JP2016502422A - Cognitive assessment treatment platform using distributed tangible graphical user interface devices - Google Patents

Abstract

A cognitive impairment diagnostic treatment system that uses a cognitive cube, game play associated with the cognitive cube, and a base device that collects data as a statistical analysis. The base device can be a computer and communicates the collected data to the web server host according to a unique ID associated with a particular cognitive cube and further associated with a particular player. Statistical data collected using game play can be used to more reliably diagnose and treat various cognitive impairments with greater confidence. [Selection] Figure 13

Description

  The present invention includes attention deficit and / or comorbidity assessment, attention deficit hyperactivity disorder, and / or treatment of medical conditions with reduced attention such as autism spectrum disorder (ASD), anxiety, depression, and epilepsy. It relates to the field of cognitive impairment.

  This application claims the benefit of US Provisional Application 61 / 549,698, filed October 20, 2011, and US Provisional Application 61 / 551,384, filed October 25, 2011. . These US provisional applications are hereby incorporated by reference in their entirety.

The entire contents of the following cited documents form part of this application.
ADHD / Caution:
1. US Pat. No. 5,913,310, June 19992. US Pat. No. 5,940,801, August 17, 1999 US Pat. No. 5,377,100, Dec. 27, 1994 US Pat. No. 5,913,310, June 22, 1999 5. US Pat. No. 6,053,739 US Patent Application Publication No. 2008/0021351. US Patent Application Publication No. 2010/0279258 US Pat. No. 7,720,610 autism:
9. US Pat. No. 6,398,222 Shifteo®:
1. US Patent Application Publication No. 2011/00979962. US Patent Application Publication No. 2012/0169748 US Design Patent No. 635190

Attention deficit, comorbidity assessment and treatment, and / or treatment of other medical conditions with attention deficit have been fundamentally challenging tasks for parents, teachers, and health care providers. For example, there is no specific test for diagnosing attention deficit. There is also no help to distinguish ADHD from medical conditions with attention deficits similar to the symptoms of this disorder. This represents a difficult situation for educators and health care providers. Thus, the following medical conditions may be comorbid with ADHD or may appear with attention deficits that are distinct from this disorder.
・ Learning or language problems ・ Autism spectrum disorder (ASD)
・ Anxiety disorders ・ Mood disorders ・ Mental disorders ・ Paroxysmal disorders ・ Traumatic brain damage ・ Frontal lobe lesions ・ Visual or hearing problems ・ Sleep disorders ・ Dementia ・ Substance use disorders

  Collecting as much information about an individual as possible from different sources is currently the best way to diagnose and treat an individual's symptoms. For example, current diagnostic aids used in the assessment of ADHD are subjective, expensive and very time consuming and provide little information about the accompanying movement in response to a stimulus. These diagnostic aids make it difficult to identify ADHD, comorbidities and / or other attention related diagnoses.

  Consider a general diagnostic aid for ADHD that is being reviewed by health care providers to help make a clinical diagnosis. Tests such as the Connor's rating scale require subjective responses from parents and teachers, making coordination difficult. Computerized Connor's Continuous Work Test (CPT) provides objective data on inattentional and impulsive response patterns. However, this test does not provide data on accompanying movements such as restlessness, hyperactivity, and other inappropriate movements. In addition, this test does not provide inter-reaction data. If the subject undergoing the test has reading disabilities, this reduces the ability of the subject to respond accurately and increases the response time. T. T. et al. O. V. A. Is another computer-based test used as a diagnostic aid for ADHD that records the response using a microswitch. This utilizes auditory and visual stimuli that remove restrictions on reading level. However, it cannot measure the reaction time and the accompanying and / or inter-reaction movements that may contribute to the mission and commission errors.

  Once the diagnosis is properly established, it is then important to establish a course of treatment. This is essential in both the school and medical fields. Attention deficits that lead to the onset of some of the common comorbidities such as anxiety and depression greatly limit adequacy and long-term potential. Dealing with these symptoms at an early age is crucial to reducing these harmful effects over time.

Drug therapy and talk therapy are central to attention deficit treatment courses and generally limit the availability of cognitive training interventions as a way to treat attention limitations. Existing ones that are often distributed on laptops, iPhones, or ipads do not consider the following because of the devices used.
• Detailed behavior patterns before and after the reaction cannot be monitored.
Data collection occurs only on one device, not more than two devices.
-It is not possible to test attention depending on the degree of spatial differentiation.

  Because there is a lack of data-driven methods to help diagnose and treat these and other disorders, a platform is needed that collects, stores, and analyzes data to reveal patterns in physical and cognitive behavior. ing.

  Furthermore, drawing people with ADHD, ASD, and other medical conditions into their treatment is another obstacle to the recovery that evidence-based tools need. Studies show that games can appeal to this blockage and provide this pull-in.

  The present invention solves many of these problems. The present invention provides a platform for collecting data that has not previously been qualitatively or quantitatively available. This platform obtains a reaction pattern and an inter-reaction movement pattern from each player. The system then combines this data with demographic attribute information and parses it globally to generate a profile that describes the player's behavior.

  This new data is generated by manual game interactions and reactions. This platform using a gaming system improves entrainment by taking advantage of human psychological tendencies to entertaining tasks triggered by visual and auditory stimuli. Techniques applied to this new type of data make it possible to assess and treat attention deficits and / or many of their comorbidities such as depression, anxiety, and ASD.

  This platform uses a tangible graphical user interface. One type of such device shown in FIG. 1 is known as “Shifto Cube”, a game platform made by Sifteo, Inc., San Francisco, California. The Shifto Cube is a motion detection radio block including a plurality of sensors and a variable display. The Shifto Cube can interact with each other in all four aspects. The Shifto Cube can be operated manually.

  Due to the characteristics of such devices, the gaming system makes it possible to consider the third dimension, which was the limit of conventional hardware devices. For example, the computer cannot indicate what the participant is doing during the disturbances. In contrast, these devices can provide clues for movement in tilting, pushing, and proximity movements. This is at a very granular level. This is because each device has an accelerometer. Furthermore, the game platform is designed to acquire data at sub-second intervals. In addition, although iPads may provide clues about participant behavior during disturbances, the platform itself is less interactive because in-game interactions do not require tangible motion.

A further advantage of using this system is insight into spatial attention ability. Neither computer-based tests nor iPads can test auditory spatial attention and visual spatial attention. The innovative platform we designed captures this type of data and creates a more robust tool. Some other advantages of this platform over existing technologies such as iPad / iTouch / iPhone include:
• The behavior pattern before and after the reaction can be monitored.
・ The effect of reading problems on reaction time and reaction patterns is eliminated.
-Allows multiple devices to collect granular data during a test session.
• The platform provides an auditory response pattern.
Tests for auditory spatial attention and visual spatial attention.

  This platform is widely useful for collecting data useful for diagnosing and treating problems in all cognitive domains. One embodiment, referred to as Groundkeeper, is specifically designed as a diagnostic aid cognitive improvement tool that allows treatment focused on executive functions such as ADHD in children and adolescents. In this game, four interactive devices or sensors are used. At any given time, gophers, groundkeepers, or empty ground appear on the device at a randomized frequency. Please refer to FIG. During certain levels, larger auditory and visual disturbance stimuli are added. Rabbits and / or birds appear between these levels, increasing the disturbing stimulus. The sound of the birds singing also changes to one or several birds. Participants are required to react as quickly as possible by having the device showing gophers hit the gavel (fourth device). The participant is instructed to hit the device only once and hears a sound indicating that the participant has hit the gopher as intended. The indicated arrangement for the basic level of the game on the device for the participant can be seen in FIG. Participants are instructed not to react to other stimuli, to do other exercises with the device, nor to cause the stimulation device to hit more than once.

  While this game or test is monitoring the behavior before and after the reaction by analyzing the degree of movement of the device as the game's difficulty increases, including the addition of spatial disturbances in later stages of the game Are designed to test several areas of attention by including a combination of multitasking techniques. In addition to providing diagnostics for executive function deficiencies, this tool analyzes tangible graphical device operational patterns using game-based applications that provide instant feedback and fine-tune patient abilities. Can treat these defects. This feedback over time is a behavior-based intervention that can improve attention capacity as a measure of executive function without the need for drug therapy. This feedback can also monitor the effects of drug therapy treatment over time.

  Another game is called Loopets. Please refer to FIG. This game is useful for intervention purposes in ASD. This game is designed to be used with more than two tangible devices. One device fits into a toy caterpillar pocket, while two or more players are each given one device. The goal of the game is to obtain a leader and follower where the leader moves the caterpillar in a series of actions over a set period of time and then causes the follower to perform the same exercise. This allows the game to capture data differences based on the movements of the devices incorporated in the caterpillar and follower, i.e., the data difference between the leader and the follower. This data is used as a feedback mechanism for behavior patterns common to social defects such as ASD. This disorder causes the temporal gyrus, a part of the brain, to be defective in visual processing. Visual processing is an extremely important process for successful social interaction. Research has shown that the function of this area of the brain can be improved by the principle of neuroplasticity, similar to muscles that improve function through exercise, but to improve this function from those with the condition Detailed tracking of the reaction is required. This activity requires the therapist, teacher, or in this case the leader, to provide physical instructions, mainly through exercise, although they are auditory instructions. The patient or player interprets this instruction and attempts to imitate it. This comprehension by the temporal gyrus appears in the player's response and shows its improvement by tracking this movement over a period of time, thus allowing the patient or player to mimic that movement. Using data from games that provide feedback, the reader can guide the patient to fine-tune their patient's physical movements in conjunction with improved visual motion processing for patients with ASD.

  Physically active games affect dopamine and norepinephrine, brain chemicals that regulate attention, mood, memory, and learning. Our game, Loopets Racing, increases physical activity, thereby increasing these chemicals and is affected by the imbalance of dopamine and / or norepinephrine, especially attention deficits, mood disorders, Useful because it provides natural treatment for disorders involving anxiety disorders.

  Data is acquired and stored in real time as the game is played. The acquired data is then parsed using the algorithm of the present invention and accumulated into predictive data that can be used by experts in diagnosing or treating cognitive impairment.

It is a figure which shows the place where the child is operating four cubes of 1st Embodiment. It is a figure which shows the graphic displayed on four cubes of 1st Embodiment. It is a figure which shows use of a gavel in 1st Embodiment. The player must use a gavel to strike a cube that represents a gopher. FIG. 7 illustrates a second game embodiment in which one cube is a leader and a second cube is operated by a follower / patient. It is a figure which shows the outline of a game platform. It is a figure which shows the interaction of the player and game in 1st Embodiment. FIG. 3 is a diagram illustrating the overall data flow of a game that is a component of a wider platform. It is a figure which shows the various states of the state machine which controls a game. It is a figure which shows the base device which carries out wireless communication with four cubes. It is a figure which shows the mechanism which a Shifto Cube uses to display a graphic. It is a figure which shows the place where the sound and the image are pushed to the cube from the base station. It is a figure showing what arranged two cubes closely. 1 is a diagram illustrating a game platform that communicates with an online database system. FIG. FIG. 6 illustrates a process for determining whether registration has been performed previously. It is a figure which shows a registration process. FIG. 6 shows a process for generating a registration code from a unique cube number. FIG. 5 shows a process for displaying a registration code on a cube. It is a figure which shows what displayed the registration code on the cube. It is a figure which shows the website registration form which registers an account holder into a link identifier. FIG. 6 is a diagram illustrating a procedure for communicating between an account holder and a web server application using a web registration form that is examined to determine whether a particular “owner” is pre-registered. FIG. 7 illustrates a procedure by which a base device receives a list of players unique to the owner of a particular set of cognitive cubes from a web server owner data store. FIG. 3 shows a system perspective of player lookup based on owner registration identifier and player data from a web host or server. FIG. 5 illustrates a base device procedure for retrieving player data and storing player data in an array in response to communication of a unique identifier to a web-based server. FIG. 6 illustrates a method for displaying a player's name on a set of cubes using a recognition cube. FIG. 5 shows the overall process of player selection using a cognitive cube. FIG. 5 shows a form that can be displayed on a web-based server where an account holder or owner can add a player to his account at any time. This form shows the type of data that can be entered and / or reported. Process for communicating game data to a web server or host or its internal storage and collecting the game data in memory for a player associated with a particular game just played according to the owner data store FIG. It is a figure which shows the data flow of the game logic which produces | generates game data and exercise | movement data. FIG. 2 shows a game state machine that repeats at sub-second intervals to acquire data from the cognitive cube and store the data in an array located in memory. FIG. 5 shows a data array arranged in memory divided into a plurality of things written at sub-second intervals, each column being derived from one or more of the cognitive cubes associated with a particular game. Associated with a particular measurement. FIG. 6 illustrates a procedure for uploading game data into a game store located on a web server or host associated with a specific owner and a specific player. The player is given the option to play again, whereby a new set of data is accumulated, statistically analyzed and communicated to a web host or server.

  Each game on the device collects player data, is synchronized, and is stored on a host or server computer. From this system, data is aggregated with demographic attribute data, educational data, and medical data and then analyzed to elucidate player behavior. These results are displayed on a user interface such as a mobile phone or web browser. This platform can be applied to any tangible graphical user interface that utilizes multiple interactive devices or sensors.

  In the first embodiment (see FIG. 5), the Shifto Cube 10 is wirelessly linked to the base device 14 operating as a computer (12). This device can be a computer provided by Shifteo, or a specialized firmware, called Shifto Base. In either case, the game is described using a Shifto SDK that supports the C ++ programming language, the Python programming language, or the C # programming language. These games are described and compiled and then executed by this base device or computer. Some parts of the game, which can be images from the game, are loaded onto the Shifto Cube before the game is played. The computer or base device is responsible for acting as the master node for this distributed system, which may involve several cubes. This computer or base device, as a master node, controls the coordination of the game and serves as a landing area for any game data received from the player during play. A schematic diagram of this Shifteo system is shown in FIG. For more details on the Shifto Cube system, see the following Shifteo patents: US Patent Application No. 12 / 909,690, US Patent Application No. 13 / 341,780, and US Design Patent No. 635190. Please refer.

  The platform data collection and storage data flow is defined in FIG. As described, the game collects player data, which is uploaded to the host or server computer, and this data is combined with the player's demographic attribute information, Analyzed to provide a behavioral profile.

  FIG. 7 shows the overall data flow of the game, which is a component of the wider platform. Data flows in each game according to control from the state machine. Once started (704), a Shifteo account holder is required to register (708) the device through the web with CogCubed, the website, if the device has not been previously registered (706). Upon completion (712), a list of players relevant to the account holder is shown on the device (710). If the device is not registered, a default player list is shown to the device (714). The player or players are asked for the names of those players to start the game (716). The game is then played and data is collected (718). When the game ends (720), the player or players can play again (722) or stop (724).

  FIG. 8 is based on various transitions in the game from the start of the game (704) to account holder registration (708), player selection (714), game play (718), game end (724). The data flow is shown. These are all events that are logically controlled by the state machine controller interface available in the Shifto SDK. Each state is executed until the logic advances, regardless of whether the game logic is activated by a human or computer. This is a standard interface utility in the Shifto SDK used to control the game state. The game is designed for tangible graphical systems such as Shifto Cube.

  More particularly, the player begins a game by loading or installing 702 a particular game on a computer or base device. This follows the Shifto game install instruction. The player then starts the game by launching the 702 runtime library (702). This library is also present on the computer or base device. This causes the computer or base device to start executing the game executable file. This game executable is described by C ++, C #, or Python and is based on specifications available from the Shifto SDK. By executing the game, the state machine is started and the first state, eg 706, is started.

  Referring to FIG. 9, a computer or base device 902 communicates wirelessly with one or more cubes 904-910 by executing the program. Each cube displays a graphic. The base device 902 plays music in the background from the computer or the base device. This music informs that the game has started. Communication is bi-directional. Each cube transmits and receives signals to and from the computer or base device, and also transmits and receives signals to and from each other.

  FIG. 1 shows a child playing a CogCubed game using a cube from the Shifto Cube system illustrated in FIG. One example of an image that can be displayed is shown in FIG.

  FIG. 10 is an overview of the mechanism that the Shifto Cube uses to display graphics. Game graphic images 108, 110, 112 are displayed on the cube by using logic and structures available in the Shifto SDK 102. This logic requires the game graphic to be an image index or structure 104 by using the Shifto utility 106 for image bundling. The images referenced by the Shifto structure exist in a directory accessible by the game system. In this case, the logic in the game program uses C # code or C ++ code to call a function available in the Shifto SDK and reference this structure pointing to the image used by the game. The original Shifto Cube employs the use of C # in the Shifto SDK, whereas the new version of the Shifto Cube uses C ++ in the Shifto SDK.

  Referring to FIG. 11, the game starts (704) and a start event in the state machine is started (718). The graphic defined in the structure is displayed on the cube using the logic from the Shifto SDK. Audio files in the format of WAV files or MP3 files are also played during this event in the game. These files referenced by the game system are played, stopped, or looped in the game by referencing the sound utility in the Shifto SDK. Unlike images, these audio files do not need to be bundled together in an index or data structure. This is part of the Shifto SDK.

  Referring to FIG. 12, the cubes are physically placed by the user. This proximity arrangement can be used to advance the game state machine seen in FIG. The Shifto SDK provides a proximity event handler. This handler can be used to logically change the state in the game.

  In one embodiment shown in FIG. 13, from the starting state, on the host 1204 or server computer (s), the online hosted player account is linked (1206) to the Shifto Cube system 1200. Is shown to advance the state machine. This link is based on a key (not shown) that exists in both the cube and the host or server computer system. This key is required to link (on output 1208) the player's physics from the GameCube to information about each player such as demographic attributes, education, and medical history.

  This link is created through a generated key that is identified on the cube and then associated with a particular set of cubes. This particular set of cubes must then be registered online by the particular cube account holder 1202. The logic from the cube looks up this key on the host or server computer and returns the names of all players associated with the account holder to the cube.

  The logic in the registration state first verifies whether registration has been performed so far, using an algorithm that examines and determines a special data structure represented by the Shifto data class in the Shifto SDK. This special data store uses non-volatile storage and survives when the game is stopped and the system is turned off. This algorithm process can be seen in FIG.

  The data store structure 1404 that is part of the Shifto SDK is examined for the presence of a unique account identifier that informs registration. If the identifier is found, the state transitions to the player state. If the identification information is not found in the non-volatile data structure, a different algorithm 1410 detailed in FIG. 15 is invoked to generate an identifier that is displayed on the cube and used for account registration. The registration process 1410 occurs when the cube account holder has not registered his device on the web.

  Referring to FIG. 15, the game platform uses an unique device ID 1502 (see below for more details) associated with a particular cube to generate an account ID that includes the key described above (1504). The game platform opens a web browser to the player (1508), inputs a numeric registration code (account ID) 1506 displayed on the game cube (1510), and hosts this data, account ID or registration code. Instructs the server computer data store 1512 to submit.

  If the cube account holder has previously registered these cubes, the algorithm finds identifier values (key, account ID, registration code) in this data store. This in turn triggers the state machine to go from registration to a player state for player selection. The logic performed by the algorithm can be seen in FIG.

  If the logic in the registration state does not find an identifier value indicating a previous registration, a different algorithm shown in FIG. 16 generates a unique numeric identifier created from one of the devices. Each cube from Shifteo is shipped with a unique hard-coded identifier 1602 that can be read programmatically through the Shifto SDK. This algorithm shown in FIG. 17 uses a C # code to parse the last few digits of the identifier from each cube (1604), and a unique key that ultimately links the physical cube to the player account. Create The process from generating unique identifier 1604, storage 1606, and display 1608 is shown in FIG. The display shown in FIG. 18 instructs the user to register a registration code (unique identifier) on the registration website.

  The identifier (1604) is stored in a special data structure 1606 represented by the Shifto data class from the Shifto SDK. This identifier is written to this structure by using the C # method from the Shifto SDK. The logic ensures that this identifier is written only if the data structure is empty.

  Referring to FIG. 17, a unique identifier 1702 parsed from only one randomly selected cube is displayed on the cube screen using another algorithm that writes the identifier digits to the display of one device. Using C #, a single cube is randomly selected from N possible cubes using standard randomization logic. This string identifier is then converted to an 8-digit decimal integer. The algorithm loops through each integer decimal number from start to end and matches the integer value against column 1 of the two-dimensional array 1704 (1710). Within this lookup array, column 1 contains a number, while column 2 (1706) contains the coordinate geometric location of each pixel needed to create that number on the screen. If it matches the integer in column 1, the algorithm retrieves the coordinates in column 2 and inputs the coordinates to the Shifteo class in the SDK that is responsible for displaying the pixels. Pixels associated with the matched integer are written to the cube and an X-axis offset is added as padding for that number if the next number exists. The new algorithm loops through all the numbers and executes this logic until all those numbers are written to the cube display.

  Referring to FIG. 18, the account holder is prompted to register this identifier on the CogCubbed website.

  On the registration website seen in FIG. 19, the player is required to provide this identifier and additional details related to his account. When submitted, the web form writes this data about the cube account holder to the host or server data repository by using standard web form technology. Referring to FIG. 20, the web form is programmed to verify that an account has not yet been created using server-side validation.

  The game platform prompts the account holder to press the cube to complete registration and advance the state. By physically pressing this cube, which is logically handled through the Shifto SDK event handler, the state machine transitions from registration 708 to player selection 718 (FIGS. 7 and 8).

  Referring to FIGS. 21 and 22, one or many players can be added to an account by using a web form on a host or server computer. This web form uses standard web techniques to insert player data such as demographic attributes, education, and medical history. This data is linked to the account identifier, allowing game dates to be combined with detailed player data.

  Referring to FIGS. 21, 22, and 23, advancing the state machine from registration to player selection triggers retrieval or display of a player list for selection by the user or player. (The player list is associated with a set of cubes via a unique ID or key.) This is performed through the following method whose overall process can be seen in FIG.

  The unique cube identifier stored in the data structure represented by the Shifto data class from the Shifto SDK is used to look up player data from a host or server data repository containing user data or player data. This retrieval process consists of. Use C # code and libraries supported by the NET framework. this. The NET framework is separate from the Shifto SDK, but is interoperable. In newer versions of the Shifto SDK, the C ++ library can be used to accomplish the same task. The web server uses the numeric identifier associated with the set of cubes (account) as a filter or predicate in the query to select player details from this repository and return it to the game cube. If the unique identifier matches the identifier registered online from the web form, this query retrieves all players associated with that particular account. The player list is sorted alphabetically from A to Z during this retrieval. The names or handles of these players, represented as character strings, are returned from the query and written to a string array in memory in the game. One player is assigned to each element of the array of N elements. This array automatically sizes itself based on the number of players returned. See FIG.

  If it does not match, this indicates that it is not registered or is improperly registered and a default male and female player name list is returned to the array. The special Shifto SDK data store is also reset to NULL or empty, so it will be prompted for registration on the next use.

  Referring to FIG. 24, player names are logically accessed in the player array by physically tilting the cube to the left or right. This movement triggers a tilt event handler supported by the Shifto SDK. This handler logic triggers a new algorithm that changes the pointer location in the array to refer to the higher or lower elements assigned to the index. As the index location changes, the algorithm points to the new array location, loads the contents of that location, which is the player's name, and then writes out each character of the player to spell the player's name. If the cube is physically tilted to the left, the algorithm decrements the array pointer by 1 if the array pointer is greater than -1. This prevents the program from leaving the boundary in the array. When the device is physically tilted to the right, the pointer value is then incremented by one.

  Based on the location of the pointer in the array, the algorithm loops each character in the player's name from left to right and matches the character value against column 1 of the two-column array. Within this lookup array, column 1 contains the character, while column 2 contains the coordinate geometric location of each pixel needed to create that character on the screen. If it matches the character in column 1, the algorithm retrieves the coordinates in column 2 and inputs these coordinates into the Shifteo class in the SDK that is responsible for displaying the pixels. The pixels associated with the matched character are written to the cube and the X-axis offset is added as padding for that number if the next number exists. The algorithm loops through all the characters in the player's name and executes this logic until all those characters are written to the cube display.

  Referring to FIG. 25, the player is instructed to tilt the device to control player selection. Each tilt to the right displays a new player on the device. When the player advances the player list to the desired player, the player is instructed to press the device.

  The player has the option of selecting one or more players for the multiplayer game by repeating the selection process. Physically pressing the cube is handled by the Shifto SDK event handler. This saves the selected player in the array. By pressing the cube twice consecutively without selecting a new player, the state machine proceeds from player selection to game start. The game state begins and the state machine remains in this state while the game is being played by each player. FIG. 26 shows several types of data fields that can be associated with each player.

  Referring to FIG. 27, a game is played and data is acquired. The game data includes subsequent physical responses from the cube exercise. This data is acquired in memory and transferred to the host or server computer data repository at the end of the game state. This data repository is linked to other player data via registration and player links.

  Referring to FIGS. 28, 29, and 30, the game begins and the state machine remains in this state until the game is complete. Game logic drives the player's reaction. Physical cube movement causes data input to the computer (FIG. 29). This cube motion data is collected in an array in memory along with the game data at subsecond intervals during the game state (FIG. 30). This data is logically stored as a variable in C # and is written to the array. Numeric and string variable data is updated in real time as the game is played in the game state. These variables are written directly and constantly into the array until the state machine goes through the state and stops when the state stops.

  The game data listed in Table I refers to game events, images, timers, randomizing counters in sequences, scoring counters, level counters, and other stimuli needed to play the game. The type and frequency of images and sounds are important for all games because of game play and the generation of reactions by physically moving the cube. These types of game objects are controlled through the Shifto SDK. The variables from Table I are aggregated between levels, levels, and game perspectives for various types of analysis.

  The physical movement data similarly listed in Table I includes any movement of the cube by the player. The Shifteo SDK event handler is used to report physical responses to the cube. The types of combination data obtained from games and physical exercise can be found in Table I.

  Referring to FIG. 31, the game state ends after a defined time period or after a goal is achieved by the player. This changes depending on the game and is controlled by logic defined in the Shifto SDK.

  If the player chooses to play again, the state machine resets itself to the starting state. If the player chooses not to play again, the state machine ends.

  As shown in FIG. 31, when the game state is ended because the set time has elapsed or the player has completed the purpose, the combination of the game data and exercise data stored in the array is the player identifier and account. Based on the registration identifier, it is uploaded and transferred to the host or server computer through a standard web protocol. The algorithm loops through the array storing the data, then. A NET library is used to transfer data securely. Newer versions of Shifto SDK can perform the same task using the C ++ library. The account registration identifier and player identifier are included in the uploaded data (Table I). These exist for account registration and player creation, which are important to the present invention. This allows all of the collected game data to be linked to data stored on the host or server computer. This includes demographic attribute data, education, and medical history of self-reported players. See FIG. The combined data, including game data, exercise data, and player data, is analyzed to provide a complete player profile across multiple cognitive domains.

  Table II shows the game summary statistics representing several factors that indicate impulsivity and carelessness. These summary statistics are generated through summation, average, and standard deviation calculations of reaction metrics across the game data by the player. Inattention generally results in more mission errors and less tilting momentum than control. Impulsiveness is expressed as more commission and more tilting momentum than controls. This response pattern is derived from the physical movement of the cube to various sound and image stimuli.

  The game can use disturbing stimuli. FIG. 2 is an example, where the player is taught to strike a gopher with a gavel. Gophers appear randomly, and other characters, such as a boy mowing the lawn, may appear randomly with the gopher and disrupt the player.

  FIG. 4 shows more detailed content about the player's movements acquired during the game. Players with more or less exercise than other players or instructors give different data profiles that may indicate cognitive deficits.

In a clinical trial of the system at the University of Minnesota, several classifier algorithms used in this platform combine player / patient data with demographic attribute data, educational data, and medical data. Produces statistically significant results in predicting diagnosis, type, and comorbidity based on The classifier algorithm relies on transformed data from the game. For example, neighbor_reaction time (item 45 in Table I) is a converted variable. This variable is calculated as follows: When considering the variables in Table I, first perform the subtraction VirtualTicks-CubeNCounter, then take this difference for each game instance into account and take the maximum CubeNCounter, and finally find the sum of CubeNCounter for each game instance As a result, the total amount of neighbor reaction for each game played is obtained. A sample SQL code that produces this transformed variable can be seen below.
The above algorithm results in a stochastic output that indicates whether the player has a certain percentage of the diagnosis and type of cognitive impairment such as ADHD, ASD, anxiety, or depression. These results can be used as diagnostic aids and / or in interventions. Exemplary results are shown in Table III.

  Inattention symptoms are measured by the increase in reaction time measured by virtual ticks, fewer commissions as defined in Table II than controls, and TiltX + TiltY + TiltZ as defined in Table I Such accompanying momentum is indicated by less than the control.

  Hyperactivity and impulsivity are defined in Table I, especially when spatial components are introduced at the game level as required by measuring spatial coordinates, thereby reducing the overall reaction time. Can be judged by the fact that there are more commissions compared to the control. There are several types of reaction times measured by ticks from the time a new stimulus is presented to the time of response. Various types of reaction times are obtained based on correct or incorrect reactions.

  ASD symptoms are determined by the fact that the mission is higher than the control, especially when spatial components are introduced at the game level, as determined by measuring spatial coordinates. It is confirmed that the commission as defined in Table I increases in response to disturbance.

  Anxiety symptoms are judged by the non-uniform distribution of response times across sessions as measured by ticks from the time a new stimulus is presented to the time of response compared to controls. Various types of reaction times are obtained based on correct or incorrect reactions. Anxiety symptoms are also judged by the higher amount of mission as defined in Table I compared to controls. In addition, an increase in momentum as defined by Table I also appears compared to the control.

  Depressive symptoms are more missions and commissions as defined in Table I compared to controls and increased cube proximity response time as defined in Table I compared to controls And when the spatial relationship as determined by measuring spatial coordinates is applied, the proximity reaction time is further increased compared to the control.

Claims (12)

A statistical data collection system,
A base device (14);
A plurality of cubes (10) responsive to three-dimensional motion and proximity to other cubes, and transmitting data relating to the three-dimensional location and proximity to other cubes to the base station; With cubes,
The base device is configured to selectively transmit images and sounds to the cube such that a player must react (12) to perform a predetermined action;
The base device is further configured to periodically obtain the data from the cube and record the data in a table, the data including data related to cognitive impairment;
The statistical data collection system, wherein the base device is further configured to determine statistics from the table, the statistics including a sum, average, and standard deviation that generate response metrics indicative of cognitive impairment. A web-based server (1204) configured to store player data including a player's name and medical history;
Means (1206) for establishing a unique relationship between a particular set of cubes and the web-based server;
The system of claim 1, further comprising:   The system of claim 2, wherein the base device is configured to determine (1504) a unique number associated with a particular set of cubes and use this number to communicate with the web-based server. .   The system of claim 3, wherein the base device and the web-based server are configured with each other to download relevant player data for each player associated with a set of cubes to the base device.   The base device reacts by the player responding in a specific way to different cube configurations or by following the lead of a lead cube operated by a person other than the player being diagnosed The system of claim 3, further configured to instruct the player to play a game involving the use of the cube.   The system of claim 5, wherein the specific configuration includes a predetermined disturbance configuration and the response to such disturbance includes a sign of cognitive impairment.   The table can be configured to record the occurrence of a particular disturbance configuration in the table, and the data from the table following the disturbance configuration can be selectively analyzed to determine a particular response The system of claim 6, wherein   Based on summary statistics, the inattentive symptoms are that the reaction time measured by virtual ticks is compared to the control and that the commissions as defined in Table I are less than the control. 8. The system of claim 7, wherein the system is determined by less associated motion as measured by TiltX + TiltY + TiltZ as defined in Table I as compared to the control.   Based on summary statistics, hyperactivity and impulsive symptoms reduced the overall reaction time, especially when the spatial components were introduced into the game level as required by measuring spatial coordinates. 8. The system of claim 7, wherein the system is determined by comparing commissions as defined in Table I, which are sometimes increased compared to controls.   Based on summary statistics, ASD symptoms compare commissions that have increased beyond control, especially when the spatial component is introduced at the game level, as determined by measuring spatial coordinates. The system of claim 7, wherein the commission as determined by and determined to increase in response to disturbances is determined.   Based on summary statistics, anxiety symptoms have a heterogeneous distribution of response times across sessions as measured by ticks from the time a new stimulus is presented to the time of response compared to controls 8. The system of claim 7, wherein the momentum as determined by and defined by Table I is increased compared to the control.   Based on summary statistics, depressive symptoms are associated with a higher number of missions and commissions as defined in Table I compared to controls and the proximity response time of the cube as defined in Table I. Claims determined by an increase in comparison and an increase in proximity response time compared to a control when a spatial relationship is applied as determined by measuring spatial coordinates. 8. The system according to 7.