Exercise ability evaluation system, exercise ability development system, exercise ability evaluation method, and exercise ability evaluation program

Abstract

A finger motion instruction unit P1a instructs a target person T to perform a finger motion. A body motion instruction unit P2a instructs the target person T to perform a body motion. A motion detection device 20 detects the finger motion and the body motion of the target person T. A fine exercise evaluation unit P1b evaluates the finger motion instructed by the finger motion instruction unit P1a on the basis of a detection signal acquired by detecting the motion of the target person T by means of the motion detection device 20. A rough exercise evaluation unit P2b evaluates the body motion instructed by the body motion instruction unit P2a on the basis of the detection signal.

Description

Athletic ability evaluation system, athletic ability development system, athletic ability evaluation method, and athletic ability evaluation program

[0001] The present invention relates to an athletic ability evaluation system, an athletic ability development system, an athletic ability evaluation method, and an athletic ability evaluation program.

[0002] It has been known that human motor skills are related to brain function, and a motion learning technique is known in which motion learning is performed in a virtual space in order to activate brain functions related to motor skills.

[0003] For example, Japanese Patent Publication No. 2000-504854 discloses a motion learning technology in which, while the student is exercising, a virtual image sequence of the student's body part or tool being used is displayed on a display device in response to the movement of the student's body part or tool being used, and simultaneously a virtual image sequence of the teacher's body part or tool being used is displayed on a display device in response to the movement of the teacher's body part or tool being used, and the student moves the virtual image sequence of the student's body part or tool being used to imitate the virtual image sequence of the teacher's body part or tool being used.

[0004] However, conventional motion learning techniques only deal with partial movements, such as movements using a part of the body or a specific tool, making it difficult to efficiently develop motor skills that take into account the overall movement of the body. Furthermore, with conventional motion learning techniques, it is difficult for subjects to maintain their motivation to continue learning, especially when they do not achieve learning benefits, making it difficult to efficiently develop motor skills based on continuous learning.

[0005] Therefore, an embodiment of the present invention aims to provide an athletic ability evaluation system, an athletic ability development system, an athletic ability evaluation method, and an athletic ability evaluation program that can more efficiently improve a subject's athletic ability using an avatar displayed in a virtual space.

[0006] A motor ability evaluation system according to an embodiment includes a finger movement instruction unit, a body movement instruction unit, a movement detection device, a fine movement evaluation unit, and a gross movement evaluation unit. The finger movement instruction unit instructs a subject to perform a finger movement. The body movement instruction unit instructs the subject to perform a body movement. The movement detection device detects the finger movement and the body movement of the subject. The fine movement evaluation unit evaluates the finger movement instructed by the finger movement instruction unit based on a detection signal obtained by detecting the subject's movement using the movement detection device. The gross movement evaluation unit evaluates the body movement instructed by the body movement instruction unit based on the detection signal.

[0007] The motor skill development system according to the embodiment further includes an object display unit, a self-operated avatar display unit, and a teaching avatar display unit. The object display unit displays a movable and / or deformable object in a virtual space. The self-operated avatar display unit displays a self-operated avatar operated by the subject, which performs an action based on the detection signal and is capable of moving and / or deforming the object in the virtual space. The teaching avatar display unit acquires teaching action information for the object from a storage unit and displays a teaching avatar that performs a teaching action based on the teaching action information. The object to be displayed is determined based on the fine motor difficulty and gross motor difficulty determined by the motor skill evaluation system, and the object's movement or deformation is adjusted, or the teaching action information is selected.

[0008] In the motor ability evaluation method according to the embodiment, a finger movement instruction unit instructs a subject to perform a finger movement, a physical movement instruction unit instructs the subject to perform a physical movement, a movement detection device detects the finger movements and physical movements of the subject, a fine motor evaluation unit evaluates the finger movements instructed by the finger movement instruction unit based on a detection signal obtained by detecting the subject's movement using the movement detection device, and a gross motor evaluation unit evaluates the physical movement instructed by the physical movement instruction unit based on the detection signal.

[0009] The motor ability evaluation program according to the embodiment includes code for causing a computer to execute processing by a finger movement instruction unit that instructs a subject to perform a finger movement, code for causing a computer to execute processing by a physical movement instruction unit that instructs the subject to perform a physical movement, code for causing a computer to execute processing by a movement detection device that detects the subject's finger movements and the physical movement, code for causing a computer to execute processing by a fine motor evaluation unit that evaluates the finger movements instructed by the finger movement instruction unit based on a detection signal obtained by detecting the subject's movement using the movement detection device, and code for causing a computer to execute processing by a gross motor evaluation unit that evaluates the physical movement instructed by the physical movement instruction unit based on the detection signal.

[0010] FIG. 1 is an explanatory diagram illustrating an example of the external configuration of an athletic ability development system according to an embodiment. FIG. 2 is a block diagram illustrating an example of the internal configuration of the athletic ability development system according to an embodiment. FIG. 3 is a block diagram illustrating an example of functional blocks of the athletic ability development system according to an embodiment. FIG. 4 is an explanatory diagram illustrating an example of a finger opening and closing exercise instruction image with a left-hand self-operated avatar displayed by a finger motion instruction unit in an athletic ability evaluation system included in the athletic ability development system according to an embodiment. FIG. 5A is an explanatory diagram illustrating an example of a target image generated by an app displayed by a finger motion instruction unit in an athletic ability evaluation system included in the athletic ability development system according to an embodiment. FIG. 5B is an explanatory diagram illustrating an example of a path image generated by an app displayed by a finger motion instruction unit in an athletic ability evaluation system included in the athletic ability development system according to an embodiment. FIG. 6 is an explanatory diagram illustrating an example of a balance image of a subject displayed by a body motion instruction unit in an athletic ability evaluation system included in the athletic ability development system according to an embodiment. FIG. 7 is an explanatory diagram illustrating an example of a breakout image in an athletic ability development system according to an embodiment. FIG. 8 is an explanatory diagram illustrating an example of a usage state of the athletic ability development system according to an embodiment. Fig. 9 is an explanatory diagram illustrating an example of a skilled movement learning image in the athletic ability development system according to the embodiment. Fig. 10 is a flowchart showing an example of the flow of a skilled movement learning process in the athletic ability development system according to the embodiment. Fig. 11 is a diagram showing measurement results of blood flow in the dorsolateral prefrontal cortex in the athletic ability development system according to the embodiment. Fig. 12 is a diagram showing measurement results of motor evoked potentials during ball catching training using a controller and a glove-type sensor in the athletic ability development system according to the embodiment.

[0011] Hereinafter, the configuration of an athletic ability development system 1 according to an embodiment will be described with reference to the drawings.

[0012] Fig. 1 is an explanatory diagram illustrating an example of the external configuration of the athletic ability development system 1. Fig. 2 is a block diagram illustrating an example of the internal configuration. Fig. 3 is a block diagram illustrating an example of functional blocks.

[0013] The motor ability development system 1 according to the embodiment is used for developing the motor ability of a subject T. The subject T of the motor ability development system 1 is a person who wishes to improve his or her motor ability. In particular, the subject T may be a person with developmental coordination disorder (DCD), for which motor ability development is recognized to be effective in improving symptoms. The subject T may also be a child whose score is below the 15th percentile on the Movement Assessment Battery for Children - Second Edition (MABC-2). In this case, the age of the subject T is preferably 6 years old or older and 12 years old or younger, but the subject T is not limited to this.

[0014] 1 and 2 , the athletic ability development system 1 includes a display device 10, a motion detection device 20, and a control device 30. The athletic ability development system 1 includes an athletic ability evaluation system 2.

[0015] The display device 10 has an LCD, an OLED, or the like, and displays an image input from the control device 30 .

[0016] The motion detection device 20 detects the finger motions and body motions of the subject T, acquires a detection signal, and transmits the detection signal to the control device 30. The motion detection device 20 has a finger motion detection device 21, a touch panel 22, a body motion detection device 23, and a camera 24.

[0017] The finger movement detection device 21 detects the movement of the fingers of the subject T and transmits a finger detection signal. The finger movement detection device 21 is a glove-type sensor that can detect the movement of the fingers of the subject T, for example, based on finger bending information acquired from bending sensors attached to the fingers and joints, and hand position information calculated by receiving electromagnetic waves such as infrared rays emitted from a base station at a predetermined position using a marker attached to the back of the hand. An example of a glove-type sensor is ContactGlove from Diver-X Corporation (Chiyoda-ku, Tokyo).

[0018] The touch panel 22 may be integrated with the display device 10, may be an independent terminal such as a tablet terminal or a smartphone, or may be integrated with the control device 30. When there is a touch input on the touch panel 22 with the fingers of the subject T, a finger detection signal is output to the control device 30.

[0019] The body movement detection device 23 detects the body movement of the subject T and transmits a body detection signal. The body movement detection device 23 is, for example, a motion capture device that can detect the body movement of the subject T based on position information of each body part calculated by receiving electromagnetic waves transmitted from a base station at a predetermined position using markers attached to each body part. An example of a motion capture device is MOCOPI (registered trademark) from Sony Group Corporation.

[0020] The camera 24 captures an image of the subject T's body and transmits the captured image as a body detection signal. Note that either the finger motion detection device 21 or the body motion detection device 23 or the camera 24 may be used alone, and fine motor assessment and gross motor assessment may be performed based on the body detection signal acquired by either one. An example of a system that can obtain a body detection signal using only the camera 24 is the Ultraleap 3Di (Ultraleap Corporation).

[0021] Examples of the control device 30 include an information processing terminal such as a PC, a tablet terminal, and a smartphone. The control device 30 has an input / output interface 31, a CPU 32, and a storage unit 33. The input / output interface 31, the CPU 32, and the storage unit 33 are connected to each other via a bus.

[0022] The input / output interface 31 is connected to the display device 10 and the motion detection device 20 .

[0023] The CPU 32 is capable of executing various types of arithmetic processing. The control device 30 realizes its functions by the CPU 32 executing a program read from the storage unit 33.

[0024] The memory unit 33 has a ROM, RAM, HDD, SSD, etc., and stores various programs that control the motor skill development system 1 and data used by the various programs, as well as programs for motor skill evaluation processing and motor skill development processing, such as a finger movement instruction unit P1a, a fine motor evaluation unit P1b, a body movement instruction unit P2a, a gross motor evaluation unit P2b, a difficulty determination unit P3, an object display unit P4, a teaching avatar display unit P5, a self-operation avatar display unit P6, a distance calculation unit P7, a feedback stimulus determination unit P8, a feedback stimulus application unit P9, a coincidence calculation unit P10, an avatar replacement unit P11, and an average avatar display unit P12, as shown in FIG. 3.

[0025] First, the athletic ability evaluation process in the athletic ability evaluation system 2 included in the athletic ability development system 1 will be described.

[0026] FIG. 4 is an explanatory diagram illustrating an example of a finger opening / closing exercise instruction image G1 on which a self-operated avatar At of the left hand is arranged, displayed by the finger action instruction unit P1a.

[0027] As shown in FIG. 4 , the finger movement instruction unit P1a instructs the subject T to perform a finger movement. More specifically, based on a finger detection signal acquired from the finger movement detection device 21, the finger movement instruction unit P1a displays a finger opening / closing instruction image G1 having an avatar of one hand on the display device 10 and instructs the subject T to continuously perform a finger opening / closing movement, which is a movement of opening and closing the fingers, for a predetermined period of time. The fine motor evaluation unit P1b evaluates the finger movement instructed by the finger movement instruction unit P1a based on a detection signal acquired by detecting the subject T's movement using the movement detection device 20, and outputs a fine motor evaluation value indicating the fine motor ability of the subject T. As a specific example, the fine motor evaluation unit P1b acquires finger bending information from the finger detection signal acquired by detecting the subject T's movement using the finger movement detection device 21, counts the number of times the subject T was able to perform a finger opening / closing movement within a predetermined period of time, and outputs a fine motor evaluation value corresponding to the number of times, counting a bending degree equal to or greater than a threshold as one time.

[0028] Fig. 5A is an explanatory diagram illustrating an example of a target image G2, and Fig. 5B is an explanatory diagram illustrating an example of a route image G3.

[0029] The finger movement instruction unit P1a may instruct the subject T to perform a finger movement using an app. More specifically, as shown in FIG. 5A , the finger movement instruction unit P1a displays multiple concentric small circles within a large circle and instructs the subject T to tap the center of the target image G2 with his or her fingers a predetermined number of times at predetermined time intervals, such as 10 times at a pace of once per second. The finger movement instruction unit P1a may be provided with a pacing function that makes the subject T aware of the tapping once per second, such as by using sound or light. The fine motor evaluation unit P1b detects the subject T's movement using the touch panel 22 and acquires a finger detection signal, and scores the tap position based on the distance from the center, such as 10 points, 9 points, 8 points, ..., 0 points, and outputs a fine motor evaluation value based on the total score.

[0030] 5B , the finger movement instruction unit P1a may, for example, display a path image G3 having a meandering path U with a predetermined width and instruct the subject T to slide his / her fingers along the path U from the start to the goal. The fine motor evaluation unit P1b calculates and outputs a fine motor evaluation value based on a finger detection signal obtained by detecting the movement of the subject T using the touch panel 22, depending on whether the subject T's fingers were able to slide correctly along the path U. More specifically, the fine motor evaluation value may be output by counting the number of errors in which the subject T's fingers deviate from the path U.

[0031] As another method for evaluating fine motor skills, the subject T may be instructed to perform opposing movements between the thumb and another finger, and the fine motor skill evaluation value may be calculated from the number of times the movement is performed per unit time and the number of errors.

[0032] FIG. 6 is an explanatory diagram illustrating an example of a balance image G4 of the subject T displayed by the body movement instruction unit P2a.

[0033] As shown in FIG. 6 , the physical movement instruction unit P2a instructs the subject T to perform physical movements. More specifically, the physical movement instruction unit P2a generates a balance image G4 of the subject T based on the body detection signal acquired from the camera 24, displays it on the display device 10, and instructs the subject T to stand on one leg with both arms outstretched. For example, the physical movement instruction unit P2a superimposes a bird R1 object on the body image of the subject T displayed in the balance image G4 at the position of the forearm when both arms are spread horizontally, instructing the subject T to spread both arms. The physical movement instruction unit P2a also superimposes an animal R2 object, such as a hedgehog, on the position of one foot of the body image of the subject T and instructs the subject T to lift one foot without stepping on the animal R2. The gross motor skill evaluation unit P2b evaluates the physical movements instructed by the physical movement instruction unit P2a based on the detection signal and outputs a gross motor skill evaluation value indicating the subject T's gross motor ability. More specifically, the physical movement instruction unit P2a instructs the subject T to stand on one leg with both arms outstretched, and the gross motor skill evaluation unit P2b acquires posture information Sb based on the body detection signal, and evaluates the subject T as follows: if the arm angle is 0 degrees or more but less than 15 degrees downward when the horizontal direction is 0 degrees, 1 point is added; if it is 15 degrees or more but less than 30 degrees, 0 point is added; if it is 30 degrees or more but less than 180 degrees, 1 point is subtracted; and if the subject T is able to stand on one leg, 3 points are added; and a gross motor skill evaluation value indicating the subject T's gross motor ability is calculated and output.

[0034] The difficulty level determination unit P3 determines the difficulty level of fine motor exercises to be presented to the subject T based on the fine motor evaluation value evaluated by the fine motor evaluation unit P1b, and determines the difficulty level of gross motor exercises to be presented to the subject T based on the gross motor evaluation value evaluated by the gross motor evaluation unit P2b. This allows the motor skill development system 1 to determine appropriate fine motor and gross motor difficulties tailored to the subject T's fine motor and gross motor abilities, thereby making motor skill development more efficient. For example, for a subject T who is poor at fine motor skills, the motor skill development system 1 can present less difficult fine motor exercises, lowering the hurdle for goal achievement and contributing to maintaining the subject T's motivation for motor learning. Furthermore, for a subject T with a high gross motor evaluation value, the motor skill development system 1 can present more difficult gross motor exercises, leading to the achievement of more advanced tasks and contributing to maintaining the subject T's motivation for motor learning.

[0035] Note that the physical movement instruction given to the subject T by the physical movement instruction unit P2a is not limited to standing on one leg. For example, the physical movement instruction unit P2a may instruct the subject T to walk on a line, and the gross movement evaluation unit P2b may evaluate the walking on the line and output a gross movement evaluation value, or the physical movement instruction unit P2a may instruct the subject T to jump, and the gross movement evaluation unit P2b may evaluate the subject T's jump and output a gross movement evaluation value.

[0036] In the above description, the finger motion detection device 21 is a glove-type sensor and the body motion detection device 23 is a motion capture device in the motion detection device 20. However, the present invention is not limited to this. The motion detection device 20 may be any type of optical, inertial sensor, mechanical, magnetic, or video type that can detect motion.

[0037] In the above description, the display device 10 has an LCD and an OLED, but is not limited to this and may be a projector, a head-mounted display, or the like.

[0038] Next, the athletic ability development process will be described.

[0039] FIG. 7 is an explanatory diagram illustrating an example of a block-breaking image G5.

[0040] In the athletic ability development process, ability development is carried out by the subject T operating a self-operated avatar At in a virtual space.

[0041] 7, the object display unit P4 displays a movable and / or deformable object on a block-breaking image G5 displayed as a virtual space. The object is, for example, a movable ball B.

[0042] The teaching avatar display unit P5 acquires teaching action information for the object from the storage unit 33, and displays a teaching avatar Ae that performs a teaching action based on the teaching action information.

[0043] The teaching movement information is generated in advance based on movements by an expert such as a teacher or coach, and is stored in the storage unit 33. It is preferable to prepare a plurality of pieces of teaching movement information so that an appropriate piece of information can be selected depending on the gross motor evaluation value and fine motor evaluation value of the subject T. It is also preferable that the movement speed, etc., can be adjusted depending on the gross motor evaluation value and fine motor evaluation value. Furthermore, the teaching avatar Ae may show an example movement once or multiple times depending on the gross motor evaluation value and fine motor evaluation value of the subject T.

[0044] The self-operated avatar display unit P6 displays a self-operated avatar At operated by the subject T in the virtual space. The self-operated avatar At operates based on a detection signal and is capable of moving and / or transforming objects. More specifically, in the example of the breakout image G5 in FIG. 7 , the self-operated avatar At is an avatar for both hands of the subject T, and operates based on a detection signal detected from both hands of the subject T by the motion detection device 20, and is capable of throwing a ball B toward a wall, breaking down blocks placed in front of the wall, and catching the ball B that bounces back.

[0045] It is preferable to display the teaching avatar Ae before the subject T makes a movement. For example, when the subject T grasps the ball B with the self-controlled avatar At, the movement of the teaching avatar Ae is displayed in the virtual space, and after the movement is completed, the subject T is permitted to make a movement in the virtual space. By referring to the movement of the teaching avatar Ae, the subject T is encouraged to predict how to effectively break down blocks by throwing the ball B, the direction in which the ball B will bounce, and the like, thereby activating brain function.

[0046] (Feedback Processing) The distance calculation unit P7 calculates the distance between the self-operated avatar At and the teaching avatar Ae. The closer the calculated distance, the more the subject T's self-operated avatar At is moving in a manner that matches the teaching avatar Ae, and the farther the calculated distance, the more the subject T's self-operated avatar At is moving in a manner that deviates from the teaching avatar Ae.

[0047] The feedback stimulus determination unit P8 determines the stimulus to be applied to the subject T by the feedback stimulus application unit P9 according to the distance calculated by the distance calculation unit P7.

[0048] When the distance is greater than a predetermined distance, the feedback stimulus determination unit P8 causes the feedback stimulus providing unit P9 to provide a stimulus to the subject T, and notifies the subject T that the action performed by the self-operated avatar At is different from the action performed by the teaching avatar Ae. For example, the feedback stimulus providing unit P9 may instruct the display device 10 to provide a visual stimulus to the subject T, such as by lighting up the screen displayed thereon, or may instruct a speaker to provide an auditory stimulus to the subject T by voice, or may instruct the finger motion detection device 21 to provide a tactile stimulus, such as by vibrating the fingers of the subject T, or may instruct an olfactory stimulus providing device to provide an olfactory stimulus to the subject T by emitting an aroma component, for example.

[0049] As a result, the subject T receives feedback and directs his / her attention to operating the self-operated avatar At that matches the teaching avatar Ae, activating his / her brain functions.

[0050] In the above description, the object is the ball B, but the object is not limited to this. The object may be a tool such as a racket, a skateboard, or a surfboard.

[0051] (Two-in-One Processing) Fig. 8 is an explanatory diagram illustrating an example of a usage state. Fig. 9 is an explanatory diagram illustrating an example of a skilled action learning image G6.

[0052] As shown in FIG. 8, a subject T wears a hand motion detection device 21 and a body motion detection device 23 and sits in front of a desk.

[0053] As shown in Figure 9, in the skilled movement learning image G6 displayed as a virtual space on the display device 10, the object display unit P4 displays the object piano Pn, the teaching avatar display unit P5 displays the teaching avatar Ae that performs the teaching movements of an expert, and the self-operation avatar display unit P6 displays the self-operation avatar At.

[0054] This allows the subject T to move his / her fingertips to operate the self-operated avatar At and play the piano Pn, and to operate the self-operated avatar At to match the teaching avatar Ae while having fun, thereby activating brain functions.

[0055] The matching degree calculation unit P10 calculates a matching degree of the motion between the self-operated avatar At and the teaching motion. The matching degree of the motion can be calculated, for example, based on the difference between the degree of bending of the fingers of the self-operated avatar At based on the finger bending information and the degree of bending of the fingers of the teaching avatar Ae, based on the angle of the orientation of each arm, or by machine learning technology using a trained model. For example, if the bending and extending fingers of the self-operated avatar At are the same as the bending and extending fingers of the teaching avatar Ae, respectively, the matching degree of the motion is high. The higher the matching degree of the motion, the more similar or identical the motions of the self-operated avatar At and the teaching avatar Ae are.

[0056] When the degree of motion matching is equal to or greater than a predetermined threshold, the avatar replacement unit P11 replaces the motion of the self-operated avatar At with the teaching motion, causing the self-operated avatar At to perform the same motion as the teaching motion. The predetermined threshold is adjusted so that motor learning of the subject T is more effective. The predetermined threshold may be adjusted so that replacement is more likely to occur for a subject T with a low fine motor evaluation value and / or a low gross motor evaluation value. Furthermore, the motion replacement ratio of the self-operated avatar At based on the teaching motion may be changed depending on the subject T's proficiency level. For example, using a motion matching rate of 80% as the standard, when the rate is 80% or higher, the motion of the self-controlled avatar At is replaced with a teaching motion; when the motion matching rate is 70% or higher but less than 80%, the self-controlled avatar At is displayed with two-thirds of the motion of the controlled avatar At reflected against one-third of the user's motion; when the motion matching rate is 60% or higher but less than 70%, the self-controlled avatar At is displayed with one-third of the motion of the controlled avatar At reflected against two-thirds of the user's motion; and when the motion matching rate is less than 60%, the user's motion is displayed as the self-controlled avatar At.

[0057] As a result, when the movements of the self-operated avatar At approach the movements taught by the teaching avatar Ae, the subject T can have a more real experience of success, knowing that his or her own movements are approaching the correct movements of the teaching information. This can improve the subject T's motivation to continue developing athletic ability, thereby making athletic ability development more efficient.

[0058] The average avatar display unit P12 hides the self-operated avatar At and displays an average avatar obtained by averaging the self-operated avatar At and the instructor avatar Ae. The average avatar is displayed by, for example, calculating the average value of the degree of finger bending of the self-operated avatar At and the degree of finger bending of the instructor avatar Ae based on the finger bending information, or the average value of the arm orientation.

[0059] This allows subject T to experience, via the average avatar, that his or her own movements are approaching the correct movements in the virtual space. As a result, even if subject T's movements deviate from the correct movements, subject T can develop athletic ability without being conscious of the experience of failure. Athletic ability development system 1 can maintain subject T's motivation to continue athletic ability development and can make athletic ability development more efficient.

[0060] (Display processing according to evaluation value) The instructor avatar display unit P5 selects instruction movement information to be displayed in the virtual space based on the fine motor evaluation value and gross motor evaluation value determined by the motor ability evaluation system 2. For example, if the fine motor evaluation value of the subject T is excellent, the instructor avatar display unit P5 selects instruction movement information of an instructor avatar Ae that performs a highly difficult fine movement. On the other hand, if the gross motor evaluation value of the subject T is low, the instructor avatar display unit P5 selects instruction movement information of an instructor avatar Ae that performs a less difficult gross movement.

[0061] The instructor avatar display unit P5 may adjust the transparency of the instructor avatar Ae based on the difficulty level determined by the difficulty level determination unit P3. For example, when the difficulty level determination unit P3 determines the fine motor difficulty level to be low, the instructor avatar display unit P5 displays the instructor avatar Ae performing the fine motor with a low transparency so that the instructor avatar Ae is easily visible. On the other hand, when the difficulty level determination unit P3 determines the fine motor difficulty level to be high, the instructor avatar display unit P5 displays the instructor avatar Ae with a high transparency so that the instructor avatar Ae is not noticeable.

[0062] Furthermore, when the difficulty level determination unit P3 determines the gross motor difficulty to be low, the instructor avatar display unit P5 displays the instructor avatar Ae with low transparency so that it is easy to see, whereas when the difficulty level determination unit P3 determines the gross motor difficulty to be high, the instructor avatar display unit P5 displays the instructor avatar Ae with high transparency so that it is not noticeable.

[0063] The transparency may be set according to the degree of matching of the movements of the subject T. For example, when the degree of matching of the movements is high, such as 80%, the transparency is set to 80% so as to be inconspicuous, and when the degree of matching of the movements is low, such as 50%, the transparency is set to 50% so as to be easily visible. The transparency of the teaching avatar Ae may also be adjusted according to the fine motor evaluation value and gross motor evaluation value of the subject T.

[0064] The object display unit P4 determines an object to be displayed based on the fine motor evaluation value and gross motor evaluation value determined by the motor ability evaluation system 2, and adjusts the movement or deformation of the object. The object display unit P4 also adjusts the movement speed of the object based on the difficulty level determined by the difficulty level determination unit P3.

[0065] For example, the object display unit P4 may slow down the movement speed of the object for performing gross movements for a subject T with a low gross movement evaluation value, compared to a predetermined movement speed. On the other hand, the object display unit P4 may speed up the movement speed of the object for performing gross movements for a subject T with a high gross movement evaluation value, compared to a predetermined movement speed. Furthermore, the object display unit P4 may slow down the movement speed of the object for performing fine movements for a subject T with a low fine movement evaluation value, compared to a predetermined movement speed. On the other hand, the object display unit P4 may speed up the movement speed of the object for performing fine movements for a subject T with a high fine movement evaluation value, compared to a predetermined movement speed.

[0066] As a result, the motor skill development system 1 displays an object and an instructor avatar Ae according to the fine motor skill evaluation value and gross motor skill evaluation value of the subject T, thereby making motor skill development more effective.

[0067] (Operation) Next, the operation of the athletic ability development system 1 will be described using a flowchart.

[0068] FIG. 10 is a flowchart showing an example of the flow of the skilled motion learning process.

[0069] The motor skill development system 1 first evaluates the motor skills of the subject T. The finger movement instruction unit P1a instructs the subject T to move his or her fingers (S1), and the finger movement detection device 21 transmits a finger detection signal of the subject T to the control device 30. The fine motor evaluation unit P1b evaluates the finger movement based on the finger detection signal acquired from the finger movement detection device 21, and outputs a fine motor evaluation value indicating the fine motor skill of the subject T (S2).

[0070] The physical movement instruction unit P2a instructs the subject T to move his / her body (S3), and the gross motor evaluation unit P2b evaluates the physical movement based on the subject T's body detection signal and outputs a gross motor evaluation value indicating the subject T's gross motor ability (S4).

[0071] The difficulty level determination unit P3 determines the fine motor difficulty level based on the fine motor evaluation value, and also determines the gross motor difficulty level based on the gross motor evaluation value (S5).

[0072] In the virtual space, the object display unit P4 displays an object, the self-operated avatar display unit P6 displays the self-operated avatar At, and the teaching avatar display unit P5 displays the teaching avatar Ae (S6).

[0073] The matching degree calculation unit P10 calculates the degree of matching of the movements of the self-operated avatar At based on the finger bending information, the difference between the degree of bending of the fingers of the teaching avatar Ae, and the difference in the orientation of their arms (S7). If the degree of matching of the movements is not within a predetermined range, the process of S7 is repeated (S8: NO). On the other hand, if the degree of matching of the movements is within the predetermined range (S8: YES), the movement of the self-operated avatar At is replaced with the teaching movement and displayed (S9).

[0074] (Experimental Results) Next, the results of an experiment conducted by the inventors of the present application to confirm the effects of the embodiment will be described.

[0075] 11 shows the blood flow measurement results of the dorsolateral prefrontal cortex (DLPFC) of the brain under the success and failure conditions of the task. The measurement results are shown as average values ​​in the bar graph, and the error bars indicate the standard deviation.

[0076] The dorsolateral prefrontal cortex is generally known to function in relation to motor skills, such as working memory, attention control, problem-solving ability, and motor planning and coordination, and it is thought that the degree of activation of these functions can be evaluated by changes in blood flow.

[0077] In the experiment, an avatar hand was generated by combining data detected from the participant's hand movements with pre-recorded CPU data at a predetermined synthesis ratio, and only the movements related to the bending and straightening of the fingers were reproduced on the display without changing the position of the avatar hand. Multiple avatar hands with different synthesis ratios were prepared, and the blood flow in the dorsolateral prefrontal cortex of the participant operating each avatar hand was measured using near-infrared spectroscopy (NIRS).

[0078] Under these conditions, it was confirmed that participants operating the avatar hand had a sense of agency, regardless of the composite ratio. Furthermore, when the task was ball-catching training and the success condition, in which participants succeeded, was compared with the failure condition, in which participants failed, it was confirmed that the sense of agency was significantly higher in the success condition than in the failure condition. Furthermore, as shown in Figure 11, the dorsolateral prefrontal cortex showed significantly greater blood flow and activation in the success condition than in the failure condition.

[0079] Next, changes in motor evoked potentials (MEPs) were measured and compared between ball catch training using a controller and a glove-type sensor. The measurement results are shown in Figure 12. In Figure 12, the average values ​​are shown as bars, and the standard deviations are shown as error bars. "Pre" indicates the measurement results before ball catch training, and "Post" indicates the measurement results after ball catch training.

[0080] In the experiment, participants performed ball-catching training by imagining the movement (Motor Imagery) while observing an image of an avatar hand catching a ball on a display (Action Observation) before (pre) and after (post) the ball-catching training. During this training, the primary motor cortex was stimulated using transcranial magnetic stimulation (TMS), and motor-evoked potentials induced in the thenar muscles (thenar) were measured using electromyography.

[0081] In the ball-catching training, participants controlled an avatar hand on a display using a controller or a glove-type sensor that sensed the movement of their actual hand, and performed the task of catching a ball 250 times.

[0082] As shown in Figure 12, the motor evoked potentials measured after the participants performed ball-catching training using the glove-type sensor were significantly increased compared to the measurements before the training, and the magnitude of the increase was greater than when using a controller. These results suggest that using a glove-type sensor, which reflects actual hand movements, during ball-catching training increases the excitability of the corticospinal tract and results in a greater learning effect than using a controller.

[0083] (Vibrotactile Stimulation) Experiment participants wore a glove-type sensor that sensed the movement of their actual hands and operated an avatar hand on a display to perform a task of catching a ball. During the task, vibrotactile stimulation was applied when the participant succeeded or failed to catch the ball, and EEG event-related potentials related to motor learning were measured. The P300 component and feedback-related negativity (FRN) of the event-related potentials obtained from EEG electrodes were investigated for changes over time in potentials before and after indicating success or failure (not shown).

[0084] The results of this experiment showed that the P300 component, an index that reflects the amount of attention paid to a stimulus, tended to have a larger amplitude when vibrotactile stimulation was applied upon success than when vibrotactile stimulation was applied upon failure, indicating that applying tactile vibration stimulation upon success makes participants more aware of the experience of success.On the other hand, the FRN, an index related to awareness of errors, had a larger amplitude after success or failure was determined, both when vibrotactile stimulation was applied upon success and when vibrotactile stimulation was applied upon failure, and the amplitude of the difference waveform between these was also large, suggesting that applying tactile vibration stimulation upon failure made it easier to detect errors.

[0085] (Effects) The athletic ability development system 1 can implement appropriate athletic ability development to improve brain functions such as integrating somatosensory information and visual information, and correcting errors in the integrated information by taking predictive information into account. In particular, when subject T implements such athletic ability development, the athletic ability development system 1 can improve blood flow within the brain and establish signal pathways within the brain to improve brain functions, particularly the brain functions integrating somatosensory information and visual information, and the brain functions correcting errors in the integrated information by taking predictive information into account. In this way, the athletic ability development system 1 can implement appropriate athletic ability development for subject T according to the accurately determined athletic ability of subject T, thereby efficiently improving coordinated motor skills.

[0086] Subject T with DCD is particularly poor at integrating somatosensory and visual information in the brain and correcting errors in this integrated information by taking predictive information into account. This makes it difficult for them to correct their motor plans, and subject T with DCD tends to lose confidence due to repeated motor failures.

[0087] To overcome DCD, it is effective to improve brain functions related to coordination, and furthermore, it is effective to repeatedly develop motor skills to move the hands, fingers, arms, legs, and the entire body including these, so as to enhance brain functions related to motor physiology. Motor skill development is effective in building signal pathways to integrate somatosensory information and visual information within the brain, and signal pathways to correct errors in such integrated information by taking predictive information into account, and is effective for subject T with DCD.

[0088] According to the embodiment, the athletic ability development system 1 and the athletic ability evaluation system 2 can more efficiently improve the athletic ability of the subject T by using an avatar displayed in a virtual space.

[0089] That is, the motor ability evaluation system 2 includes a finger movement instruction unit P1a that instructs the subject T to perform finger movements, a physical movement instruction unit P2a that instructs the subject T to perform physical movements, a movement detection device 20 that detects the finger movements and physical movements of the subject T, a fine motor evaluation unit P1b that evaluates the finger movements instructed by the finger movement instruction unit P1a based on the detection signal obtained by detecting the movements of the subject T using the movement detection device 20, and a gross motor evaluation unit P2b that evaluates the physical movements instructed by the physical movement instruction unit P2a based on the detection signal.

[0090] The difficulty determination unit P3 determines the difficulty of the fine motor skills to be presented to the subject T based on the fine motor skill evaluation value evaluated by the fine motor skill evaluation unit P1b, and determines the difficulty of the gross motor skills to be presented to the subject T based on the gross motor skill evaluation value evaluated by the gross motor skill evaluation unit P2b.

[0091] The motor skill development system 1 further includes an object display unit P4, a self-operated avatar display unit P6, and a teaching avatar display unit P5. The object display unit P4 displays movable and / or deformable objects in a virtual space. The self-operated avatar display unit P6 displays a self-operated avatar At operated by the subject T, which performs actions based on detection signals and is capable of moving and / or deforming objects in the virtual space. The teaching avatar display unit P5 acquires teaching action information for the object from the memory unit 33, displays a teaching avatar Ae that performs teaching actions based on the teaching action information, determines the object to be displayed based on the difficulty of fine motor skills and gross motor skills determined by the motor skill evaluation system 2, and adjusts the movement or deformation of the object or selects teaching action information.

[0092] The teaching avatar display unit P5 adjusts the transparency of the teaching avatar Ae based on the difficulty level determined by the difficulty level determination unit P3.

[0093] The object display unit P4 adjusts the moving speed of the object based on the difficulty level determined by the difficulty level determination unit P3.

[0094] The distance calculation unit P7 calculates the distance between the self-operated avatar At and the teaching avatar Ae, and the feedback stimulus determination unit P8 determines the stimulus to be given to the subject T by the feedback stimulus giving unit P9 based on the distance calculated by the distance calculation unit P7.

[0095] The matching calculation unit P10 calculates the degree of matching between the action performed by the self-operated avatar At and the teaching action, and the avatar replacement unit P11 replaces the action performed by the self-operated avatar At with the teaching action when the degree of matching is within a predetermined range, and makes the self-operated avatar At perform the same action as the teaching action.

[0096] The motor ability evaluation method instructs the subject T to perform a finger movement using a finger movement instruction unit P1a, instructs the subject T to perform a physical movement using a body movement instruction unit P2a, detects the finger movements and body movements of the subject T using a movement detection device 20, evaluates the finger movements instructed by the finger movement instruction unit P1a based on the detection signal obtained by detecting the movements of the subject T using the movement detection device 20, and evaluates the body movements instructed by the body movement instruction unit P2a based on the detection signal using a gross motor evaluation unit P2b.

[0097] The motor ability evaluation program includes code for causing a computer to execute processing of a finger movement instruction unit P1a that instructs finger movements to subject T, code for causing a computer to execute processing of a physical movement instruction unit P2a that instructs physical movements to subject T, code for causing a computer to execute processing of a movement detection device 20 that detects the finger movements and physical movements of subject T, code for causing a computer to execute processing of a fine motor evaluation unit P1b that evaluates the finger movements instructed by the finger movement instruction unit P1a based on detection signals obtained by detecting the movements of subject T using the movement detection device 20, and code for causing a computer to execute processing of a gross motor evaluation unit P2b that evaluates the physical movements instructed by the physical movement instruction unit P2a based on the detection signals.

[0098] As described above, the embodiments of the present invention have been described, but the embodiments are not limited to these, and various changes, modifications, etc. are possible within the scope that does not change the gist of the present invention.

[0099] Furthermore, the order of execution of each step of each procedure in the embodiments may be changed, multiple steps may be executed simultaneously, or the steps may be executed in a different order each time, as long as this does not contradict the nature of the steps. Furthermore, all or part of the steps of each procedure in the present embodiment may be realized by hardware or by a program.

[0100] According to an embodiment of the present invention, it is possible to provide an athletic ability evaluation system, an athletic ability development system, an athletic ability evaluation method, and an athletic ability evaluation program that can more efficiently improve the athletic ability of a subject using an avatar displayed in a virtual space.

[0101] This application claims priority from Japanese Patent Application No. 2024-083081 filed in Japan on May 22, 2024, and the above disclosure is incorporated herein by reference in its entirety.

Claims

1. A motor ability evaluation system comprising: a hand movement instruction unit that instructs a subject to perform hand and finger movements; a physical movement instruction unit that instructs the subject to perform physical movements; a movement detection device that detects the hand and finger movements and the physical movements of the subject; a fine motor evaluation unit that evaluates the hand and finger movements instructed by the hand movement instruction unit based on detection signals obtained by detecting the subject's movements using the movement detection device; and a gross motor evaluation unit that evaluates the physical movements instructed by the physical movement instruction unit based on the detection signals.

2. The motor ability assessment system of claim 1, further comprising a difficulty determination unit, which determines the difficulty of fine motor skills to be presented to the subject based on the fine motor skill evaluation value evaluated by the fine motor skill evaluation unit, and determines the difficulty of gross motor skills to be presented to the subject based on the gross motor skill evaluation value evaluated by the gross motor skill evaluation unit.

3. A motor ability development system further comprising an object display unit, a self-operated avatar display unit, and a teaching avatar display unit, wherein the object display unit displays movable and / or deformable objects in a virtual space, the self-operated avatar display unit displays a self-operated avatar operated by the subject in the virtual space that performs an action based on the detection signal and is capable of moving and / or deforming the object, the teaching avatar display unit acquires teaching action information for the object from a memory unit, and displays a teaching avatar that performs teaching actions based on the teaching action information, and determines the object to be displayed based on the difficulty of fine motor skills and the difficulty of gross motor skills determined by the motor ability evaluation system described in claim 2, and adjusts the movement or deformation of the object, or selects the teaching action information.

4. The athletic ability development system according to claim 3, wherein the instructor avatar display unit adjusts the transparency of the instructor avatar based on the difficulty level determined by the difficulty level determination unit.

5. The athletic ability development system according to claim 3, wherein the object display unit adjusts the moving speed of the object based on the difficulty level determined by the difficulty level determination unit.

6. The athletic ability development system of claim 3, further comprising a distance calculation unit, a feedback stimulus determination unit, and a feedback stimulus application unit, wherein the distance calculation unit calculates the distance between the self-controlled avatar and the teaching avatar, and the feedback stimulus determination unit determines the stimulus to be applied to the subject by the feedback stimulus application unit according to the distance calculated by the distance calculation unit.

7. The athletic ability development system of claim 3, further comprising a similarity calculation unit and an avatar replacement unit, wherein the similarity calculation unit calculates a degree of similarity between the action performed by the self-controlled avatar and the teaching action, and the avatar replacement unit, when the degree of similarity is within a predetermined range, replaces the action performed by the self-controlled avatar with the teaching action and causes the self-controlled avatar to perform the same action as the teaching action.

8. A motor ability evaluation method, comprising: a finger movement instruction unit instructing a subject to perform a finger movement; a physical movement instruction unit instructing the subject to perform a physical movement; a movement detection device detecting the finger movements and physical movements of the subject; a fine motor evaluation unit evaluating the finger movements instructed by the finger movement instruction unit based on detection signals obtained by detecting the subject's movements with the movement detection device; and a gross motor evaluation unit evaluating the physical movements instructed by the physical movement instruction unit based on the detection signals.

9. A motor ability evaluation program having: code for causing a computer to execute processing by a hand movement instruction unit that instructs a subject to perform hand movement; code for causing a computer to execute processing by a body movement instruction unit that instructs the subject to perform body movement; code for causing a computer to execute processing by a movement detection device that detects the subject's hand movements and the body movements; code for causing a computer to execute processing by a fine motor evaluation unit that evaluates the hand movement instructed by the hand movement instruction unit based on a detection signal obtained by detecting the subject's movement with the movement detection device; and code for causing a computer to execute processing by a gross motor evaluation unit that evaluates the body movement instructed by the body movement instruction unit based on the detection signal.

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