A cognitive model-based cognitive status assessment system that uses a user-customized cognitive model based on learning to perform cognitive testing tasks on behalf of the user

Abstract

A cognitive state assessment system is provided which extracts game data from input information on a user terminal relating to a cognitive game provided over a short period of time, constructs a user-customized cognitive model based on learning for cognitive state diagnosis, and processes the tasks required for diagnosing the cognitive state based on the user-customized cognitive model so as to be automatically performed in the user-customized cognitive model, thereby dramatically reducing the time and fatigue required for diagnosing the cognitive state and enabling various diagnoses and assessments to be performed. [Solution] A method for operating a cognitive state assessment device, comprising: a step of extracting first game data for cognitive assessment from reaction input information regarding a user's cognitive game application; a customized task performance model construction step of applying the extracted first game data to a user customized cognitive model based on artificial intelligence learning in which a cognitive model based on a cognitive architecture is pre-linked and learned corresponding to game data for each cognitive task, to generate a customized cognitive task performance model corresponding to the user; and a cognitive ability assessment step of using the customized cognitive task performance model to obtain alternative performance results of a cognitive task selected for each cognitive assessment item, and evaluating the user's cognitive ability for each cognitive evaluation item based on the alternative performance results.

Description

[Technical Field]

[0001] The present invention relates to a cognitive state assessment device and a method of operation thereof, and more particularly to a cognitive model-based cognitive state assessment system that uses a learning-based, user-customized cognitive model to perform cognitive testing tasks on behalf of the user. [Background technology]

[0002] Providing parents with information about their children can improve problem solving, provide confidence in parental decisions, and enable them to be more responsive to the needs of their children as they grow, as parents' knowledge of their cognitive developmental status enhances their ability to respond appropriately to their children.

[0003] For this reason, parents often visit specialized diagnostic institutions together with their children to understand their child's developmental status, where the child undergoes medical examinations, standardized tests (e.g., Social Maturity Assessment Test, KEDI-WISC, Portage Cognitive Development Test, etc.), informal tests, observations, questionnaires, and interviews.

[0004] Furthermore, even if an elderly person is suffering from dementia or is suspected of having depression, they will visit such specialized diagnostic institutions and undergo various cognitive tests.

[0005] However, conventional diagnostic methods require numerous interviews and tasks, taking at least two hours. This can lead to problems such as subjects, such as children or the elderly, refusing to be diagnosed or becoming too tired to complete the interviews and tasks properly. Summary of the Invention [Problem to be solved by the invention]

[0006] The present invention has been devised to solve the above-mentioned problems, and has an object to provide a cognitive state assessment system that extracts game data from input information on a user's terminal regarding a cognitive game provided in a short period of time, constructs a user-customized cognitive model based on learning for cognitive state diagnosis, and processes tasks necessary for cognitive state diagnosis based on the user-customized cognitive model so that they are automatically performed in the user-customized cognitive model, thereby dramatically reducing the time and fatigue required for cognitive state diagnosis and enabling various diagnoses and assessments. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems, an apparatus according to an embodiment of the present invention includes a cognitive state assessment device, which comprises a game data processing unit that extracts first game data for cognitive assessment from reaction input information related to a user's cognitive game application, a customized task performance model construction unit that applies the extracted first game data to a user-customized cognitive model based on artificial intelligence learning in which a cognitive model based on a cognitive architecture is pre-linked and learned corresponding to game data for each cognitive task, thereby generating a customized cognitive task performance model corresponding to the user, and a cognitive ability assessment unit that uses the customized cognitive task performance model to obtain alternative performance results for cognitive tasks selected for each cognitive assessment item, and evaluates the user's cognitive ability for each cognitive assessment item based on the alternative performance results.

[0008] Furthermore, a method according to an embodiment of the present invention for solving the above-described problems includes, in an operating method of a cognitive state assessment device, a step of extracting first game data for cognitive assessment from reaction input information related to a user's cognitive game application, a customized task performance model construction step of applying the extracted first game data to a user-customized cognitive model based on artificial intelligence learning in which a cognitive model based on a cognitive architecture is pre-linked and learned corresponding to game data for each cognitive task, to generate a customized cognitive task performance model corresponding to the user, and a cognitive ability assessment step of using the customized cognitive task performance model to obtain alternative performance results of a cognitive task selected for each cognitive assessment item, and evaluating the user's cognitive ability for each cognitive assessment item based on the alternative performance results.

[0009] Furthermore, the method according to the embodiment of the present invention for solving the above problems can be realized by a computer-readable recording medium and a computer program for executing the method on a computer. [Effects of the Invention]

[0010] According to an embodiment of the present invention, a cognitive state assessment device and an operating method thereof can be provided that extract game data from input information on a user's terminal regarding a cognitive game provided over a short period of time, construct a user-customized cognitive model based on learning for cognitive state diagnosis, and process the tasks required for cognitive state diagnosis so that they are automatically performed in the user-customized cognitive model based on the user-customized cognitive model, thereby dramatically reducing the time and fatigue required for cognitive state diagnosis and enabling various diagnoses and assessments.

[0011] As a result, according to an embodiment of the present invention, personalized diagnosis and evaluation using cognitive modeling can be performed, which can be used in education, medical care, etc., and various interview tests such as ADHD tests, which previously took about two hours, can be conducted in a casual format based on a simple and short game.

[0012] In addition, according to the embodiment of the present invention, it is possible to perform self-diagnosis of cognitive status, thereby enabling the monitoring of cognitive health status and the prompt identification of the cause of illness, as well as the effect of promoting cognitive health that leads to treatment. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a conceptual diagram showing an outline of the entire system of the present invention. [Figure 2] FIG. 2 is a block diagram illustrating in more detail the cognitive state assessment device according to the embodiment of the present invention. [Figure 3] FIG. 1 is a diagram illustrating variable modeling data for constructing a cognitive architecture according to an embodiment of the present invention. [Figure 4] FIG. 10 is a diagram illustrating the operation of each game application for calculating a task model variable according to an embodiment of the present invention. [Figure 5] 1 is a ladder diagram for specifically explaining the overall system operation of the present invention. [Figure 6-7] 10A and 10B are diagrams for illustrating an example of a report interface output from a parent terminal according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0014] The following merely illustrates the principles of the present invention. Therefore, those skilled in the art will be able to devise various devices and methods that embody the principles of the present invention and are within the concept and scope of the present invention, even though not explicitly described or shown herein. It should be understood that all conditional terms and embodiments listed herein are, in principle, expressly intended only for the purpose of helping the concept of the present invention to be understood, and are not limiting to the embodiments and conditions specifically listed in this specification.

[0015] Moreover, all detailed descriptions reciting specific embodiments, as well as principles, aspects, and embodiments of the present invention, should be understood to be intended to encompass structural and functional equivalents of such items, including not only currently known equivalents but also equivalents developed in the future, i.e., any elements invented to perform the same function, regardless of structure.

[0016] Thus, for example, the block diagrams herein should be understood to represent conceptual views of illustrative circuitry embodying the principles of the invention. Similarly, all flowcharts, state transition diagrams, pseudocode, and the like, may be substantially represented on a computer-readable medium and should be understood to represent various processes performed by a computer or processor, whether or not a computer or processor is explicitly shown.

[0017] The functions of the various elements illustrated in the figures, including functional blocks represented by processors or similar concepts, may be provided through the use of dedicated hardware as well as hardware capable of running software in association with appropriate software. When provided by a processor, the functions may be provided by a single dedicated processor, a single shared processor, or a plurality of individual processors, some of which may be shared.

[0018] Additionally, the explicit use of terms such as processor, control, or similar concepts should not be construed as exclusively referring to hardware capable of executing software, but should be understood to implicitly include, without limitation, digital signal processor (DSP) hardware, read-only memory (ROM), random access memory (RAM), and non-volatile memory for storing software. Other commonly known and commonly used hardware may also be included.

[0019] In the claims herein, elements expressed as means for performing a function recited in the detailed description are intended to include any method for performing that function, including, for example, a combination of circuit elements that perform that function, or software in any form, including firmware / microcode, etc., combined with appropriate circuitry for invoking the software to perform that function. The invention defined by such claims is such that the functionality provided by the various recited means is combined and combined in the manner required by the claims, and any means capable of providing that functionality should be understood to be equivalent to what is grasped from this specification.

[0020] The above-mentioned objects, features, and advantages will become more apparent from the following detailed description taken in conjunction with the accompanying drawings, which will enable those skilled in the art to easily implement the technical concept of the present invention. In describing the present invention, if it is recognized that a detailed description of known technologies related to the present invention may obscure the gist of the present invention, such detailed description will be omitted.

[0021] A preferred embodiment of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] FIG. 1 is a conceptual diagram showing an outline of the entire system according to an embodiment of the present invention.

[0023] The overall system according to one embodiment of the present invention comprises a cognitive state assessment device 100, a user terminal 200, a parent terminal 400, and a learning-based user-customized cognitive model 300.

[0024] The cognitive state assessment device 100 can be connected to each user terminal 200, parent terminal 400, and learning-based user-customized cognitive model 300 via a wired / wireless network to provide a cognitive state diagnosis and assessment service according to an embodiment of the present invention, and can communicate with each other.

[0025] Here, each of the networks can be realized by any type of wired / wireless network, such as a local area network (LAN), a wide area network (WAN), a value added network (VAN), a personal area network (PAN), a mobile radio communication network, or a satellite communication network.

[0026] The user terminal 200 and the parent terminal 400 may be any one of individual devices such as a personal computer, a mobile phone, a smart phone, a smart pad, a laptop computer, a personal digital assistant (PDA), and a portable media player (PMP), or may be a multi-device including at least one of shared devices such as a kiosk or a stationary display device installed in a specific location.

[0027] First, the user terminal 200 may be a terminal device of a subject of cognitive assessment, which is a terminal registered in advance in the cognitive state assessment device 100 together with the guardian terminal 400. The user terminal 200 may output a cognitive game provided by the cognitive state assessment device 100 according to the cognitive assessment items, and may receive user response data corresponding to the cognitive game and transfer it to the cognitive state assessment device 100.

[0028] In such a system configuration, the cognitive state assessment device 100 can preliminarily construct a learning-based user-customized cognitive model 300. The cognitive state assessment device 100 can construct the learning-based user-customized cognitive model 300 by comparing and learning cognitive game data extracted from user response data corresponding to a cognitive game with past cognitive state data diagnosed for the subject. For learning, various deep learning methods such as a convolutional neural network (CNN), a deep neural network (DNN), a recurrent neural network (RNN), and a long short-term memory (LSTM) can be used, and analysis methods such as regression analysis and statistical relational analysis methods can also be used.

[0029] More specifically, the cognitive state assessment device 100 can pre-construct a user-customized cognitive model based on artificial intelligence learning, in which a cognitive model based on a cognitive architecture is pre-linked and pre-trained to correspond to game data for each cognitive task.

[0030] Here, the cognitive model based on such a cognitive architecture may include a cognitive model based on the well-known ACT-R (Adaptive Control of Thought Rational) architecture, and the cognitive assessment items may include Attention-Deficit / Hyperactivity Disorder (ADHD) assessment items corresponding to the ACT-R model, thereby enabling evaluation of cognitive items corresponding to ADHD based on game data.

[0031] To this end, the cognitive state assessment device 100 first extracts first game data for cognitive assessment from the user's reaction input information regarding a cognitive game application, applies the extracted first game data to the learning-based user-customized cognitive model 300 to generate a customized cognitive task performance model corresponding to the user, uses the customized cognitive task performance model to obtain alternative performance results of the cognitive task selected for each cognitive assessment item, and evaluates the user's cognitive ability for each cognitive assessment item based on the alternative performance results.

[0032] Here, the task performance model is an automatic task performance model generated by predicting the user's cognitive state from game data input using a learning-based user-customized cognitive model 300, and may be a model that automatically performs a series of various interviews and tasks that previously took about two hours to diagnose cognitive conditions such as ADHD without any additional user input.

[0033] That is, the task performance model is a model that outputs result data predicted when a task for cognitive assessment is performed by a user-customized cognitive model constructed using the game data, and this can be predicted based on a preset evaluation standard for each task. For example, if the reaction speed variable of the user-customized cognitive model is 0.5, the task performance model can output, as the alternative performance result, a result predicted when a cognitive assessment task is performed in a state where the reaction speed variable is 0.5.

[0034] Therefore, the cognitive game application according to an embodiment of the present invention can be configured to collect response variables for generating such a task performance model. The cognitive state assessment device 100 can extract such response variables from game data by type, and thus can provide the user terminal 200 with a cognitive game application that is configured in stages in advance.

[0035] Such cognitive game applications may include cognitive games that can be completed in a short period of time and may include cognitive games in which various tasks are performed sequentially or simultaneously in parallel to extract cognitive variables that can be used to diagnose and assess cognitive conditions.

[0036] Meanwhile, the cognitive game application configured in this manner can be output from the user terminal 200, and the subject inputs user reaction inputs for playing the game into the user terminal 200. The user terminal 200 can process the input user reaction input information and transfer it to the cognitive state assessment device 100.

[0037] The cognitive state assessment device 100 then uses the cognitive game data extracted from the user response input information and applies it to the learning-based user-customized cognitive model 300, thereby generating a user-customized cognitive model and generating a customized task performance model corresponding to the user-customized cognitive model.

[0038] As a result, the cognitive state assessment device 100 can obtain diagnostic result data of the cognitive state of each user by alternatively driving the customized task performance model by digitizing existing tasks that were configured for humans to evaluate their own cognitive state and inputting them into the customized task performance model, and appropriate diagnostic and assessment information based on the obtained result data can be quickly processed and provided to the user terminal 200, parent terminal 400, or a separate institution.

[0039] FIG. 2 is a block diagram for more specifically explaining the cognitive state assessment device according to the embodiment of the present invention.

[0040] The cognitive state assessment device 100 according to an embodiment of the present invention may include a cognitive model generation unit 110, a cognitive ability assessment unit 120, and a customized task performance model construction unit 130, and the learning-based user-customized cognitive model 300 may be connected to the cognitive state assessment device 100, or may be included in the cognitive state assessment device 100, or may be pre-constructed on an external server or the like.

[0041] First, the cognitive model generation unit 110 includes a cognitive architecture construction unit 111 , a game data processing unit 112 , a user terminal input information processing unit 113 , and a cognitive model learning modeling unit 114 .

[0042] First, the cognitive architecture configuration unit 111 stores and manages architecture data of pre-constructed cognitive variables in order to extract variables for evaluating and diagnosing cognitive states from game data of a game application.

[0043] Then, the user's input information input to the user terminal input information processing unit 113 is processed as a cognitive variable in the game data processing unit 112 and is provided to the cognitive model learning modeling unit 114 .

[0044] Then, the cognitive model learning modeling unit 114 inputs the cognitive variables of the game data processing unit into the learning-based user-customized cognitive model 300 to construct a customized task performance model.

[0045] More specifically, for example, the cognitive architecture construction unit can construct a cognitive model architecture based on conditional-action statements configured to match preset modules and buffers using a cognitive model based on the well-known ACT-R (Adaptive Control of Thought Rational) architecture in order to logically construct human cognitive / behavioral processes, and the game data processing unit 112 can perform processing to map each conditional-action statement of the cognitive model architecture to preset game data.

[0046] The cognitive model learning modeling unit extracts cognitive model variables related to working memory, attention, cognitive flexibility, inhibition, processing speed, etc., obtained from the result data of the user playing N games from the architecture mapping data of the game data processing unit 112 and the input information of the user terminal input information processing unit 113, and applies the extracted cognitive model variables to the learning-based user-customized cognitive model 300 to construct a user-customized personalized cognitive model.

[0047] The customized task performance model construction unit 130 can then use such a personalized cognitive model to construct a task-customized cognitive task performance model that can perform the cognitive task selected for each cognitive assessment item instead.

[0048] For this purpose, the customized task performance model configuration unit 130 configures the basic task performance model architecture based on the above-mentioned ACT-R, but applies variables for each personalized cognitive model, and when a task is input, it can generate a virtual task performance model configured to repeatedly measure each user's performance time, error rate, mission success rate, correct answer rate, consecutive success rate, etc.

[0049] The customized task execution model construction unit 130 individually generates such a task execution model and can further receive game data (N+1) and subsequent data that was not used in the modeling from the user terminal 200 to verify its accuracy.

[0050] Such N+1th and subsequent game data may be passed to the accuracy verification unit 127 of the cognitive ability assessment unit 120. The accuracy verification unit 127 may compare and detect errors in model prediction information based on comparative evaluation of execution time, error rate, latency, etc., and if the error is equal to or greater than a threshold, may decide to execute an additional game and provide a notification to the user terminal 200. Through such model self-learning, the customized task execution model construction unit 130 may more accurately generate a user-replicated cognitive model for automatically executing a customized task on behalf of the user.

[0051] The cognitive ability assessment unit 120 includes a cognitive model-based task substitution performance unit 121 that uses a customized task performance model to automatically perform a task based on the cognitive model.

[0052] Here, the tasks may include diagnostic or interview tasks that can be substituted and configured according to each diagnostic purpose or subject, and the cognitive state assessment device 100 may further be provided with a task selection unit 122 that selects and configures tasks based on each purpose, such as assessing ADHD status, or on user classification.

[0053] The cognitive state assessment device 100 is equipped with a result data processing unit that processes the result data, and the result data may be provided to the parent or user terminal 200 via a cloud connection unit, or output onto the screen of the parent terminal 400 via an interface output unit 125, or provided to a cognitive enhancement track recommendation unit 126, and processed so that a cognitive enhancement process corresponding to the cognitive state diagnosis result is provided to the parent terminal 400 and output.

[0054] More specifically, the cognitive ability assessment unit 120 uses the cognitive model-based task substitution performance unit 121 to perform various tasks that the user should actually perform based on the substitution performance of the customized task performance model, and can perform various tasks M or more times based on the user's customized learned and replicated performance abilities (how many missions are performed, how many errors occur, what targets are frequently missed, etc.).

[0055] The result data processing unit 124 may perform quantification based on a pre-set criterion or a pre-defined algorithm to construct the performance result data.

[0056] The interface output unit 125 may then configure an analysis result interface using the quantified performance result data, and report data including the configured analysis result interface may be provided to the parent terminal 400 .

[0057] As a result, the parent terminal 400 can provide the user's cognitive state assessment information through various types of interfaces. For example, the analysis result interface may be reported in the form of a pentagonal spider map, or additional analyzed information may be output as qualitative data.

[0058] Furthermore, the result data processing unit 124 can predict data for the next two weeks using statistical analysis based on the information collected so far, and provide the predicted data to the user terminal 200. For this purpose, the result data processing unit 124 can perform analysis processing to calculate a growth regression equation using a cognitive model and learning, and generate predicted data for the next two weeks.

[0059] In addition, when a predetermined cognitive status item is below a threshold, the cognitive enhancement track recommendation unit 126 can perform a recommendation process in which it configures an enhancement track consisting of enhancement tasks that can enhance the ability of the item that is below the threshold as a recommended track, and provides the configured recommended track to the parent terminal 400 or the user terminal 200.

[0060] Here, the recommended track information may be provided to the user terminal 200 or the parent terminal 400, and may include one or more game information stages. Here, each recommended game may include a task for comprehensively improving cognitive ability, and in particular, may include a task for more intensively strengthening an item that is predicted to be lacking and is below the threshold.

[0061] For this series of processes, all RAW data (unprocessed data) may be primarily stored in the user terminal 200, then processed and provided to the cognitive state assessment device 100, and the compiled data may be stored in a cloud server via the cloud connection unit 123, and the final compiled data may be provided to the user terminal 200 or the parent terminal 400.

[0062] By building such a system, personalized diagnosis / assessment using cognitive modeling can be carried out quickly and easily, which can be used in education, medical care (treatment), etc. In particular, it can make testing for children with ADHD, which currently takes nearly two hours, more casual and quicker.

[0063] In addition, currently, 90% of children with potential ADHD in Korea do not visit a medical institution for treatment. However, by using this cognitive status assessment device 100, it becomes easier for them to seek treatment after a simple self-diagnosis, which has the advantage that it can be used not only for diagnosing children but also for diagnosing general cognitive disorders such as autism, depression, and dementia.

[0064] FIG. 3 is a diagram illustrating variable modeling data for constructing a cognitive architecture according to an embodiment of the present invention.

[0065] Referring to FIG. 3, the cognitive model learning modeling unit 114 includes a task variable modeling unit 1141, a cognitive model variable modeling unit 1143, a feature variable modeling unit 1145, and a scoring variable modeling unit 1147, which perform each task based on a cognitive learning model.

[0066] The task variable modeling unit 1141 can perform a process of modeling the user input results for each task extracted from each game data as model variables for performing cognitive tasks to evaluate cognitive ability.

[0067] The cognitive model variable modeling unit 1143 can then perform modeling to set learning variables acquired based on the cognitive architecture in order to configure a cognitive model.

[0068] The ACT-R model is an example of a cognitive architecture. In ACT-R, eight modules are configured to handle various functions of the human brain, and each module and the production system, which acts as a central processing unit, are configured to exchange information, i.e., chunks, related to cognitive processes through a buffer. Although the buffer can store and process only one chunk at a time, each module can simultaneously search and store multiple pieces of information, and the production system can be configured to simultaneously compare and process tasks that comply with multiple production rules in parallel.

[0069] Therefore, the cognitive model variable modeling unit 1143 can convert the buffers and system structures preset by such cognitive architecture into data and select and adjust learning variables for constructing a personalized cognitive model.

[0070] The feature variable modeling unit 1145 can perform modeling to extract feature variables useful for alternatively performing tasks based on game data from the variables modeled in the cognitive model variable modeling unit 1143. Here, the feature information may be variables extracted using a well-known support vector machine (SVM) method, and examples of the primary feature information include an activation function for learning, a base level activation value, cognitive accuracy, and cognitive delay time, while examples of the secondary feature information include the minimum value, maximum value, average, standard deviation, and variance of the primary feature information.

[0071] In addition, the scoring variable modeling unit 1147 can model algorithms and scoring variables that can calculate cognitive screening and cognitive assessment scores corresponding to an individual, which may be processed by adjusting variables corresponding to evaluation functions for one or more cognitive assessment items that are calculated using previously set task variables, cognitive model variables, and feature variables.

[0072] FIG. 4 is a diagram illustrating the operation of each game application for calculating task model variables according to an embodiment of the present invention.

[0073] 4, task model variables calculated from game data according to an embodiment of the present invention can be broadly categorized as a working memory variable model, an inhibitory variable model, a divided attention variable model, a flexibility variable model, and a processing speed variable model. However, these are merely examples, and it goes without saying that additional variable models may be included.

[0074] First, the working memory capacity variable model represents the ability to memorize information received from other sensory organs and retrieve the information within a certain short period of time. A game application based on this model displays a series of numbers in sequence, and the user can input the displayed series of numbers in reverse order. Furthermore, correct answer scores, time required to answer correctly, etc. can be used as model variables, and as a result, they can be reflected in a customized cognitive assessment task performance model as working memory capacity variables.

[0075] The inhibitory force variable model indicates selective / concentrated activity and state abilities, such as clearly perceiving or responding to only specific stimuli from numerous stimuli from the external environment or from within the individual. Examples of game applications based on this include the well-known Stroop test. The Stroop test displays words or objects in different shades, and asks the user to select only specific shades or objects, thereby assessing selective / concentrated activity abilities. The user can input response data to select an object corresponding to the test query. Furthermore, model variables can include matching stimulus information, incongruent stimulus information, and overall stimulus information, which can be used as inhibitory force variables and can be reflected in a customized cognitive assessment task performance model.

[0076] The divided attention variable model indicates the ability to respond to various demands in the surrounding environment while simultaneously responding to two different types of stimuli, and indicates whether two tasks can be performed simultaneously. The game application displays sequential numbers with different colors, and a user can select sequential numbers with different colors and input them as response data. Correct answer scores and time required to answer correctly can be used as model variables, and as a result, they can be reflected in a customized cognitive assessment task performance model as divided attention variables.

[0077] The flexibility variable model indicates the mental ability to appropriately adapt thinking and behavior in response to changes in the external environment and rules, and the ability to adapt thinking to meet required changes. The game application is an application for selecting cards suitable for card sorting criteria, and the user can select an appropriate card according to the criteria and input it as response data. The model variables can include correct answer scores, consecutive correct answer scores, and time required to answer correctly, which can be reflected as flexibility variables in a customized cognitive assessment task performance model.

[0078] The processing speed variable model also indicates the time it takes to respond to a stimulus and the speed at which the cognitive information can be understood and responded, whether it is visual, auditory, or motor. The game application is a prompt-based figure or object selection application, allowing the user to select different shapes or the presented shape and input it as response data. The model variables can include correct answer scores and the time required to correctly answer, which can then be reflected in the customized cognitive assessment task performance model as processing speed variables.

[0079] FIG. 5 is a ladder diagram for specifically explaining the overall system operation of the present invention.

[0080] Referring to FIG. 5, the cognitive state assessment device 100 according to the embodiment of the present invention first constructs cognitive architecture data and an initial cognitive model based on tasks for each cognitive assessment item (S1001).

[0081] Then, the cognitive state assessment device 100 registers the user information of the user terminal 200 and the guardian terminal 400 (S1003). Here, the user information includes terminal identification information, user account information, telephone number information, and family relationship information.

[0082] Thereafter, the user terminal 200 receives cognitive assessment item information from the cognitive state assessment device 100 (S1004), and plays one or more games corresponding to cognitive diagnostic tasks set in advance for each cognitive assessment item (S1005).

[0083] Then, the user terminal 200 configures model variables based on the user input data (S1007), and the configured game data and model variable information are delivered to the cognitive state assessment device 100 (S1009). Here, step S1007 can also be performed in the cognitive state assessment device 100.

[0084] After this, the cognitive state assessment device 100 performs personalized cognitive model modeling based on learning (S1011), constructs a customized task performance model using the personalized cognitive model (S1013), and uses the customized task performance model to obtain alternative performance results for the selected task for each cognitive assessment item (S1015).

[0085] Then, the cognitive state assessment device 100 uses the substitute performance result data to construct an analysis result interface for each cognitive assessment item (S1017), and provides the analysis result interface for each cognitive assessment item to the parent terminal 400 (S1019).

[0086] Thereafter, the parent terminal 400 can output an analysis result report (S1021), and the cognitive state assessment device 100 can provide the parent terminal 400 with cognitive enhancement track recommendation information based on the analysis result (S1023).

[0087] 6 and 7 are diagrams for exemplifying report interfaces output from a parent terminal according to an embodiment of the present invention.

[0088] First, referring to FIG. 6, the analysis result interface can output a numerical value of the cognitive state based on the user's result data, and additional information such as a reinforcement game to supplement missing elements and information on nearby hospitals can be output.

[0089] 7, the evaluation interface can process and output the user's result data into a pentagonal graph based on the reference variable, and can track and predict changes over a certain period (two weeks) and output them. In addition, the user can check the values ​​that have changed through the reinforcement game, providing a function that allows the user to easily monitor and supplement their cognitive status.

[0090] The above-described method according to the present invention can be created as a program to be executed on a computer and stored on a computer-readable recording medium. Examples of computer-readable recording media include read-only memory (ROM), random access memory (RAM), compact disc (CD) read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device.

[0091] The computer-readable recording medium can be distributed among computer systems connected via a network, and the computer-readable code can be stored and executed in a distributed manner. Functional programs, codes, and code segments for implementing the method can be easily construed by programmers skilled in the art to which the present invention pertains.

[0092] Furthermore, although preferred embodiments of the present invention have been illustrated and described above, the present invention is not limited to the specific embodiments described above, and it goes without saying that various modifications can be made by a person having ordinary knowledge in the technical field to which the invention pertains without departing from the gist of the present invention as claimed in the claims, and these modified embodiments should not be understood individually from the technical ideas and perspectives of the present invention.

Claims

1. A method of operating a cognitive state assessment device, comprising: deriving first game data for cognitive assessment from reaction input information related to a user's cognitive game application; a customized task execution model construction step of applying the extracted first game data to a user-customized cognitive model based on artificial intelligence learning, in which a cognitive model based on a cognitive architecture is pre-associated and learned in correspondence with game data for each cognitive task, to generate a customized cognitive task execution model corresponding to the user; a cognitive ability evaluation step of acquiring alternative performance results of the cognitive task selected for each cognitive evaluation item using the customized cognitive task performance model, and evaluating the user's cognitive ability for each cognitive evaluation item based on the alternative performance results; A method of operating a cognitive state assessment device, comprising:

2. The customized cognitive task performance model comprises:

2. The method of claim 1, further comprising: a virtual task performance model that predicts at least one of the user's performance time, error rate, and correct answer rate corresponding to the selected cognitive task, and outputs the alternative performance result.

3. The cognitive model based on the cognitive architecture includes a cognitive model based on an Adaptive Control of Thought-Rational (ACT-R) architecture; 2. The method of claim 1, wherein the cognitive assessment items include an Attention-Deficit / Hyperactivity Disorder (ADHD) assessment item corresponding to the ACT-R model.

4. 2. The method for operating a cognitive state assessment device according to claim 1, further comprising an accuracy verification step of receiving additional game data different from the first game data from the user terminal of the user and verifying the accuracy of the customized cognitive task performance model.

5. The cognitive ability assessment step includes:

2. The method for operating the cognitive status assessment device according to claim 1, further comprising a result data processing step of constructing result data from the cognitive ability assessment using an analysis interface and outputting the result data to a parent terminal pre-registered in correspondence with the user.

6. The cognitive ability assessment step includes:

2. The method for operating a cognitive state assessment device according to claim 1, further comprising a cognitive enhancement track recommendation step of recommending enhancement tasks corresponding to cognitive ability items assessed to be below a predetermined threshold based on result data from the cognitive ability assessment.

7. In the cognitive state assessment device, a game data processing unit that extracts first game data for cognitive evaluation from reaction input information related to the user's cognitive game application; a customized task execution model construction unit that applies the extracted first game data to a user customized cognitive model based on artificial intelligence learning, in which a cognitive model based on a cognitive architecture is pre-trained in association with game data for each cognitive task, to generate a customized cognitive task execution model corresponding to the user; a cognitive ability assessment unit that acquires alternative performance results of the cognitive task selected for each cognitive evaluation item using the customized cognitive task performance model, and assesses the user's cognitive ability for each cognitive evaluation item based on the alternative performance results; A cognitive state assessment device comprising:

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