KR102564072B1 - multi cognitive training device using artificial intelligence and method for player cognition using the same - Google Patents

Abstract

A cognitive training device based on a content game for multiple players according to an embodiment of the present invention includes a display unit displaying a content game and detecting a touch input for the content game; and a management system that controls the display unit, wherein the management system includes: a display unit that receives the sensed touch input and controls the display unit to display the content game; a storage unit for storing information about the content game and information about a user playing the content game; a recognition unit recognizing a touch pattern for a touch input received from the display unit; a determination unit determining object information corresponding to the touch pattern recognized by the recognition unit; and a control unit that determines a specific input for the content game or a subject of the touch input according to the object information determined by the determination unit.

Description

Content game-based cognitive training device and method for multiple players {multi cognitive training device using artificial intelligence and method for player cognition using the same}

The present invention relates to a content game-based cognitive training device and method for a plurality of players enabling a plurality of users to receive cognitive training and cognitive stimulation through a content game at the same time.

As people's average lifespan is significantly extended, the incidence of geriatric diseases is also rapidly increasing. According to US statistics, mortality rates from major diseases such as cancer and cardiovascular disease are steadily decreasing due to improved treatment methods, but death rates from dementia are reported to be continuously increasing.

In fact, according to the Alzheimer's Association of America, since 2000, the death rate due to dementia has increased by 89%. Along with population aging, the incidence of dementia is also increasing, and the cause of dementia has not yet been identified. However, the information related to dementia known so far is as follows.

When the brains of patients with dementia were analyzed, a typical example was the fact that clumps (plaques) of a protein called amyloid beta were observed as a kind of waste along the periphery of the brain cells. Based on this, research on removing amyloid beta was actively conducted at one time, but it was not established as an alternative to solving dementia. This is because, even if amyloid beta was removed, there were many cases in which people's cognitive abilities did not improve, and even people with many plaques (clots) did not suffer from dementia.

In addition, it has been reported that people with dementia in the early stage often recover from dementia with continuous cognitive ability training and cognitive stimulation rather than the above-mentioned drug treatment method.

For this reason, many complex stimulation devices or methods for preventing dementia by simultaneously providing physical activity and brain stimulation have been proposed, and Korean Patent Publication No. 2009-0067578 is one of these technologies. This technology is a method in which game contents such as language, math, or common sense are provided to users through a monitor, and when the user takes a specific reaction action according to the instructions of the provided contents, the result is fed back to the user.

Although this technology is expected to increase the concentration of education in that it can visually provide various types of content games to users, it is possible to store the results of repetitive tests without information about the users, and thus provide contents for each level. method to provide.

In addition, since the technology of Korean Patent Publication No. 2009-0067578 provides brain stimulation using game contents to a specific user, it is limited to individual dementia patients. That is, there is a problem in that people with similar dementia states cannot provide cognitive ability training or cognitive stimulation in a cooperative manner.

Republic of Korea Patent Publication No. 2009-0067578

An object of the present invention is a content game-based cognitive training device and method for multiple players using artificial intelligence capable of providing various cognitive training and cognitive stimuli such as visual, auditory, and physical movements to dementia patients or patients with low cognitive ability. is in providing

In addition, an object of the present invention is a content game-based cognitive training device and method for multiple players using artificial intelligence, in which a plurality of dementia patients or patients with low cognitive ability can receive cognitive training and cognitive stimulation in a cooperative manner at the same time. is in providing

In addition, an object of the present invention is to analyze various touch patterns input to the display area by players while playing a content game through a learning model based on deep learning, and then to artificially recognize an object or player inputting a touch pattern accurately. It is to provide a content game-based cognitive training device and method for multiple players using intelligence.

In addition, an object of the present invention is a content game base for multiple players using artificial intelligence capable of distinguishing players who provide touch input in a content game based on the motion of the player playing the content game and the patterns input to the display area. It is to provide a cognitive training device and method of.

A cognitive training device based on a content game for multiple players according to an embodiment of the present invention includes a display unit displaying a content game and detecting a touch input for the content game; and a management system that controls the display unit, wherein the management system includes: a display unit that receives the sensed touch input and controls the display unit to display the content game; a storage unit for storing information about the content game and information about a user playing the content game; a recognition unit recognizing a touch pattern for a touch input received from the display unit; a determination unit determining object information corresponding to the touch pattern recognized by the recognition unit; and a control unit that determines a specific input for the content game or a subject of the touch input according to the object information determined by the determination unit.

In addition, a content game-based cognitive training method for multiple players according to an embodiment of the present invention includes a display unit displaying a content game and detecting a touch input for the content game, and a management system controlling the display unit. A content game-based cognitive training method for multiple players provided by a multi-cognitive training apparatus comprising: controlling the display unit to display the content game; Receiving a touch input for the displayed content game; Recognizing a touch pattern for a touch input received from the display unit; determining object information corresponding to the recognized touch pattern from a pre-stored list; and determining a specific input for the content game or subject of the touch input according to the determined object information, and proceeding with the content game.

Content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention can provide various cognitive training and cognitive stimuli such as visual, auditory and physical movements to dementia patients or patients with low cognitive ability It works.

In addition, the content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention can provide cognitive training and cognitive stimulation in a manner in which a plurality of dementia patients or patients with low cognitive abilities cooperate at the same time It works.

In addition, the content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention analyzes various touch patterns input to the display area while players play the content game through a learning model based on deep learning. After that, there is an effect of accurately recognizing an object or a player inputting a touch pattern.

In addition, a content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention provides touch input in the content game based on the motion of the player playing the content game and patterns input to the display area It has the effect of distinguishing players.

1 is a diagram showing how users use a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention.
2 is a perspective view showing the structure of a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention.
3 is a block diagram of a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention.
4A to 4D are diagrams showing how a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention provides a play area according to the number of users.
5 is a diagram for explaining a process of recognizing a user or an object based on a touch input input to a display unit by a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention.
6 to 8 are views for explaining the principle of recognizing a user using a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention and an object used in a provided content game.
9 is a diagram for explaining a user's touch motion and content object motion in a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention.
10 is a diagram illustrating a state in which a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention recognizes a touch position of a display area.
FIG. 11 is a diagram illustrating a state in which possible touch patterns CP are estimated from touch contact units TC input to the display area DA.
12 is a diagram illustrating touch IDs corresponding to touch information such as the touch contact unit TC.
13 is a diagram in which a function corresponding to a touch ID is applied to a content game played in the display area DA.
14 is a block diagram showing a specific configuration of a recognition unit of a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention.
15 is a specific block diagram of a judgment unit of a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention.
16 is a diagram for explaining how a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention recognizes a plurality of players.

Since the present invention can apply various transformations and have various embodiments, specific embodiments will be illustrated in the drawings and described in detail in the detailed description. Effects and features of the present invention, and methods for achieving them will become clear with reference to the embodiments described later in detail together with the drawings. However, the present invention is not limited to the embodiments disclosed below and may be implemented in various forms. In the following embodiments, terms such as first and second are used for the purpose of distinguishing one component from another component without limiting meaning. Also, expressions in the singular number include plural expressions unless the context clearly dictates otherwise. In addition, terms such as include or have mean that features or elements described in the specification exist, and do not preclude the possibility that one or more other features or elements may be added. In addition, in the drawings, the size of components may be exaggerated or reduced for convenience of explanation. For example, since the size and thickness of each component shown in the drawings are arbitrarily shown for convenience of description, the present invention is not necessarily limited to the illustrated bar.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, and when describing with reference to the drawings, the same or corresponding components are assigned the same reference numerals, and overlapping descriptions thereof will be omitted. .

1 is a diagram showing how users use a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention. 2 is a perspective view showing the structure of a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention.

1 and 2, the multi-cognitive training apparatus 100 using artificial intelligence of the present invention includes a display unit 100a and a base unit 100b supporting the display unit 100a. The display unit 100a includes a display area DA providing various content games to users and a non-display area NDA disposed along the circumference of the display area DA. A display panel capable of displaying a content game may be disposed in an area corresponding to the display area DA. The display panel may be a touch screen panel (TSP) implemented with a liquid crystal display (LCD) or an organic light emitting display (OLED). In addition, the multi-cognitive training apparatus 100 of the present invention is a personal computer, laptop, notebook, netbook or tablet, personal digital assistant (PDA), navigation, home appliance, image processing device, It can be implemented in a device such as a smart phone, 3D TV or DID (Digital Information Display). In particular, each component of the present invention can be operated within the processor and memory disposed in the above-described devices.

Recognition means capable of recognizing a user may be disposed in the non-display area NDA. For example, a plurality of authentication pads (N1, N2, N3, N4) capable of checking information of a user using a content game may be disposed. The authentication pads (N1, N2, N3, N4) may recognize a card including user's unique identifier information and provide a customized content game based on the recognized user's information. In addition, when the first to fourth authentication pads (N1, N2, N3, N4) recognize different information for a plurality of users, based on this, a content game that a plurality of users can play together can be recommended or provided. there is. That is, the multi-cognitive training apparatus 100 of the present invention can provide a cognitive training content game or a cognitive stimulation content game required for each of a plurality of users, or recommend and provide a content game that a plurality of users can play together. there is. In this specification, a user using the multi-cognitive training apparatus 100, a player using a content game, and a user using a service provided by the multi-cognitive training apparatus 100 are used without distinction. Accordingly, the player who plays the content game may be named a user or a user because he/she uses or uses the multi-cognitive training apparatus 100 .

In addition, when the multi-cognitive training apparatus 100 using artificial intelligence of the present invention provides a content game performed by a plurality of users (P1, P2, P3, P4) or each content game suitable for individual users, display Area DA may be divided into first to fourth game areas 110a, 110b, 110c, and 110d.

A plurality of users (players: P1, P2, P3, P4) may place markers M in their respective divided first to fourth game areas 110a, 110b, 110c, and 110d and proceed with the content game. Also, the display area DA may include the common display area CDA. The common display area (CDA) is commonly applied to all of the multiple users (players: P1, P2, P3, P4) when multiple users (players: P1, P2, P3, P4) play one content game together. It may be a game area to be. In addition, when a plurality of users (players P1, P2, P3, P4) play individual content games, it may be a common area used by individual content games.

Referring to FIG. 2 , the display unit 100a of the multi-cognitive training apparatus 100 using artificial intelligence of the present invention may be implemented in the form of a rectangular plate or table. The upper surface of the display unit 100a includes a display area DA displaying a content game and a non-display area NDA. In addition, first sensor units 130a in which a plurality of sensors are disposed at regular intervals may be disposed on each of the four sides of the display unit 100a. The first sensor unit 130a serves to obtain location information of a user for playing a content game. Accordingly, the sensors constituting the first sensor unit 130a may be any one or a combination of at least one of an ultrasonic sensor, an infrared sensor, a LIDAR sensor, a radar sensor, and a camera sensor.

A second sensor unit 130b capable of obtaining face information (facial information) of users (players) may be disposed in the display area DA of the display unit 100a. In the drawing, four sensors are disposed in areas corresponding to each corner of the quadrangular display unit 100a, but this may vary according to the number of users playing the content game. For example, when 6 players play a content game, 6 or more sensors constituting the second sensor unit 130b may be configured.

The third sensor unit 130c may be disposed on an upper surface corresponding to each corner of the non-display area NDA of the display unit 100a. The third sensor unit 130c acquires information on the user's (player's) ID card when an ID card containing the user's unique identifier information is placed and provides a content game or a play area where the content game is played according to the number of ID cards. can be used to divide In addition, the third sensor unit 130c may play a role of recognizing the presence or absence of a player playing a currently provided content game based on a state in which the ID card of the player is placed. In particular, the area of the third sensor unit 130c may partially overlap the display area DA.

In the non-display area NDA of the display unit 100a, first to fourth authentication pads N1, N2, N3, and N4 may be disposed. In the drawing, although each of the four corner regions of the display unit 100a is disposed, it is not fixed. In particular, even if the user marker M is sequentially contacted by the control unit connected to the first to fourth authentication pads N1, N2, N3, and N4, information including unique identifier information for each user is stroked. If possible, only one authentication pad (N) can be placed.

In addition, in the multi-cognitive training apparatus 100 using artificial intelligence of the present invention, a fourth sensor unit 130d may be disposed in a space above the display unit 100a. The fourth sensor unit 130d continuously acquires subject information of players playing the content game and reflects it to the content game, or acquires motion information of the player (user) and uses it as information for determining the player's cognitive ability. The sensor constituting the fourth sensor unit 130d may be composed of a Charge Coupled Device (CCD) or a Complementary Metal Semiconductor (CMOS).

The base unit 100b includes a first support 120 that supports the display unit 100a and can vertically move, rotate, and tilt the display unit 100a, and is disposed below the first support 120 to It includes a second support part 121 in contact with. Components that control the operation of the multi-cognitive training apparatus 100 to be described below may be disposed inside the first support 120 . In addition, the second support part 121 may include a plurality of bridge parts to distribute loads between the display unit 100a and the first support part 120 while being coupled to the first support part 120 . As shown in the drawing, a moving means 123 may be disposed in each bridge unit.

Also, although not specifically illustrated in FIGS. 1 and 2 , the display unit 100a may be disposed in a horizontal direction or vertically inclined by the first support 120 . Accordingly, the first support 120 may include a shaft coupled to the rear surface of the display unit 100a to move vertically. The shaft can move up/down in the up/down direction by the power provided by the driving unit, and the display unit 100a is placed on the ground in response to the up/down motion of the shaft. It may be erected in a vertical direction or disposed inclined to have a predetermined angle with respect to the ground.

In this way, when the display unit 100a is erected or disposed at an angle, it can be used for a content game in which players are positioned on both sides with the display unit 100a interposed therebetween.

In addition, the display unit 100a may be provided with an event provider capable of providing players with a vivid sense of realism in the process of playing a content game. The event providing unit may be composed of a plurality of air nozzles, vibration motions, or intelligent speakers.

As such, the content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention provides various cognitive training and cognitive stimulation such as visual, auditory, and physical movements to dementia patients or patients with low cognitive abilities. There are effects that can be done.

In addition, the content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention can provide cognitive training and cognitive stimulation in a manner in which a plurality of dementia patients or patients with low cognitive abilities cooperate at the same time It works.

In addition, the content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention analyzes various touch patterns input to the display area while players play the content game through a learning model based on deep learning. After that, there is an effect of accurately recognizing an object or a player inputting a touch pattern.

In addition, a content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention provides touch input in the content game based on the motion of the player playing the content game and patterns input to the display area It has the effect of distinguishing players.

3 is a block diagram of a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention. 4A to 4D are diagrams showing how a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention provides a play area according to the number of users. 5 is a diagram for explaining a process of recognizing a user or an object based on a touch input input to a display unit by a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention. 6 to 8 are views for explaining the principle of recognizing a user using a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention and an object used in a provided content game. 9 is a diagram for explaining a user's touch motion and content object motion in a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention. 10 is a diagram illustrating a state in which a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention recognizes a touch position of a display area. 11 is a diagram showing possible touch patterns CP estimated from touch contact units TC input to the display area DA, and FIG. 12 shows touch information such as the touch contact unit TC. 13 is a diagram showing a touch ID corresponding to , and FIG. 13 is a diagram in which a function corresponding to a touch ID is applied to a content game played in the display area DA.

Referring to FIGS. 3 to 13 together with FIG. 2 , the multi-cognitive training apparatus 100 using artificial intelligence of the present invention includes a display unit 100a and a base unit 100b.

The multi-cognitive training apparatus 100 of the present invention may recognize users who play or tools used in the content game to provide a customized content game to the user. In addition, the multi-cognitive training apparatus 100 of the present invention may provide customized cognitive training or cognitive stimulation content games to each of a plurality of users according to their cognitive abilities. The multi-cognitive training apparatus 100 includes first to fourth sensor units 130a, 130b, 130c, and 130d, an input unit 301, a storage unit 302, a driving unit 303, a content providing unit 304, and a control unit ( 305), a recognition unit 306, a determination unit 307, and a display unit 308 may be operated by a management system.

As described above, the first sensor unit 130a acquires distance and location information between the user for cognitive ability training and the multi-cognitive training apparatus 100, and the second sensor unit 130b allows the user to play the content game. In order to acquire facial (face) information before and after playing in a state located at one's place, the third sensor unit 130c is a marker (M) including an ID card including user information or a card including object information. ) and the information of the marker M, and the fourth sensor unit 130d acquires motion information of players (users) playing the content game.

In particular, the second sensor unit 130b and the fourth sensor unit 130d may include a camera including a color image sensor and a depth image sensor. In some implementations, the depth image sensor may provide a depth image in which depth information of a scene is expressed as a 16-bit integer in [mm], for example. The number of bits for expressing depth information is not limited to 16 bits and may be changed, and may be provided in a real number type without being limited to an integer type. The depth image sensor may measure distances from a camera to an object and a background using infrared rays, etc., and provide a depth image having a value proportional to or inversely proportional to the distance.

The pixel value of the depth image may be, for example, not RGB color information but, for example, depth information in the unit of [mm] (but is not limited thereto) as an integer.

The color image sensor is a device that acquires a color image, and may be, for example, a complementary metal-oxide-semiconductor (CMOS) image sensor, a charge-coupled device (CCD) image sensor, or a stereo camera. The depth sensor may be a kinect, a time-of-flight (TOF) depth camera, or an optical 3D scanner.

The input unit 301 may include a touch screen panel since touch information may be input through the display unit 308 . Accordingly, the input unit 301 includes information provided through the first to fourth sensor units 130a, 130b, 130c, and 130d and the display unit 308, prior information about the user, and information related to the content game (pattern information). can be provided. Also, the input unit 301 may be integrally implemented with the display unit 308 .

The storage unit 302 may include information about content games and information about users. For example, when a user conducts a test to find out the degree of dementia in advance, result information thereof may be stored. Information about content games may include information about characters played in each game and information about operations that can be performed in each game. The storage unit 302 may include a hard disk drive (HDD), solid state disk (SSD), silicon disk drive (SDD), ROM, RAM, CD-ROM, magnetic tape, floppy disk, and an optical data storage device. . Storage 302 also includes instructions (eg, executable instructions), such as computer readable instructions or processor readable instructions. The instructions may include one or more instructions executable by a computer, such as by each of one or more processors.

For example, one or more instructions may be executable by one or more processors to perform operations that include processing a depth image to determine a motion vector of the depth image and to encode the depth image. there is.

As described above, the drive unit 303 physically moves the display unit 100a constituting the multi-cognitive training apparatus 100 or configures the first to fourth sensor units 130a, 130b, 130c, and 130d. It can provide power to move the sensors.

The content providing unit 304 may provide content games prepared for cognitive ability training and content games prepared for cognitive stimulation.

After recognizing and analyzing touch patterns based on touch information provided from the display unit 308 , the recognition unit 306 may recognize an object corresponding to the analyzed pattern. Also, the recognition unit 306 may recognize touch information provided by a player as well as touch information of a marker disposed on an object.

The determination unit 307 may acquire patterns recognized through the display unit 308 and object information corresponding to the patterns, or may filter recognized patterns but patterns unrelated to the current content game. In this way, a combination of the selected object recognition information and the touch information provided from the player through the display unit 308 may finally determine which command for which object.

In addition, the recognition unit 306 and the determination unit 307 may determine content games to be provided based on the number of users who will play the content game and information about the users. For example, when a plurality of users are authenticated by the multi-cognitive training device 100, an individually customized content game may be provided based on information of each user, or a content game in which a plurality of users may proceed together may be provided.

Also, the recognition unit 306 and the determination unit 307 may divide the display area DA into a plurality of areas to correspond to a plurality of authenticated users, and then provide a game area to each user. At this time, only when the user's marker is simply authenticated through the authentication pads, the display area DA is not divided and the information input through the above-described first to fourth sensor units 130a, 130b, 130c, and 130d is combined and divide

In particular, the multi-cognitive training apparatus 100 of the present invention, when a plurality of users play a content game, needs to move along the circumference of the display unit 100a, the second sensor unit 130b and the fourth sensor unit 130d ) can be used to individually recognize a plurality of users (players) and track their locations. In this way, when a player is recognized and tracked based on the images provided by the second sensor unit 130b and the fourth sensor unit 130d, when the first content game starts, the divided game area set for each player is displayed. It is possible to move to the location of the corresponding player along the edge of the area DA.

Accordingly, when the player moves while playing the content game, there is no need to return to his or her initially set divisional game area. If the divided game areas set for a plurality of users (players) overlap each other, use the ultrasonic sensor information of the first sensor unit 130a as the closest area to the game area immediately adjacent to the game area of the player. can be located. For example, when the second player is in the position of the fourth player while playing the content game, the second player is placed in an area adjacent to the fourth player's game area so as not to overlap with the fourth player's game area so that the next play can proceed. do.

As described above, since the input unit 301 can be integrally formed with the display unit 308, the control unit 305, the storage unit 302, the driving unit 303, the content providing unit 304, and the recognizing unit 306 , The determination unit 307 may be disposed in the base unit 100b of the multi-cognitive training apparatus 100.

4A to 4D, the multi-cognitive training apparatus 100 using artificial intelligence of the present invention can divide the display area DA into a plurality of divided game areas to correspond to the number of users using content games. there is.

When there are two users who will perform cognitive ability training or cognitive stimulation training through content games, the display area DA is divided into an A1 game area and an A2 game area, as shown in FIG. 4A. Two users can play different content games in the divided game areas A1 and A2 or play one content game simultaneously in their own game areas.

As described above, in the case of a cooperative game or competitive game in which one content game is played together, the user may move along the circumference of the display unit 100a while playing the game. In the multi-cognitive training apparatus 100 of the present invention, the divided game areas A1 and A2 recognize and track the user, and move the game area to a position corresponding to the current player position. Accordingly, the player (user) playing the content game can proceed with the next play at the moving position without returning to his or her initially set divided game areas A1 and A2.

When there are three users who will perform cognitive ability training or cognitive stimulation training through content games, the display area DA is divided into an A1 area, an A2 game area, and an A3 game area, as shown in FIG. 4B. When there are four users who will perform cognitive ability training or cognitive stimulation training through content games, as shown in FIG. 4C, the display area DA is A1 game area, A2 game area, A3 game area, and A4 game area divided into areas When there are 5 users who will perform cognitive ability training or cognitive stimulation training through content games, as shown in FIG. area and A5 game area.

In addition, as described above, in the case of a cooperative game or a competitive game in which 3, 4, or 5 players play a single content game together, when users move while playing the game, the divided game areas (A1, A2, A3 , A4, and A5) may move by tracking the movement direction of the users. Accordingly, players (users) playing the content game can continuously proceed to the next play from the position where the play was performed without returning to the initially set or previously located game area.

The multi-cognitive training apparatus 100 using artificial intelligence of the present invention can recognize objects such as tools used in content games or markers M capable of identifying users (players).

5 is a diagram for explaining how a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention recognizes a user's marker or a tool used in a game. User markers or tool markers are composed of physical objects. That is, it can be seen as the recognition of an object rather than the recognition of a part of the user's body.

Accordingly, the user marker M and the marker M attached to the tool include a touch point TP capable of providing touch information to the display unit 100a. For each marker M, the size of the touch point TP, the location of the touch point TP, and the number of touch points TP may be different.

Referring to (a) of FIG. 5 , when three touch points TP are disposed on a marker M and each touch point TP is connected, a triangular touch pattern CP implemented by the touch points TP can be obtained. Also, all areas of the three touch points TP may be the same or at least one may be different. As shown in the drawing, the area occupied by the touch point TP is the touch area TA, the touch pattern CP formed by connecting the touch points TP, and the area of the touch pattern CP is the pattern area. (PA), the direction (TD) of the touch point related to the direction information for each touch point (TP) is defined.

The multi-cognitive training apparatus 100 using artificial intelligence of the present invention may obtain information provided by each marker M by analyzing the touch points TPs disposed on the marker M. For example, figure information about whether the touch pattern CP is a triangle, a quadrangle, or a pentagon may be obtained using the touch point TP disposed on one marker M. That is, the multi-cognitive training apparatus 100 of the present invention may obtain information about the size and shape of figures constituting the touch pattern CP. Also, information about the touch area TA for each touch point TP may be acquired. In addition, information about the direction of the touch point TP corresponding to each vertex of the figure constituting the touch pattern CP may be obtained. For example, in the triangle of FIG. 5 (a), if a virtual mutually perpendicular direction coordinate axis is formed at the center, the upper vertex is north (N), the lower left touch point (TP) is southwest (SW), and the lower right touch point (TP) may obtain direction (TD) information of the touch point, such as southeast (SE).

In this way, the multi-cognitive training apparatus using artificial intelligence of the present invention can distinguish each marker M based on various information provided by the touch points TP disposed on the markers.

In addition, the multi-cognitive training apparatus using artificial intelligence of the present invention is the touch area of the touch points (TP) arranged on the marker, the touch pattern (CP) formed by the touch points (TP), and the touch pattern (CP) A plurality of markers can be distinguished from each other by combining the direction information of the touch point TP located at each vertex and this information.

6 illustrates a principle of recognizing a marker M of a user using a content game provided by the multi-cognitive training apparatus 100 . Markers M including different information are provided to users who play content games for cognitive ability training or content games for cognitive stimulation so that they can be recognized as different players in the game. The marker M may be recognized by the authentication pads N1, N2, N3, and N4 of the aforementioned multi-cognitive training device 100 or recognized by the marker recognition unit of the display unit 100a. As described above, the markers M each provided to a plurality of users may be composed of touch points TP having different numbers and shapes.

As shown in (a) to (e) of FIG. 6 , the first marker M1 and the second marker M2 have the same number of touch points TP. However, the first marker M1 has a structure in which the touch points TP are disposed at corner areas adjacent to each other around the touch points TP disposed at the corner of the first marker M1. , and the second marker M2 has a structure in which touch points TP are disposed at both corners and the center of the second marker M2. Therefore, the positions of the touch points TP of the first marker M1 and the second marker M2 are different, and the shape (shape of a figure) of the touch pattern CP is also determined based on the touch points TP disposed at each marker. It varies. Based on this information, the multi-cognitive training apparatus 100 of the present invention distinguishes the first marker M1 and the second marker M2.

Although only the first and second markers M1 and M2 with three touch points TP are shown in the drawing, a plurality of markers M composed of three touch points TP may be formed. When there are a plurality of markers M composed of three touch points TP, it may be difficult to accurately distinguish only the location of the touch points TP and the shape of the touch panel CP. In this case, the touch area TA for each of the touch points TP disposed on each marker M is made different or one or two of the three touch points TP are set to different types of touch points TP. ) can be implemented. For example, one of the three touch points TP may be formed as a circle, and the other two may be formed as an ellipse or a triangle (or quadrangular structure), respectively.

Referring to (c) and (d) of FIG. 6 , four touch points TP are disposed at the third and fourth markers M3 and M4. The touch points TP of the third marker M3 are disposed at each of the four corners of the third marker M3, and the touch points TP of the fourth marker M4 are located on one side of the fourth marker M4. Two touch points TP are disposed at both corners, and two touch points TP are disposed between both corners of one side and the other side facing each other. Therefore, the touch pattern CP formed by the touch points TP of the third marker M3 is a rectangular pattern identical to the shape of the third marker M3, and the touch point TP of the fourth marker M4 The touch pattern CP formed by these has a trapezoidal shape. That is, since the number of touch points TP disposed on the third and fourth markers M3 and M4 is the same, but the shapes of the touch patterns CP are different, the two markers M3 and M4 are designated as different markers. can be recognized. As described above, when there are a plurality of markers M composed of four touch points TP, the touch areas TA of the four touch points TP are formed differently or By combining the location coordinate information, the markers M can be recognized differently.

The fifth marker M5 in (e) of FIG. 6 has five touch points TP, and the touch pattern CP formed by these touch points TP has a pentagonal structure. Accordingly, since the shape of the first to fourth markers M1, M2, M3, and M4 of (a) to (d) and the touch pattern CP are different, they can be distinguished. As described above, when there are a plurality of markers M composed of five touch points TP, the touch areas TA of the five touch points TP are formed differently or By combining the location coordinate information, the markers M can be recognized differently.

As shown in FIG. 7, when the provided content game is a chess game, the multi-cognitive training apparatus 100 using artificial intelligence of the present invention can recognize which tools (words) are used in the chess game. . That is, markers M may be attached to each piece of the chess game, and the number of touch points TP or touch patterns CP consisting of the touch points TP may be attached to the marker M to distinguish each piece. The shape of can be set differently.

A chess game consists of pieces composed of kings, queens, bishops, knights, rooks, and pawns placed on both sides of 64 squares to capture the opponent's king. Therefore, the multi-cognitive training apparatus 100 must be able to recognize the pieces so that the chess game can be played by the player's play. In (a) to (d), markers (M) are attached to the lower side of the king, queen, bishop, and knight used in chess to recognize the type of piece (tool). Three touch points TP are disposed on the marker M attached to the king, and they form a triangular touch pattern CP. Four touch points (TP) are arranged on the marker (M) attached to the queen, and they are formed in the structure of a triangular touch pattern (CP) as shown in (a), but an additional touch point (TP) is placed in the center It can be distinguished from the King's marker (M). As described above, the recognition of the marker M is based on the number of touch points TP, the touch pattern CP formed by the touch points TP, the area (shape) of each touch point TP, and the touch pattern. Since the areas of CP are combined and recognized, even if the number of touch points TP is the same, they can be recognized as different markers M.

8 is a content game, like a mole game, when a player uses a hammer (tool), markers (M) are attached to both edge surfaces of the hammer to distinguish players (Player1, Player2, Player3, Player4). there is.

Three touch points (TP) are arranged on the marker M of the poke hammer of the first player (player1), and four touch points (TP) are placed on the marker M of the poke hammer of the second player (player2). ) is placed, four touch points (TP) are placed on the marker M of the poke hammer of the third player (player3), and five touch points (TP) are placed on the marker M of the poke hammer of the fourth player (player4). A touch point TP is disposed. As described in FIG. 7, each player's hammer has the number of touch points (TP), the touch pattern (CP) formed by the touch points (TP), the area (shape) of each touch point (TP), and It can be recognized by combining information about the area of the touch pattern CP.

In particular, as shown in FIG. 8, since the mole game is progressed by each player holding his or her hammer and touching the display area DA where moles are displayed, information on the touch point TP disposed on the marker M and The motion information of the player acquired by the fourth sensor unit 130d disposed in the multi-cognitive training apparatus 100 may be used together.

That is, the touch point TP is disposed on the marker M disposed on the hammer, and when the marker M of the hammer is brought into contact with the display area DA by the player's motion, the touch point TP including the touch point TP The display unit 308 acquires marker (M) information. In this case, when a plurality of players (player1, player2, player3, and player4) use hammers at the same time, motion information of the players may be additionally considered to obtain more accurate game result information.

For example, if there are balloons to pop or moles to hit in the display area (DA), and they are classified to correspond to each player (player1, player2, player3, player4) (color, shape, etc.) , It is possible to accurately distinguish the hammer (player) that is in contact (touched) with a balloon or mole, so that game progress and game results can be displayed. Therefore, when a plurality of pop hammers contact (touch) a balloon or mole in a specific area, the multi-cognitive training apparatus 100 of the present invention is a fourth sensor unit so that matching between the pop hammer and the balloon or mole can be accurately distinguished. The motion information of the player by (130d) is additionally considered. This will be described in more detail with reference to FIG. 15 .

9 is a diagram for explaining finger touch information and functions in the content game when a user's (player's) finger touch information is used when a content game is played. When a user (player) performs a finger touch (FT) on a character or object of a content game with an index finger as shown in (a), the multi-cognitive training apparatus 100 of the present invention recognizes that the touched character or object is selected and enable the set function.

As in (b), when the first and second finger touches FT1 and FT2 are performed using the index and middle fingers, the multi-cognitive training apparatus 100 of the present invention adjusts the size of the touched character or object in the content game It can be recognized as doing and functioning. As in (c), when the first to third finger touches FT1, FT2, and FT3 are performed with the index, middle, and ring fingers (or thumb, index and middle fingers), the multi-cognitive training apparatus 100 of the present invention is touched It can recognize a character or object as moving and make it function.

As in (d), when the first to fourth finger touches (FT1, FT2, FT3, FT4) are performed using the index finger, middle finger, ring finger, and little finger (or thumb, index finger, middle finger, and ring finger), The multi-cognitive training apparatus 100 may recognize and function as rotating a character or object touched in a content game.

(a) of FIG. 10 recognizes the touch portion touched on the display area DA in the form of positional coordinates, and (b) shows that when touch points TP are arranged like the marker M, the corresponding touch point ( TP) is recognized as one touch ID by specifying numbers ①, ②, and ③, and (c), as described above, the area or shape of the touch point (TP) disposed on the marker (M) It represents the case of doing differently and recognizing the area due to the finger touch (FT) by a person's finger.

When a touch point (TP) or a touch by a finger is input to the display area (DA), the multi-cognitive training apparatus 100 using the artificial intelligence of the present invention for the touch portion is the horizontal axis (X) of the display area (DA). coordinate) and the vertical axis (Y coordinate). Accordingly, the multi-cognitive training apparatus 100 of the present invention recognizes the positional coordinates of the touch portion when a touch input is provided to the display area DA.

Also, in (b), a plurality of markers M having the same number of touch points TP or different numbers of touch points TP in the display area DA or a finger touch FT by a finger is input In this case, information such as a touch pattern (CP) may be obtained by numbering the corresponding touch contact unit as ①, ②, and ③. That is, the touch ID may be set based on the shape, size, and location information of each touch contact unit for the touch pattern CP composed of touch contact units.

In addition, as in (c), based on the touch area TA recognized in the display area DA by the touch points TP disposed on the marker M and the finger touches FT by the fingers An object or the like touched on the display area DA may be identified.

For example, when a marker M where touch points TP are arranged or a finger touch FT by a finger is input through the display area DA, the multi-cognitive training apparatus 100 of the present invention provides each touch contact unit Recognizes the positional coordinates (x, y) for When a plurality of users play a content game, many touch contact units (touch points or finger touches, etc.) are recognized in the display area DA, and it is necessary to filter only valid touch information among such touch information. Marker information by the touch points TP of the marker M or function information by a finger are set in advance and stored. Thereafter, when touch inputs are provided to the display area DA, it is necessary to extract only valid information from a lot of touch information touched on the display area DA.

11 is a diagram showing possible touch patterns CP estimated from touch contact units TC input to the display area DA, and FIG. 12 shows touch information such as the touch contact unit TC. 13 is a diagram showing a touch ID corresponding to , and FIG. 13 is a diagram in which a function corresponding to a touch ID is applied to a content game played in the display area DA.

Referring to FIGS. 11 to 13 , in the display area DA, a tool used for a content game, a player's (user's) marker M, and player's finger touch information may be input. Therefore, as shown in FIG. 11 , a large number of touch contact units TC can be recognized in the display area DA, and a plurality of touch patterns CP formed of these touch contact units TC are provided. can appear As shown in the drawing, when 16 touch contact units TC are recognized in the display area DA, touch patterns CP that can be recognized as 16 touch contact units TC are first to eleventh. These are the touch patterns (P1 to P11).

However, since the first to eleventh touch patterns P1 to P11 do not all provide content game, player's finger touch, or player's marker M information, it is necessary to select valid touch patterns among these touch patterns. there is.

As shown in FIG. 12, the multi-cognitive training apparatus 100 using artificial intelligence of the present invention uses the touch pattern CP composed of the touch contact units TC shown in (a) to (d) as a touch ID. It is saved in the form (ID11, ID21, ID23, ID105). As described above, the touch ID information includes not only the shape of the touch pattern CP composed of the touch contact units TC, but also information on the areas of each touch contact unit TC, the direction of the touch contact unit TC, Area information of the touch pattern CP is combined and stored as one touch ID information.

Therefore, as shown in FIG. 11 , when a plurality of touch contact units TC are input to the display area DA, the first to eleventh touch patterns P1 to P11 made of these touch contact units TC are recognized. Then, the recognized first to eleventh touch patterns P1 to P11 are compared with pre-stored touch ID information to select only information valid for the currently provided content game.

As shown in FIG. 13, among the first to eleventh touch patterns P1 to P11 recognized in FIG. 11, the first touch pattern P1: ID11, the fourth touch pattern P4: ID23, and the eleventh touch pattern It can be seen that only (P11: ID21) and the seventh touch pattern (P7: ID105) are matched with information pre-stored in the multi-cognitive training apparatus 100. The seventh touch pattern P7 matches the touch pattern of the pre-stored information, but does not function on the display area DA if the touch pattern is not currently used in the content game.

The first touch pattern (P1: ID11) instructs a character (person) and performs a function of moving in the direction where it is located, and the fourth touch pattern (P4: ID23) controls the movement speed of an object within a range in a content game. It performs the function of doubling, the 11th touch pattern (P11: ID21) performs the function of instructing the vehicle and moving in the direction in which it is located, and the 7th touch pattern (P7: ID105) is currently being executed. In the content game being played, there are no registered objects or function data.

Accordingly, as shown in FIG. 13 , among the first to eleventh touch patterns P1 to P11 displayed on the display area DA, the first touch pattern P1: ID11 and the fourth touch pattern P4: ID23 ) and the 11th touch pattern (P11: ID21) only works in the content game.

As such, the content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention provides various cognitive training and cognitive stimulation such as visual, auditory, and physical movements to dementia patients or patients with low cognitive abilities. There are effects that can be done.

In addition, the content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention can provide cognitive training and cognitive stimulation in a manner in which a plurality of dementia patients or patients with low cognitive abilities cooperate at the same time It works.

In addition, the content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention analyzes various touch patterns input to the display area while players play the content game through a learning model based on deep learning. After that, there is an effect of accurately recognizing an object or a player inputting a touch pattern.

In addition, a content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention provides touch input in the content game based on the motion of the player playing the content game and patterns input to the display area It has the effect of distinguishing players.

14 is a block diagram showing a specific configuration of a recognition unit of a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention. 15 is a specific block diagram of a judgment unit of a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention. 16 is a diagram for explaining how a multi-cognitive training apparatus using artificial intelligence according to an embodiment of the present invention recognizes a plurality of players.

14 and 15 together with FIGS. 2 and 3, the multi-cognitive training apparatus 100 using artificial intelligence of the present invention includes first to fourth sensor units 130a, 130b, 130c, and 130d, an input unit 301, a storage unit 302, a drive unit 303, a content providing unit 304, a control unit 305, a recognizing unit 306, a determination unit 307, and a display unit 308. The recognition unit 306 recognizes and analyzes touch information input through the display unit 308 to recognize a pattern recognition unit 306a, a pattern analysis unit 306b, a pattern database 306c (Pattern Data Base), It includes an object recognition unit 306d and an object database 306e (Object Data Base).

As described above, the storage unit 302 disposed in the multi-cognitive training apparatus 100 of the present invention is the touch patterns CP composed of the touch patterns CP of the markers M and the finger touch by the user's finger ) is stored. When the touch information by the player's (user's) finger touch and the marker's (M's) touch points (TP) are input through the display area (DA) of the display unit (308), the pattern recognition unit ( 306a).

As described in FIG. 11, touch information is generated in the form of a plurality of touch contact units TC in the display area DA by the touch provided by the touch points TP disposed on the marker M and the player's finger. is entered

The pattern analyzer 306b analyzes the touch patterns CP formed by the touch contact units TC based on touch information determined as an effective touch area. That is, based on the pattern information stored in the pattern DB 306c, the touch patterns CPs by the touch contact units TC input to the display area DA are touch patterns indicating objects or specific functions (effects). It analyzes whether it is a touch pattern that implements . The pattern DB 306c is shown as a configuration of the recognition unit 306a, but may be implemented as a part of the storage unit 302 of the multi-cognitive training apparatus 100.

After the pattern analyzer 306b analyzes the touch patterns CP of the touch contact units TC input to the display area DA, the results are provided to the object recognizer 306d. The object recognizer 306d recognizes which object or specific function the touch patterns CP analyzed by the pattern analyzer 306b are associated with. The object recognizing unit 306d compares the touch pattern CP provided from the pattern analyzing unit 306b based on object information (including specific effect and function information corresponding to the touch pattern) stored in the object database 306e. . That is, in the object database 306e, characters active in each content game, information on specific effects and functions that can be performed in the game, and touch patterns (CPs) are listed in the form of a lookup table. Accordingly, a character having the same touch pattern CP or a specific effect or function in a game may be matched to the touch patterns CP analyzed by the pattern analyzer 306b. At this time, the object recognition unit 306d may receive content information and recognize an object or a specific function currently used in the content game.

In addition, the object recognition unit 306d receives each content game information stored in the storage unit 302 and recognizes it as a touch pattern (CP), but determines whether or not the touch pattern is valid (used) in relation to the current content game. can be filtered. For example, if the pattern analysis unit 306b analyzes the touch pattern (CP), but is not currently used in the content game provided to the user or a specific effect (function), the object recognition unit 306d will filter it out. can

When the object recognition unit 306d matches the touch pattern CP and the object (or the specific effect of the game), the determination unit 307 may finally determine the touch information input to the display area DA. . For example, although it is recognized as a touch pattern (CP), it may be matched whether it is touch information by a player's finger, not an object (tool).

The determination unit 307 of the multi-cognitive training apparatus 100 of the present invention determines which player inputs touch information to the display area DA when a plurality of players play a content game on the display unit 100a. It may be determined whether it is touch information.

The determination unit 307 includes an image separation unit 416 that separates the images captured by the second sensor unit 130b and the fourth sensor unit 130d into an image centered on the player's face and an image centered on the player's motion. , a face image conversion unit 417 and a motion image conversion unit that converts the face image and motion image separated by the image separation unit 416 into an image that can be extracted using a learning model 420 based on deep learning ( 418), a pattern image converting unit 419 that converts touch information input to the display unit (a touch contact unit contacted by a tool or a touch point of a finger), a face image converting unit 417, and a motion image converting unit ( 418) and the learning model 420 built by machine learning to extract images for each player based on the converted image output from the pattern image conversion unit 419, the player (face), the player's motion (movement), and the player A separation extraction unit 421 that extracts an image of an object (tool: touch information input to the display unit) used by the player, and a location information providing unit 424 in which location information of players provided from the first sensor unit 130a is stored. , an inspection unit 422 that inspects which player the touch information is based on the images extracted from the separation extraction unit 421 and the location information of the players provided from the location information providing unit 424, and the inspection unit ( 422), when the touch information and the players are matched, a decision unit 423 is included to finally determine which player is the touch input for the touch information input for each position of the display area DA.

Here, the facial image conversion unit 417, the motion image conversion unit 418, and the pattern image conversion unit 419 are used to perform machine learning on the image captured by the sensor unit and the touch information input to the surface area. proceed with the conversion.

As shown in FIG. 16, when four players (player1, player2, player3, player4) play the content game provided by the multi-cognitive training device 100, each player uses a hammer to display the unit. The method of inputting touch information to the touch panel of (100a) may be performed. Although the drawing shows using a tool (object), this is not fixed. Accordingly, touch information may be input by a finger touch of each player's finger or by using another tool.

Among the bubbles displayed on the display area, when each player needs to pop their own bubble, the player touches the display area where the bubble is displayed using a hammer (tool). However, if multiple players input touch information at the same time, or if a bubble to be touched by a player is close to an adjacent player's bubble, or if a specific area is hit with a hammer at the same time, which player's touch information touches the bubble first It is necessary to accurately determine whether

To this end, the multi-cognitive training apparatus 100 of the present invention may use the learning model 420 built by machine learning. For machine learning of the learning model 420, not only a neural network but also a machine learning algorithm such as a decision tree, a Bayesian network, or a support vector machine (SVM) may be used.

For example, it may include neural networks having fully connected layers such as Mask-RCNN (Mask Recurrent Convolutional Neural Network). Accordingly, the neural network constituting the learning model 372 may include a feature pyramid network (FPN), a core neural network (Resnet), and a region proposal network.

The learning model 420 includes touch information input on the display area DA by players playing the content game provided by the multi-cognitive training device 100, touch information by a marker M or a finger, and It can be built by deep learning based on motion (movement) images of multiple players.

The recognition unit 306 analyzes whether the touch information input to the display area DA constitutes the touch pattern CP, and recognizes whether the analyzed touch pattern CP is an object (tool) or a player's finger. Also, the object recognizer 306d may recognize whether the touch pattern CP is a function used in a content game. In this way, the recognized touch pattern CP is finally determined by the determination unit 307 and controlled by the control unit 305 .

Also, when a plurality of players play a content game, the determination unit 307 may recognize and determine touch information input by each player. The determination unit 307 separates the player image provided from the second sensor unit 130b and the fourth sensor unit 130d into a player's face image and a player's motion image; converting the separated player's face image and motion image into an image capable of machine learning by a learning model 372; converting touch information input to the display area DA into an image capable of machine learning by a learning model 372; performing machine learning on the converted face image, motion image, and touch information image by the learning model 372; Extracting related images (face images, motion images, and corresponding touch information images) for each player with respect to the images subjected to machine learning by the learning model 372; inspecting players corresponding to each touch information based on the extracted image and the location information of the players provided by the first sensor unit 130a; and determining a player for each touch information.

As described above, the players corresponding to the plurality of pieces of touch information input to the display area DA are positioned by the first sensor unit 130a disposed along the circumference of the side of the display unit 100a. It can be determined whether it is located on the left and right sides or up and down (front and rear) of (100a). In addition, when one of the players located on the left and right or up and down uses a hammer (tool) to burst the bubble in the opposite area, the player who burst the bubble is located closer to the display unit 100a than the player located on the opposite side. .

If the distance between a pair of players located on the left and right sides or up and down and the display unit 100a is similar, the player's face image and the player's motion captured by the second sensor unit 130b and the fourth sensor unit 130d The player may be determined by additionally considering the video.

In addition, when at least one touch information is input to a specific area of the display area DA (for example, when a plurality of players touch a specific area with their hammers), the touch input to the display area DA It can be determined by considering the touch time of the information, the player's face, motion image, and the player's location information.

As such, the content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention provides various cognitive training and cognitive stimulation such as visual, auditory, and physical movements to dementia patients or patients with low cognitive abilities. There are effects that can be done.

In addition, the content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention can provide cognitive training and cognitive stimulation in a manner in which a plurality of dementia patients or patients with low cognitive abilities cooperate at the same time It works.

In addition, the content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention analyzes various touch patterns input to the display area while players play the content game through a learning model based on deep learning. After that, there is an effect of accurately recognizing an object or a player inputting a touch pattern.

In addition, a content game-based cognitive training device and method for multiple players using artificial intelligence according to the present invention provides touch input in the content game based on the motion of the player playing the content game and patterns input to the display area It has the effect of distinguishing players.

Embodiments according to the present invention described above may be implemented in the form of program instructions that can be executed through various computer components and recorded on a computer-readable recording medium. The computer readable recording medium may include program instructions, data files, data structures, etc. alone or in combination. Program instructions recorded on the computer-readable recording medium may be specially designed and configured for the present invention, or may be known and usable to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical recording media such as CD-ROMs and DVDs, and magneto-optical media such as floptical disks. medium), and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter or the like as well as machine language codes generated by a compiler. A hardware device may be modified with one or more software modules to perform processing according to the present invention and vice versa.

Specific implementations described in the present invention are examples and do not limit the scope of the present invention in any way. For brevity of the specification, description of conventional electronic components, control systems, software, and other functional aspects of the systems may be omitted. In addition, the connection of lines or connecting members between the components shown in the drawings are examples of functional connections and / or physical or circuit connections, which can be replaced in actual devices or additional various functional connections, physical connection, or circuit connections. In addition, if there is no specific reference such as “essential” or “important”, it may not be a component necessarily required for the application of the present invention.

In addition, the detailed description of the present invention described has been described with reference to preferred embodiments of the present invention, but those skilled in the art or those having ordinary knowledge in the art will find the spirit of the present invention described in the claims to be described later. And it will be understood that the present invention can be variously modified and changed without departing from the technical scope. Therefore, the technical scope of the present invention is not limited to the contents described in the detailed description of the specification, but should be defined by the claims.

100: multi-cognitive training device
100a: display unit
100b: base unit
120: first support
121: second support
123: means of transportation
130a: first sensor unit
130b: second sensor unit
130c: third sensor unit
130d: fourth sensor unit
301: input unit
302: storage unit
303: driving unit
304: content provision unit
305: control unit
306: recognition unit
307: judgment unit
308: display unit
TP: touch point
TA: touch area
CP: Touch pattern
TD: direction of touchpoint

Claims (11)

a display unit that displays a content game and senses a touch input for the content game; and
Includes a management system for controlling the display unit,
The management system,
a display unit that receives the sensed touch input and controls the display unit to display the content game;
a storage unit for storing information about the content game and information about a user playing the content game;
a recognition unit recognizing a touch pattern for a touch input received from the display unit;
a determination unit determining object information corresponding to the touch pattern recognized by the recognition unit; and
A control unit for determining a specific input for the content game or a subject of the touch input according to the object information determined by the determination unit;
The display unit senses a touch input according to at least one touch point attached to the marker,
The recognizing unit recognizes a touch pattern according to at least one parameter among the size, shape, location, and number of the touch points;
The determination unit determines a user or a tool for the marker as object information according to the touch pattern of the recognized touch point.
A cognitive training device based on content games for multiple players. delete According to claim 1,
The control unit determines the user for the marker determined by the determination unit among the plurality of users playing the content game as the user who is the subject of the touch input.
A cognitive training device based on content games for multiple players. According to claim 1,
The control unit controls to proceed with the content game based on a tool for the marker determined by the determination unit among a plurality of tools for playing the content game.
A cognitive training device based on content games for multiple players. According to claim 4,
The storage unit stores information on touch points of markers matched by a plurality of tool types as a list,
The determination unit detects a touch point of a marker that matches the recognized touch pattern, determines a tool matched to the detected touch point of the marker,
The control unit proceeds with the content game based on the determined tool being disposed at the touch input location.
A cognitive training device based on content games for multiple players. According to claim 5,
The content game is a chess game,
The storage unit stores information on touch points for markers disposed below each type of chess piece in a list,
The determination unit detects touch point information matched to the recognized touch pattern from the list;
The control unit determines that the type of chess piece matched with the detected touch point is disposed at a position corresponding to the touch input and controls the chess game to proceed.
A cognitive training device based on content games for multiple players. According to claim 1,
The control unit controls to display one content game on the entire display area of the display unit;
The display unit receives a touch input for the content game,
The determination unit determines a user for the touch input.
A cognitive training device based on content games for multiple players. a display unit that displays a content game and senses a touch input for the content game; and
Includes a management system for controlling the display unit,
The management system,
a display unit that receives the sensed touch input and controls the display unit to display the content game;
a storage unit for storing information about the content game and information about a user playing the content game;
a recognition unit recognizing a touch pattern for a touch input received from the display unit;
a determination unit determining object information corresponding to the touch pattern recognized by the recognition unit; and
A control unit for determining a specific input for the content game or a subject of the touch input according to the object information determined by the determination unit;
The content game is a game played by touch input with each tool given to a plurality of users,
Different markers are disposed on each tool of the plurality of users,
The determination unit determines tool information having a marker according to a touch pattern of the touch input;
The control unit determines the user having the tool information as the subject of the touch input and controls the content game to proceed.
A cognitive training device based on content games for multiple players. A content game-based cognitive training method for multiple players provided by a multi-cognitive training device including a display unit that displays a content game and detects a touch input for the content game, and a management system that controls the display unit. ,
controlling the display unit to display the content game;
Receiving a touch input for the displayed content game;
Recognizing a touch pattern for a touch input received from a display unit;
determining object information corresponding to the recognized touch pattern from a pre-stored list; and
Determining a specific input for the content game or a subject of the touch input according to the determined object information and proceeding with the content game;
The step of determining object information corresponding to the recognized touch pattern from a pre-stored list,
Detecting a touch point of a marker that matches the recognized touch pattern, and determining a tool matched to the detected touch point of the marker.
Content game-based cognitive training method for multiple players. delete A content game-based cognitive training method for multiple players provided by a multi-cognitive training device including a display unit that displays a content game and detects a touch input for the content game, and a management system that controls the display unit. ,
controlling the display unit to display the content game;
Receiving a touch input for the displayed content game;
Recognizing a touch pattern for a touch input received from a display unit;
determining object information corresponding to the recognized touch pattern from a pre-stored list; and
Determining a specific input for the content game or a subject of the touch input according to the determined object information and proceeding with the content game;
Controlling the display unit to display the content game may include controlling the display unit to display one content game on the entire display area of the display unit, and receiving touch inputs for the content game from a plurality of users. including the steps of
The step of determining object information corresponding to the recognized touch pattern from a pre-stored list,
Determining a user for a touch input received for the content game from among the plurality of users
A cognitive training method based on content games for multiple players.