of the user. Software for using the dementia risk assessment provided by the server system 120 is installed in the information communication terminal 110. Further, the information communication terminal 110 is communicably connected to the server system 120 via the network 130.

First, the information communication terminal 110 acquires the user's exercise information by using the device mounted on the information communication terminal 110 (step S1000). This device is, for example, the motion sensor 340 and the GPS device 350 of the mobile terminal 200, and the motion sensor 440 and the GPS device 450 of the wearable device 210. The user's exercise information is a quantification of the user's exercise amount during a predetermined period (1 day, 1 week, 2 weeks, 1 month, etc.) of the user, and is, for example, the calorie consumption amount due to the user's exercise. The information communication terminal 110 acquires the age information and the gender information of the user together with or separately from the acquisition of the exercise information (step S1001).

Next, the information communication terminal 110 transmits the acquired exercise information from the information communication terminal 110 to the server system 120 (step S1010). In the server system 120, the transmitted exercise information is subjected to a statistical test with a data group (see: FIG. 5) in which the exercise information and the dementia risk are associated with each other, and the user's dementia risk is evaluated. When the information communication terminal 110 also transmits the acquired user's age information and gender information to the server system 120 (step S1011), the server system 120 evaluates the user's dementia risk based on these information as well. Will be done. When the processing in the server system 120 is completed, the information communication terminal 110 receives the evaluation result of the dementia risk from the server system 120 (step S1020). As a result, the evaluation result of the dementia risk is displayed on the screen of the information communication terminal 110. In addition, the information communication terminal 110 receives lifestyle advice, its own estimated brain image, and information about the brain atrophy site related to the risk of dementia from the server system 120, and these are displayed on the screen ( Step S1021).

FIG. 12 is a flow chart showing an example of processing in the server system 120. Software for using the dementia risk assessment provided by the server system 120 is installed in the server system 120.

First, the server system 120 acquires the user's exercise information by communicating with the user's information communication terminal 110 via the network 130 (step S1100). This step is performed after step S1010 in FIG. Next, the server system 120 evaluates the user's dementia risk by performing a statistical test on the acquired exercise information with a data group (reference: FIG. 5) in which the exercise information and the dementia risk are associated with each other (step). S1110). When the server system 120 acquires at least one of the user's age information and gender information together with the user's exercise information (step S1101), the data group is based on at least one of the user's age information and gender information. (Reference: FIG. 5) and a statistical test are performed to evaluate the user's risk of dementia (step S1111).

After evaluating the dementia risk, the server system 120 estimates the user's brain image based on the acquired motor information, and generates data for visualizing the estimated brain image on the screen of the information communication terminal 110 (step S1120). ). In estimating this brain image, as in the case of the statistical test, if, for example, the exercise amount average (calorie consumption average) of a predetermined period (1 week, 2 weeks, 1 month, etc.) is used among the acquired exercise information. Good. In addition, the server system 120 determines lifestyle-related advice to the user based on the evaluation result of the risk of dementia (step S1130). At this time, the server system 120 may determine lifestyle advice based on the acquired exercise information (step S1131). In addition, if the results of steps S1110 and S1111 evaluate that there is a risk of dementia, the server system 120 identifies the site of brain atrophy associated with that risk of dementia (step S1140).

Next, the server system 120 provides the user's information communication terminal 110 with the evaluation result of the dementia risk (step S1150). In addition, the server system 120 provides the information communication terminal 110 with the estimated user's brain image, the determined lifestyle advice, and the information about the identified brain atrophy site (steps S1151, S1152, S1153). The identified brain atrophy site is displayed on the screen of the information communication terminal 110 in a manner different from that of other parts of the brain.

According to the present embodiment described above, the user can easily know the risk of dementia and can contribute to the prevention of dementia.

The embodiments described above are for facilitating the understanding of the present invention, and are not for limiting and interpreting the present invention. Each element included in the embodiment and its arrangement, conditions, shape, size, and the like are not limited to those exemplified, and can be changed as appropriate. For example, one or a plurality of processes (step S1001 and the like) shown by the dotted line frame in FIGS. 11 and 12 may be omitted as appropriate.

100 ... Information processing system, 110 ... Information communication terminal, 120 ... Server system, 130 ... Network, 200 ... Mobile terminal, 210 ... Wearable device, 300 ... Communication interface, 301 ... Mobile communication antenna, 302 ... Wireless antenna, 310 ... User interface, 311 ... Touch panel, 312 ... Microphone, 320 ... Arithmetic processing unit, 321 ... Receiver unit, 322 ... Transmitter, 330 ... Storage unit, 340 ... Motion sensor, 350 ... GPS device, 400 ... Communication interface, 410 ... User interface, 420 ... Arithmetic processing unit, 430 ... Storage unit, 440 ... Motion sensor, 450 ... GPS device, 510 ... Communication interface, 520 ... Arithmetic processing unit, 521 ... Acquisition unit, 522 ... Evaluation unit, 523 ... Brain image estimation Department, 524 ... Brain atrophy site identification part, 525 ... Advice decision part, 526 ... Providing part, 530 ... Memory part, 513 ... Subject DB, 532 ... Brain atrophy site DB, 533 ... Advice DB, 810 to 815, 840 ... , 850 ... body axis cross-sectional image, 851 ... stereoscopic image, 852, 853 ... slide bar, 860 ... brain atrophy site, 861 ... field, 862 ... information, 863, 870 ... field, 871 ... graph, 872 ... field, 873 ... User position, 880, 881 ... field, 890, 891 ... field, 900 ... brain image, 901-903 ... field, 905 ... slide bar, 906 ... index, 910 ... field

Claims (13)

Acquiring the user's exercise information by communicating with the user's information communication terminal via a network, and
Estimating the user's brain image based on the acquired exercise information,
For the acquired exercise information, perform a statistical test with a data group in which the exercise information and the dementia risk are associated with each other to evaluate the dementia risk of the user.
To provide the evaluation result of dementia risk to the information and communication terminal,
The method performed by the server system, including. And generating data for visualizing estimated boss was brain images on a screen of the information communication terminal,
Providing the generated data to the information communication terminal and
The method performed by the server system according to claim 1, further comprising. Determining lifestyle-related advice to the user based on the evaluation result of dementia risk,
Providing the determined lifestyle advice to the information and communication terminal,
The method performed by the server system according to claim 1 or 2, further comprising. The method performed by the server system according to claim 3, further comprising determining the lifestyle advice based on the acquired exercise information. If assessed as at risk for dementia
Identifying the site of brain atrophy associated with the risk of dementia
Providing information about the identified brain atrophy site to the information communication terminal, and
The method performed by the server system according to any one of claims 1 to 4, further comprising. It further includes displaying a brain image including the identified brain atrophy site on the screen of the information communication terminal.
The method performed by the server system according to claim 5, wherein the brain image represents the identified brain atrophy site in a manner different from other parts of the brain. In the data group, at least one of age and gender is associated with motor information and dementia risk.
The method further comprises acquiring at least one of the user's age information and gender information.
The server according to any one of claims 1 to 6, wherein assessing the risk of dementia includes performing a statistical test with the data group based on at least one of the acquired age information and gender information. The method performed by the system. The method executed by the server system according to any one of claims 1 to 7, wherein the information communication terminal includes at least one of a mobile terminal and a wearable device. An acquisition unit that acquires the user's exercise information by communicating with the user's information communication terminal via a network.
A brain image estimation unit that estimates the user's brain image based on the acquired motion information,
With respect to the acquired exercise information, an evaluation unit that evaluates the dementia risk of the user by performing a statistical test with a data group in which the exercise information and the dementia risk are associated with each other.
A provider that provides the evaluation results of dementia risk to the information and communication terminal, and
Server system with. The server system according to claim 9, further comprising a storage unit for storing the data group. To a server system that is connected to a user's information communication terminal so that it can communicate via a network.
By communicating with the information communication terminal, the movement information of the user can be acquired.
Estimating the user's brain image based on the acquired exercise information,
For the acquired exercise information, perform a statistical test with a data group in which the exercise information and the dementia risk are associated with each other to evaluate the dementia risk of the user.
To provide the evaluation result of dementia risk to the information and communication terminal,
A program that executes. To the information communication terminal of the user who is connected to the server system via the network.
By using the device mounted on the information communication terminal, the movement information of the user can be acquired.
Sending the acquired exercise information from the information communication terminal to the server system,
And receiving the server system to the estimated brain image of the user based on the transmitted motion information, the information about the estimated brain image,
Regarding the transmitted exercise information, the evaluation result of the dementia risk is received from the server system that evaluated the dementia risk of the user by performing a statistical test with a data group in which the exercise information and the dementia risk are associated with each other. To do and
A program that executes. The program according to claim 12, wherein the information communication terminal includes at least one of a mobile terminal and a wearable device.

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