Improved cognitive function training application control method and device

Abstract

To provide a method of controlling a cognitive function training application which significantly improves symptoms of users with cognitive impairment.SOLUTION: A method disclosed herein comprises: determining whether or not a cognitive function training application has been initiated by an input from a user to a terminal; optimizing cognitive function training provided by the cognitive function training application to suit the user according to a result of the determination as to whether the cognitive function training application has been initiated or not and information on the user of the terminal; and providing the optimized cognitive function training through the terminal once the cognitive function training application is initiated or resumed by the user.SELECTED DRAWING: Figure 10

Description

[Technical field]

[0001] The present invention relates to a method for controlling an application installed on a terminal, and more particularly, to a method for controlling an application that trains cognitive functions and an apparatus for implementing the method. [Background technology]

[0002] South Korea is considered to have entered an aging society. As the aging society advances, the number of dementia patients will increase rapidly, and the social costs incurred in treating and caring for dementia patients will inevitably increase gradually.

[0003] Training that stimulates the areas of the brain responsible for cognitive function has been proven to be effective in preventing dementia and improving the symptoms of existing dementia, and several papers have proven that when patients with cognitive impairment in the pre-stages of dementia receive training that can improve their cognitive function, their cognitive function improves to a greater extent than patients who have already developed dementia. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Republic of Korea Patent Publication No. 10-2020-0066578 (Published on June 10, 2020) Summary of the Invention [Problem to be solved by the invention]

[0005] The technical problem to be solved by the present invention is to provide a method for controlling an application that trains cognitive functions and an apparatus for implementing the method. [Means for solving the problem]

[0006] A method according to one embodiment of the present invention for solving the technical problem includes the steps of determining whether a cognitive function training application has been started by a user input to a terminal, optimizing the cognitive function training provided by the cognitive function training application to suit the user based on the result of determining whether the cognitive function training application has been started and user information of the terminal, and providing the optimized cognitive function training through the terminal when the cognitive function training application is started or resumed by the user.

[0007] In the method, the user information may be information that has been collected in advance by a sensor of the terminal.

[0008] In the method, the user information may be information regarding the user's circadian rhythm and schedule collected by a sensor of the terminal.

[0009] In the method, the user information may be at least one of the user's sleep time, the number of people living with the user, an external activity level, and a depression level, which are inputted after the cognitive function training application is first executed.

[0010] In the method, the optimizing step may provide a visual or audible output of the range of training times during the day that is most suitable for the user.

[0011] In the method, the user information may be external information for the day on which the cognitive function training application provides cognitive function training and personal information of the user for the day.

[0012] In the method, the optimizing step may optimize cognitive training in real time taking into account collected user input after it is determined that the cognitive training application has been initiated.

[0013] In the method, when the user's input exceeds a certain level, the cognitive function training can be interrupted for a certain period of time or the training speed of the cognitive function training can be changed.

[0014] In the method, if the user's input is below a certain level, the cognitive function training may be suspended for a certain period of time or the training speed of the cognitive function training may be changed.

[0015] In the method, input unrelated to the user may be collected in addition to the user's input, and the cognitive function training may be interrupted when the collected input exceeds a certain level.

[0016] In the method, the step of providing the optimized cognitive function training through the terminal can suspend cognitive function training until the collected input falls below a certain level.

[0017] In the method, when the user's input satisfies a preset condition, at least one of visual guidance information and audio guidance information may be output through the terminal.

[0018] In the method, a fatigue level of the user can be calculated based on an input from the user, and a progress speed of the optimized cognitive function training can be adjusted based on the calculated fatigue level.

[0019] A system according to another embodiment of the present invention for solving the technical problems includes a start determination unit that determines whether a cognitive function training application has been started by a user's input to a terminal, a training optimization unit that optimizes the cognitive function training provided by the cognitive function training application to suit the user based on the result of determining whether the cognitive function training application has been started and user information of the terminal, and a training provision unit that provides the optimized cognitive function training through the terminal when the cognitive function training application is started or resumed by the user.

[0020] An embodiment of the present invention may provide a computer program stored in a computer readable storage device for carrying out the method. Effect of the Invention

[0021] According to the present invention, the symptoms of a user suffering from cognitive impairment can be significantly improved. [Brief description of the drawings]

[0022] [Figure 1] FIG. 1 is a schematic diagram showing an overall system for implementing the present invention. [Diagram 2] FIG. 2 illustrates a logical system block diagram of a training application according to one embodiment of the present invention. [Diagram 3] FIG. 3 is a block diagram showing an example of a processing section subdivided according to function. [Figure 4] FIG. 4 is a flow chart illustrating an example of an operational process of the sub-modules of the processing unit of FIG. [Diagram 5] FIG. 5 is a diagram illustrating an improved cognitive function training application control method according to an embodiment of the present invention. [Figure 6] FIG. 6 is a diagram illustrating an embodiment in which the absence of a user is detected and cognitive function training is optimized. [Figure 7A] FIG. 7A is a diagram illustrating an example in which cognitive function training is optimized in a situation in which a user's voice is normally input. [Figure 7B] FIG. 7B is a diagram illustrating an example in which cognitive function training is optimized in a situation in which the user's voice is normally input. [Figure 8] FIG. 8 is a diagram illustrating an example of a situation in which cognitive function training is interrupted. [Figure 9] FIG. 9 is a diagram illustrating an example of outputting a training time range that is most suitable for a user. [Figure 10]FIG. 10 is a flowchart illustrating an example of the cognitive function training application control method described with reference to FIGS. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] Since the present invention can be modified in various ways and can have various embodiments, a specific embodiment will be illustrated in the drawings and described in detail. The effects and features of the present invention, as well as methods for achieving the same, will become apparent from the following detailed description of the embodiments together with the drawings. However, the present invention is not limited to the embodiments disclosed below, and can be embodied in various forms.

[0024] Hereinafter, an embodiment of the present invention will be described in detail with reference to the accompanying drawings. When describing with reference to the drawings, the same or corresponding components are given the same reference numerals, and duplicate descriptions thereof will be omitted.

[0025] In the following embodiments, the terms "first", "second" and the like are not used in a limiting sense but are used for the purpose of distinguishing one component from another component.

[0026] In the following embodiments, singular expressions include plural expressions unless the context clearly indicates otherwise.

[0027] In the following embodiments, terms such as "include" or "have" mean the presence of features or components described in the specification, and do not preclude the possibility that one or more other features or components may be added.

[0028] When an embodiment can be embodied in other ways, the order of certain steps may be performed out of the order described, for example, two steps described in succession may be performed substantially simultaneously or may be performed in the reverse order from that described.

[0029] FIG. 1 is a schematic diagram showing an overall system for implementing the present invention.

[0030] Referring to FIG. 1, an overall system 1 according to the present invention has a structure in which a user terminal group 110 and a management server 20 are connected via a communication network 130.

[0031] The user terminal group 110 may include at least one or more user terminals. For example, the number of user terminals included in the user terminal group 110 may be one or n as shown in Figure 1. In Figure 1, n may be an integer equal to or greater than 1.

[0032] Each user terminal included in the user terminal group 110 is a terminal of a user who uses the training program according to the present invention, and refers to an electronic device equipped with a communication module capable of communicating with the management server 20 .

[0033] The user terminal means a smart device including an input device for receiving user input, an output device (display) for visually outputting the input of the user terminal and the processing result of the terminal, and a communication module capable of communicating with an external device, and is not limited in size or type as long as it includes only the input device, output device, and communication module described above. For example, in FIG. 1, the user terminal is shown in the form of a smartphone, but the user terminal may be a PC, a notebook computer, a netbook, or the like capable of communicating with the management server 20.

[0034] A user who uses a user terminal means a person who uses an application for improving symptoms of a patient with cognitive impairment, and may be a patient diagnosed with cognitive impairment or a guardian of the patient. As another example, the user may be a tester who repeatedly runs the application to improve its performance.

[0035] The management server 20 is a server in which an integrated management program is installed, and refers to a server that manages and controls data flow while communicating with a plurality of user terminals included in the user terminal group 110. An integrated management program (integrated management application) is installed in the management server 20, and according to an embodiment, a part of the integrated management program is embodied in a client form operated by a user terminal, and can be installed in the user terminals included in the user terminal group 110.

[0036] The communication network 130 performs a function of connecting the user terminals included in the user terminal group 110 to the management server 20, and may include various wired and wireless communication networks such as a data network, a mobile communication network, and the Internet.

[0037] In the present invention, an application refers to a logical device that can control a screen output from a user terminal included in the user terminal group 110 under the control of the management server 20. An application does not have a physical form and can undergo a process of being optimized for a user who uses the application multiple times. That is, the application can be continuously updated based on an input entered by a user through a user terminal and an instruction received by the management server 20. A patient with cognitive impairment can improve symptoms of cognitive impairment by repeatedly using an application operated by a user terminal. Since an application is a program embodied in a process that can improve symptoms of cognitive impairment, it will be referred to as a "training application" for convenience of explanation below.

[0038] The training application may be installed and operated in at least one of the user terminal and the management server 20. As an example, the training application may be installed in the user terminal and controlled so that various training algorithms capable of improving the symptoms of cognitive impairment of the user are visually, audibly, and tactilely output. As another example, the training application may be installed in the management server 20 and embodied in a form that controls the contents to be output on the display of the user terminal. In this case, only a simple client that visually, audibly, and tactilely displays data received from the management server 20 is installed in the user terminal, and the function of dynamically controlling the execution of the training algorithm according to the user's input is performed by the training application installed in the management server 20. As yet another example, the training application may be embodied in a form that is divided and installed in the user terminal and the management server 20. In other words, as long as only the operating characteristics of the training application fall within the scope of the present invention, the scope of the present invention is not limited by the form in which the training application is installed or the type of device in which the training application is installed.

[0039] FIG. 2 illustrates a logical system block diagram of a training application in accordance with one embodiment of the present invention.

[0040] The training application is a device that is not physically detected but logically exists to embody the functionality for improving symptoms of cognitive impairment in accordance with the present invention, and hereinafter the training application may be referred to as a "training device."

[0041] 2, it can be seen that a training device 200 according to an embodiment of the present invention includes a database 210, a communication unit 230, a processing unit 250, and an output unit 270. Depending on the embodiment, the training device according to the present invention may be embodied in a form in which the communication unit 230 and the output unit 270 are included in the processing unit 250, or may be embodied so as to be operable substantially only by the database 210 and the processing unit 250.

[0042] The database 210 stores various data necessary for the training device to operate. As an example, the database 210 stores a program for executing a training algorithm for improving cognitive function while communicating with the management server 20, and can execute a function of temporarily or semi-permanently storing data processed by the processing unit 250.

[0043] The communication unit 230 performs a process for communicating with the management server 20 when the training device is installed in a user terminal. Specifically, the communication unit 230 can process an authentication procedure required to run the training device while communicating with the management server 20. The authentication procedure can be performed by a prescription code issued by a doctor, which will be described later. When the training device is embodied in the management server 20, the communication unit 230 can be omitted.

[0044] The processing unit 250 processes data received and transmitted by the communication unit 230, and prepares and controls a screen to be output by the training device to the display of the user terminal. The processing unit 250 may refer to a data processing device having a structured circuit for executing a function expressed by a code or an instruction included in a program. For example, the processing unit 250 may be at least one of a microprocessor, a processor core, a multiprocessor, an application-specific integrated circuit (ASIC), and a field programmable gate array (FPGA). As described above, when the training device is not embodied as a physical device but is embodied only as a logical device, the processing unit 250 may be embodied in the form of a virtual machine that operates by imitating the operating characteristics of at least one of a microprocessor, a processor core, a multiprocessor, an ASIC, and an FPGA.

[0045] In one embodiment, the processing unit 250 may perform a function of combining data received by the communication unit 230 with information stored in the database 210 and processing the combined data, or issuing an instruction to the communication unit 230 and the output unit 270 to operate appropriately to implement the method according to the present invention. The functions performed by the processing unit 250 are not limited to a specific function, and although the processing unit 250 is shown as a single module in FIG. 2, the processing unit 250 may be divided into multiple modules depending on the process of the processing unit 250. The processing unit 250 configured with divided modules will be described later with reference to FIG. 3.

[0046] The output unit 270 performs a function of calculating and outputting various data in response to a command from the processing unit 250. The output unit 270 performs a function of calculating and outputting various data in response to a command from the processing unit 250, and may be embodied in a form included in the processing unit 250 or may be omitted depending on the embodiment.

[0047] FIG. 3 is a block diagram showing an example of a processing section subdivided according to function.

[0048] In FIG. 3, user terminal 110-1 is an exemplary illustration of one of the n user terminals included in user terminal group 110 described in FIG. 1, and user terminal 110-1 refers to an electronic device equipped with a display device that visually outputs the results of data processing by user terminal 110-1, a speaker that audibly outputs the results, and an input device that receives user input.

[0049] 3, the user terminal 110-1 is shown in the form of a smartphone, but the user terminal 110-1 when the present invention is embodied is not limited to a smartphone, and may include all devices installed in a fixed position such as a general personal computer (PC), and mobile terminals such as a tablet personal computer (Tablet PC) and a netbook. Therefore, the training device 200 may be driven in a form included in other hardware devices such as a microprocessor or a general-purpose computer system. That is, the training device 200 may be directly mounted on the terminal 110-1, or may be embodied in a form connected to the terminal 110-1 via a wired or wireless network and controlling various data output to the display and speaker of the terminal 110-1.

[0050] In Fig. 3, only the processing unit 250 of the training device 200 is highlighted, and referring to Fig. 3, it can be seen that the processing unit 250 includes a first output control unit 251, a second output control unit 253, a training evaluation unit 255, and a visual display control unit 257. The processing unit 250 and submodules of the processing unit 250 in Fig. 3 are only components shown to highlight the features of the embodiment of the present invention. Therefore, it will be understood by a person skilled in the art that an embodiment different from the embodiment shown in Fig. 3 may further include other general-purpose components in addition to the components shown in Fig. 3.

[0051] The first output control unit 251 responds to an input to the user terminal and controls the first training algorithm to be output to the user terminal. Here, the input to the user terminal means that the user applies a specific input to the user terminal through an input device, and can include not only input of vowels and consonants to compose a sentence, but also touch input to a touchpad of the user terminal, voice input to a speaker of the user terminal, and shake input by holding and shaking the user terminal.

[0052] The user can check the training algorithm output from the user terminal and input corresponding to the training algorithm to perform training to improve the symptoms of cognitive impairment, and the first output control unit 251 can control the first training algorithm to be output to the user terminal when an appropriate user input is detected. Here, the appropriate user input can be authentication information for outputting the first training algorithm. For example, the user can execute an application installed in the user terminal 110-1 and log in, and if the user is not yet authorized to use the application, the user can perform a membership registration procedure through a membership registration.

[0053] In one embodiment, a user can input a prescription code given by a doctor in addition to a normal login procedure, and output a first training algorithm. The first output control unit 251 can verify whether the input prescription code is a valid code through communication with an EMR (Electronic Medical Record) server, and can control to output a first training algorithm if the prescription code is valid. The prescription code can be, but is not limited to, eight digits. Depending on the embodiment, the first output control unit 251 can process information authenticated by the prescription code in addition to the login information.

[0054] In the present invention, the first training algorithm refers to a regular training algorithm that is first performed to improve the symptoms of cognitive impairment of a user, and is distinguished from a second training algorithm described below. The first training algorithm may include a plurality of detailed training algorithms, and may be treated as a type of algorithm set due to the characteristic of including a plurality of detailed training algorithms.

[0055] The second output control unit 253 may control the second training algorithm to be output to the user terminal 110-1 when the first training algorithm is completed. The second training algorithm may also include a plurality of detailed training algorithms, similar to the first training algorithm, and may be treated as a type of algorithm set due to the characteristic of including a plurality of detailed training algorithms. The second output control unit 253 may receive history information regarding the execution and completion of the first training algorithm by the first output control unit 251, and may control the second training algorithm to be output to the user terminal 110-1 if there is valid history information. The detailed training algorithm included in the second training algorithm is different from the detailed training algorithm included in the first training algorithm, and the second training algorithm is configured as an algorithm for greatly amplifying the primary training effect when the primary training for the symptoms of the cognitive impairment of the user is executed by the first training algorithm. That is, the second training algorithm means a training algorithm that is premised on the first training algorithm being executed preemptively.

[0056] In one embodiment, the second output control unit 253 may control the second training algorithm to be output from the user terminal 110-1 after a predetermined time has elapsed since the first training algorithm has ended. The symptom improvement effect of cognitive impairment according to the present invention may be expressed while the first training algorithm and the second training algorithm are sequentially and repeatedly executed, and in particular, in order to maximize the training effect for the second training algorithm, it is preferable to rest the brain for a certain period of time after the training according to the first training algorithm is executed. In order to maximize the training effect as described above, the second output control unit 253 may control the second training algorithm to be output to the user terminal 110-1 only after a predetermined period of time has elapsed, and may control the second training algorithm not to be output even if the first training algorithm has ended if the predetermined period of time has not elapsed. Here, the predetermined period of time may be one hour, and may be set to a time shorter or longer than one hour depending on the embodiment.

[0057] In the present invention, the number of detailed training algorithms included in the first training algorithm may be a fixed first number, for example, the first number may be three, but is not limited thereto.

[0058] In addition, in the present invention, the number of detailed training algorithms included in the second training algorithm may be a number selected by a third number according to a preset condition from a fixed second number. For example, the second number may be 9 and the third number may be 4, but is not limited thereto. The preset conditions set in the second output control unit 253 may be various.

[0059] In addition, in the present invention, the criterion for selecting the third number may be the result of evaluation of the user's input. If there is a detailed training algorithm that is evaluated as being weak during training by the user, it may be included in the training included in the third number as a mandatory part. The second output control unit 253 may grasp the strengths and weaknesses of the user in cooperation with the training evaluation unit 255 and guide the training to proceed in a manner that complements the weaknesses. That is, the first training algorithm is mandatory to be executed in its entirety, but only a part of the detailed training algorithm included in the second training algorithm may be executed, and a criterion for selecting the part may be the user's training achievement level.

[0060] The training for improving symptoms of cognitive impairment performed according to the present invention may be performed on a basic unit of one day. That is, the first training algorithm and the second training algorithm can be effectively processed only when they are executed sequentially on the same day. As an example, when the first training algorithm ends at 23:30 on a specific date and the predetermined time required for the second training algorithm to be output is set to one hour, the second output control unit 253 can control the first output control unit 251 to output the first training algorithm to the user terminal 110-1 as the first training of the date, not the second training algorithm, even if the user executes a training application at 0:30 on the day following the specific date after the first training algorithm ends. The process of executing the first training algorithm and the second training algorithm on the same day will be described later.

[0061] When the second training algorithm is completed, the training evaluation unit 255 can evaluate the user's input to the first training algorithm and the second training algorithm. Here, the user's input to the first training algorithm and the second training algorithm can be a training result for the training algorithm. When the first training algorithm or the second training algorithm is output to the user terminal, at least a part of the input input by the user through the input device of the user terminal 110-1 can be the training result of the first training algorithm or the second training algorithm, and the training evaluation unit 255 collects the training results and measures whether the user's cognitive impairment symptoms have improved or worsened compared to the past with a grade or score.

[0062] The visual display control unit 257 may control the user terminal 110-1 to output a first visual display based on the result of the evaluation by the training evaluation unit 255. Here, the first visual display may be output through a display of the user terminal 110-1, and the visual effect (color, shape, pattern, sparkle, etc.) of the first visual display may vary depending on the training sincerity and training execution level of the training algorithm performed by the user.

[0063] As an example, the first visual representation may be a flower of memory. In the present invention, the flower of memory is a representative example of a visual representation that may be displayed in a variety of ways as the user continues to train for improving symptoms of cognitive impairment, and has a characteristic that the more sincerely the user participates in the training and the better the user performs the training, the more the flower of memory will improve in appearance.

[0064] The memory flower can change its appearance from a bud to a full bloom. In the present invention, the memory flower does not only provide the user with an aesthetic effect, but can provide a better visual effect according to the user's trainability and training performance, and can motivate the user to participate in training more enthusiastically. In other words, the memory flower improves the sustainability of training.

[0065] In addition, the visual display control unit 257 can visually stimulate the area of ​​the user's brain responsible for cognitive function by repeatedly and chronologically showing the user beautiful natural phenomena such as the memory flower, and can induce the user to improve the symptoms of cognitive dysfunction. In addition, the user can feel a sense of accomplishment as he visually checks the increasing number of memory flowers through the user terminal.

[0066] FIG. 4 is a flow chart illustrating an example of an operational process of the sub-modules of the processing unit of FIG.

[0067] The method according to FIG. 4 can be implemented by the first output control unit 251, the second output control unit 253, the training evaluation unit 255, and the visual display control unit 257 described in FIG. 3, and therefore, hereinafter, the method will be described with reference to FIG. 3, and any overlapping description with the contents described in FIG. 3 will be omitted.

[0068] The first output control unit 251 can control the first training algorithm to be output in response to an input to the user terminal (S410).

[0069] The second output control unit 253 can perform control so that the second training algorithm is output when the first training algorithm is completed (S430).

[0070] The training evaluator 255 may evaluate the user's inputs to the first and second training algorithms S450 once the second training algorithm is completed.

[0071] The visual display control unit 257 may control a visual display to be output to the user terminal based on the result of the evaluation performed by the training evaluation unit 255 S470.

[0072] FIG. 5 is a diagram illustrating an improved cognitive function training application control method according to an embodiment of the present invention.

[0073] In FIG. 3, the processing unit 250 may include a first output control unit 251, a second output control unit 253, a training evaluation unit 255, and a visual display control unit 257, and it has already been explained that the first output control unit 251, the second output control unit 253, the training evaluation unit 255, and the visual display control unit 257 can logically embody an application (hereinafter, "cognitive function training application") that can train the cognitive function of the user by controlling the screen output to the user terminal 110-1.

[0074] The following describes an improved cognitive function training application control method that can significantly improve the effect of cognitive function training provided to a user by effectively controlling the process of the above-mentioned cognitive function training application.

[0075] JPEG0007671083000001.jpg65154 Table 1 is a table for explaining an apparatus for implementing the above-mentioned improved cognitive function training application control method. More specifically, the modules listed in Table 1 are not directly shown in FIG. 3, but they refer to detailed modules of an apparatus for implementing the above-mentioned improved cognitive function training application control method, and may be implemented in a form physically or logically included in the processing unit 250.

[0076] The control system 259 is a system that physically or logically includes modules that can embody an improved cognitive function training application control method according to one embodiment of the present invention, and may include a start judgment unit 2591, a training optimization unit 2593, and a training provision unit 2595.

[0077] The start determination unit 2591 can determine whether or not a cognitive function training application has been started. More specifically, the start determination unit 2591 can perform a function of determining whether or not a cognitive function training application has been started by a user's input to the user terminal 110-1, and transmitting the result of the determination to the training optimization unit 2593.

[0078] As an example, when a user executes a cognitive function training application installed in the user terminal 110-1 through various input devices (microphone, touchpad, keyboard, etc.) provided in the user terminal 110-1 and successfully drives the application, the start determination unit 2591 may determine that the cognitive function training application has been started. As another example, when user B executes a cognitive function training application installed in the user terminal 110-1 owned by user A and logs in as user B by inputting user B's account information (ID and password), the start determination unit 2591 may determine that the cognitive function training application has not been started normally. That is, only when the cognitive function training application is normally driven on a terminal owned by the user with the user's identification information, the start determination unit 2591 may determine that the cognitive function training application has been started. The start determination unit 2591 may utilize not only the user's login information but also other information such as the user's fingerprint information to process the above authentication procedure.

[0079] Then, the training optimization unit 2593 can optimize the cognitive function training provided by the cognitive function training application to suit the user based on the result of determining whether the cognitive function training application has been started and the user information of the user terminal 110-1.

[0080] At this time, the training optimization unit 2593 can know whether or not the cognitive function training application has been started by receiving the information from the start determination unit 2591. Furthermore, the user information of the user terminal 110-1 determined by the training optimization unit 2593 may be information previously stored in the user terminal 110-1, or, as another example, may be user information input by the user to the user terminal 110-1 within a certain time from when the training optimization unit 2593 attempts to optimize the cognitive function training application. The training optimization unit 2593 can receive consent for personal information collection from the user in order to acquire the information previously stored in the user terminal 110-1 as user information.

[0081] In one embodiment, the user information of the user terminal 110-1 may be information previously collected by a sensor of the user terminal 110-1. Here, the sensor includes not only a sensor connected in an inseparable manner to the user terminal 110-1 but also all sensors detachable from the user terminal 110-1, and may be at least one of a microphone, a camera, a proximity sensor, an illuminance sensor, a temperature sensor, a humidity sensor, a pressure sensor, a GPS, an acceleration sensor, a gravity sensor, a rotation sensor, a geomagnetic sensor, a distance sensor, a fingerprint recognition sensor, an iris recognition sensor, and a heart rate sensor (a type of optical sensor). In addition, information on a circadian rhythm and a schedule based on a biosignal of the user collected by the sensor of the user terminal 110-1 may also be the user information acquired by the training optimization unit 2593.

[0082] In another embodiment, the user information of the user terminal 110-1 may be information input after the cognitive function training application is first executed. For example, when the cognitive function training application is installed and operated in the user terminal 110-1, the cognitive function training application may collect information on at least one of the user's sleep time, the number of people living with the user, the user's external activity level, and the user's depression level in the form of a questionnaire, and the collected information may be used by the training optimization unit 2593 with the user's consent.

[0083] Here, the user's sleep time and the number of people living with the user may be values ​​selected from integers in a predetermined range, and the user's external activity level may be a value that quantifies the user's subjective feeling, for example, level 5 may be a value selected by a user who does a lot of external activity, and level 1 may be a value selected by a user who is active indoors only by himself.

[0084] The depression level may be a value obtained by quantifying a user's subjective feeling like the external activity level, or may be a value obtained by quantifying a conventionally known Beck depression assessment and a PHQ-9 depression scale, depending on the embodiment. The above-mentioned information on the external activity level and depression level is merely an example, and the present invention is not limited to a specific method.

[0085] In another embodiment, the user information of the user terminal 110-1 may be external information on the day when the cognitive function training application provides the cognitive function training and personal information of the user on that day. Here, as an example of external information on the day when the cognitive function training is provided, information on the weather and temperature on the day when the cognitive function training is performed may be external information on the day.

[0086] In this embodiment, the user's personal information may be information about the current day, and if the user's personal information is in the form of photos, notes, or messages, it may be information collected 1 to 2 weeks before the current day, and if the user's personal information is information about a schedule, it may be information about the schedule 1 to 2 weeks before the current day or 1 to 2 weeks after the current day.

[0087] Additionally, the personal information of the user of user terminal 110-1 may include at least one of messages in the form of SMS, MMS stored in the user's terminal, search terms, conversations on messenger, YouTube, and national medical records.

[0088] The training optimization unit 2593 optimizes the cognitive function training application means adjusting the process of the cognitive function training application as appropriately as possible for a user who logs in through proper procedures and receives cognitive function training through user terminal 110-1. When the cognitive function training application is optimized, not only can cognitive function training be provided to the user more efficiently, but the user can also feel enjoyment while receiving the cognitive function training, thereby improving sustainability.

[0089] Here, adjusting the process of the cognitive function training application means changing within a certain range the form in which the cognitive function training application provides the cognitive function training to the user. For example, when the cognitive function of the user is significantly deteriorated and the speed of the cognitive function training by the cognitive function training application feels too fast, the method according to an embodiment of the present invention can help the user to recover from the cognitive function disorder by receiving the cognitive function training by lowering the speed of the cognitive function training to a certain level. In addition, when the external situation surrounding the user suddenly changes and the user cannot normally perform the cognitive function training even if the cognitive function training is started, according to the present invention, the cognitive function training can be controlled so that the cognitive function training is resumed when the external situation surrounding the user improves even after a certain time has passed after the started cognitive function training is temporarily suspended. In addition, when the user's health condition suddenly deteriorates or the user's fatigue level is excessively high, the sensor activated in the user terminal 110-1 detects the deterioration of the user's health condition or high fatigue level, and the training optimization unit 2593 can suspend the cognitive function training (determine whether to proceed) according to the current state of the user, or appropriately delay the proceeding speed.

[0090] In the present invention, optimization of cognitive function training may mean changing the process of cognitive function training, in which one cycle is repeated, to suit the user. For example, if a cognitive function training process consisting of exactly 10 minutes is started and proceeds for 4 minutes, then is interrupted for 5 minutes due to the need for optimization, and then is resumed and completed, the cognitive function training, which originally took 10 minutes, is recorded as having been completed in 15 minutes, and such an increase in the length of the cycle may be an example of optimization in the present invention.

[0091] As another example, in the present invention, optimization of cognitive function training may mean modifying the cognitive function training process using any visual or auditory material to suit the user. For example, while the cognitive function training process is in progress, images and music that can enhance the user's concentration or attention may be provided to the user through the user terminal 110-1, and the insertion of such images and music is for a specific user only, and therefore may be considered as optimization for the user.

[0092] JPEG0007671083000002.jpg38163 JPEG0007671083000003.jpg52163 Tables 2 and 3 exemplarily show monologues of a particular user. In Tables 2 and 3, the Cogtera application is considered to be an example of a cognitive function training application.

[0093] More specifically, Table 2 shows the results of training optimization unit 2593 extracting images and text from weather, photos stored in user terminal 110-1, notes stored in user terminal 110-1, schedules stored in user terminal 110-1, etc., optimizing cognitive function training based on the extracted images and text, and providing it to the user. This enables the user to effectively train to improve their cognitive function through familiar images and text.

[0094] Table 3 also exemplarily shows that users can effectively train their cognitive functions by listening to fast beat music and using colors and images that can improve their concentration.

[0095] When the cognitive function training application is started or resumed by the user, the training providing unit 2595 can provide the user with optimized cognitive function training through the user terminal 110-1. That is, when the optimized component of only the user determined by the training optimization unit 2593 is reflected in the cognitive function training, the training providing unit 2595 executes the cognitive function training reflecting the optimized component and provides it to the user, and such a function of the training providing unit 2595 can be differentiated from the function of a module that executes the cognitive function training stored in the existing database 210 without modifying it.

[0096] The functions of the control system 259 and the sub-modules belonging to the control system 259 described above will be explained below with reference to FIG.

[0097] The first screen 510 in Fig. 5 is an example of a screen that can be output when a cognitive function training application is executed on the user terminal 110-1. Specifically, the first screen 510 in Fig. 5 requests the user to "memorize words by speaking them out loud," and can output the words that the user should pronounce after a certain period of time has passed.

[0098] The training optimization unit 2593 detects that a sound unrelated to the user's voice is input through the microphone of the user terminal 110-1 beyond a certain volume (certain level), temporarily suspends the cognitive function training, and optimizes the cognitive function training so as to provide visual and auditory guidance information to the user. The second screen 550 of FIG. 5 shows that visual guidance information is provided to the user. When a certain time has elapsed from the temporarily suspended cognitive function training or the user actively clicks the "Continue" button, the cognitive function training can be resumed, and the third screen 590 of FIG. 5 shows that the cognitive function training has been resumed.

[0099] Sounds unrelated to the user's voice can include the sound of pouring water into a cup, noises generated by the sink or toilet bowl in the bathroom, telephone ringtones, voices of people other than the user, television sounds, announcements, sirens, and sounds that are louder than everyday noise.

[0100] As an optional embodiment, even if a sound unrelated to the user's voice is input above a certain volume, if the user's voice is clearly input, the training optimization unit 2593 may not optimize the cognitive function training to prevent a delay in training and ensure user convenience. In this case, the training optimization unit 2593 may additionally request the user's consent to omit the optimization of the cognitive function training.

[0101] FIG. 6 is a diagram illustrating an embodiment in which the absence of a user is detected and cognitive function training is optimized.

[0102] The first screen 610 in Fig. 6 indicates that the cognitive function training application has been normally started by the user. At this time, in a situation where the sensor of the user terminal 110-1 detects that the user is not adjacent to the user terminal 110-1 and the cognitive function training cannot be normally performed, the training optimization unit 2593 outputs the second screen 650 in Fig. 6 to the user terminal 110-1 to temporarily suspend the cognitive function training, and when the user is detected, outputs the third screen 690 in Fig. 6 to allow the cognitive function training to continue.

[0103] 7A and 7B are diagrams that illustrate an example in which cognitive function training is optimized in a situation in which the user's voice is normally input.

[0104] First, FIG. 7A is a schematic diagram showing that when the user's speech collected through the sensor of the user terminal 110-1 is analyzed, if the user's speech is unclear, the user's speech rate is slow, or the user's speech volume is low, the cognitive function training is not immediately performed, but is temporarily delayed to induce the user to resume speaking. In this process, the training optimization unit 2593 optimizes the cognitive function training in real time by considering the collected user input (when the user's input exceeds or does not reach a certain level) after determining that the cognitive function training application has been started, and can occur even if there is no input unrelated to the user as in FIG. 5. The user can visually check the guidance screen 730a of FIG. 7A or check the auditory guidance information output through the user terminal 110-1 and speak again to resume the cognitive function training.

[0105] Next, Fig. 7B is a diagram showing a schematic diagram of calculating the fatigue level of the user and optimizing the cognitive function training based on the calculated fatigue level by the training optimization unit 2593. The situation as shown in Fig. 7B can be effective in the following situation.

[0106] JPEG0007671083000004.jpg45163Table 4 shows a monologue of a 68-year-old female user, and exemplarily illustrates a situation in which a user who uses a cognitive function training application feels high fatigue. The training optimization unit 2593 collects the user's voice volume, speech start timing, speech rate, speech habit, blink count, blink rate, and pupil size through various sensors (microphone, camera, timer, iris recognition sensor, etc.) activated in the user terminal 110-1, calculates the user's fatigue level in real time by considering at least one of them, and optimizes the cognitive function training by interrupting or delaying the cognitive function training process when the calculated fatigue level exceeds a certain level. As an example, if the voice volume is low, the speech start timing is late, the speech rate is slow, or the blink count is significantly reduced, the training optimization unit 2593 can determine that the user's fatigue level is higher than normal.

[0107] FIG. 8 is a diagram illustrating an example of a situation in which cognitive function training is interrupted.

[0108] The third screen 850 of Figure 8 is a screen output through the user terminal 110-1 when it is determined that cognitive function training cannot proceed normally in a situation such as that of Figures 7A and 7B, and the training optimization unit 2593 and the training provision unit 2595 can suspend and resume the cognitive function training application for a certain period of time so that the user can have sufficient rest.

[0109] FIG. 9 is a diagram illustrating an example of outputting a training time range that is most suitable for a user.

[0110] A user can set a training time suitable for the user by executing a cognitive function training application, or can set the cognitive function training application to automatically suggest a training time, as in the training time setting screen 910 of FIG. 9. The training optimization unit 2593 can pattern and analyze the user's daily life collected through the sensor of the user terminal 110-1 when the cognitive function training application is not started, and visually or audibly output a training time range that is most suitable for the user's cognitive function training through the user terminal 110-1 based on the analysis result. The training time recommendation screen 950 of FIG. 9 is a schematic diagram showing an embodiment in which the user terminal 110-1 is activated and suggests training regardless of the user's input when the training time is determined by the training optimization unit 2593. The training optimization unit 2593 can optimize one cycle of cognitive function training by taking into consideration information such as the user's circadian rhythm and schedule as a whole, calculating the most suitable time range for cognitive function training out of 24 hours a day, and including a process of suggesting the calculated time range to the user in the introduction part of the cognitive function training.

[0111] JPEG0007671083000005.jpg58163Table 5 is an example of a user's impressions to explain the training time recommendation process described in FIG. 9. As shown in Table 5, the user is recommended the training time that is most suitable for him / her, and can perform the training at that time to achieve high performance. The recommended training time can be the time when the user is least busy when considering the user's schedule and when the user's circadian rhythm is most stable.

[0112] FIG. 10 is a flowchart illustrating an example of the cognitive function training application control method described with reference to FIGS.

[0113] FIG. 10 can be executed by the control system 259 and the sub-modules of the control system 259 described in FIG. 5, and therefore a description that overlaps with the contents described in FIG. 5 to FIG. 9 will be omitted.

[0114] The start determination unit 2591 can determine whether or not a cognitive function training application has been started by a user's input to the user terminal 110-1 (S1010).

[0115] The training optimization unit 2593 can optimize the cognitive function training provided by the cognitive function training application to suit the user (the user's environment and user's condition) based on the result of determining whether the cognitive function training application has been started and the user information of the user terminal 110-1 (S1030).

[0116] The training providing unit 2595 can provide optimized cognitive function training through the user terminal 110-1 when the cognitive function training application is started or resumed by the user S1050.

[0117] According to the present invention, a training algorithm for dramatically improving the symptoms of cognitive impairment in a patient having the symptoms of cognitive impairment can be provided in various forms.

[0118] The above-described embodiments of the present invention may be implemented in the form of a computer program that can be executed by various components on a computer, and such a computer program may be recorded on a computer-readable medium, which may include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and hardware devices specially configured to store and execute program instructions, such as ROMs, RAMs, and flash memories.

[0119] Meanwhile, the computer program may be one specially designed and constructed for the present invention, or one that is well known and available to those skilled in the art of computer software. Examples of computer programs include not only machine code, such as that produced by a compiler, but also high-level language code that can be executed by a computer using an interpreter, etc.

[0120] The specific implementation described in the present invention is one embodiment and does not limit the scope of the embodiments in any way. For the sake of brevity of the present specification, descriptions of conventional electronic configurations, control systems, software, and other functional aspects of the system may be omitted. Furthermore, the line connections or connecting members between components shown in the drawings are illustrative of functional connections and / or physical or circuit connections, and may be shown as various alternative or additional functional connections, physical connections, or circuit connections in an actual device. Furthermore, unless specifically mentioned as "essential" or "important," a component may not necessarily be required to apply the present invention.

[0121] In the present specification (particularly in the claims), the use of the term "said" and similar indicators can be applied to both the singular and the plural. In addition, when a range is described in the present invention, it is equivalent to describing each individual value constituting the range in the detailed description of the invention, as including the invention to which each individual value belonging to the range is applied (unless otherwise stated). Finally, unless otherwise stated, the steps constituting the method of the present invention are clearly described in order, the steps may be performed in an appropriate order. The present invention is not necessarily limited to the order of the steps described. In the present invention, the use of all examples or exemplary terms (for example, etc.) is merely for the purpose of describing the present invention in detail, and the scope of the present invention is not limited by the examples or exemplary terms unless otherwise limited by the claims. Furthermore, those skilled in the art will understand that various modifications, combinations and changes can be made according to design conditions and factors within the scope of the appended claims or their equivalents.

Claims

1. A control method for a control system including a start determination unit, a training optimization unit, and a training provision unit, comprising: a step of the start determination unit determining whether or not a cognitive function training application has been started by a user's input to a terminal; The training optimization unit optimizes the cognitive function training provided by the cognitive function training application for the user based on a result of determining whether the cognitive function training application has been started and user information of the terminal; The training providing unit provides the optimized cognitive function training through the terminal when the cognitive function training application is started or resumed by the user's input; The optimizing step includes: An improved cognitive function training application control method comprising the steps of calculating a fatigue level of the user based on an input from the user, and adjusting a progress speed of the optimized cognitive function training based on the calculated fatigue level.

2. The user information is The improved cognitive function training application control method according to claim 1 , wherein the information is collected in advance by a sensor of the terminal.

3. The user information is 2. The improved cognitive function training application control method according to claim 1, wherein the information is information regarding a circadian rhythm and a schedule based on the user's biological signals collected by a sensor of the terminal.

4. The user information is The improved cognitive function training application control method of claim 1, wherein at least one of the user's sleep time, the number of people living with the user, the external activity level, and the depression level is input since the cognitive function training application is first executed.

5. The optimizing step includes:

2. The improved cognitive function training application control method according to claim 1, further comprising visually or audibly outputting the range of training times during the day that is most suitable for the user.

6. The user information is The improved cognitive function training application control method according to claim 1 , wherein the cognitive function training application provides external information for the day on which the cognitive function training application provides cognitive function training and personal information of the user for the day.

7. The optimizing step includes: The improved cognitive training application control method of claim 1 , further comprising optimizing cognitive training in real time taking into account collected user input after it is determined that the cognitive training application has been initiated.

8. The optimizing step includes: The improved cognitive function training application control method according to claim 7 , further comprising the steps of: suspending the cognitive function training for a certain period of time or changing the training speed of the cognitive function training when the user's input exceeds a certain level.

9. The optimizing step includes: The improved cognitive function training application control method according to claim 7 , further comprising the steps of: suspending cognitive function training for a certain period of time or changing a training speed of the cognitive function training if the user's input is below a certain level.

10. The optimizing step includes:

8. The improved cognitive function training application control method of claim 7, further comprising collecting inputs unrelated to the user other than the user input, and interrupting the cognitive function training when the collected inputs exceed a certain level.

11. The step of providing the optimized cognitive function training through the terminal includes:

11. The improved cognitive training application control method of claim 10, further comprising suspending cognitive training until the collected input falls below a certain level.

12. The step of providing the optimized cognitive function training through the terminal includes: The improved cognitive function training application control method according to claim 1 , further comprising: outputting at least one of visual guidance information and audio guidance information through the terminal when the user's input satisfies a preset condition.

13. The optimizing step includes: The improved cognitive function training application control method according to claim 1 , further comprising: calculating a fatigue level of the user based on the user's input; and determining whether or not to proceed with the optimized cognitive function training based on the calculated fatigue level.

14. A computer-readable recording medium storing a program for executing the method according to claim 1 through a computer.

15. a start determination unit that determines whether or not a cognitive function training application has been started by a user's input to the terminal; A training optimization unit that optimizes the cognitive function training provided by the cognitive function training application according to the user based on a result of determining whether the cognitive function training application has been started and user information of the terminal; a training providing unit that provides the optimized cognitive function training through the terminal when the cognitive function training application is started or resumed by the user's input; The training optimization unit includes: An improved cognitive function training application control device that calculates a fatigue level of the user based on the user's input and adjusts a progress rate of the optimized cognitive function training based on the calculated fatigue level.

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