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ArticlesEffect of Augmented Reality Affordance on Motor Performance: In the Sport Climbing
• Myeong-Hyeon Heo1 and Dongho Kim2,*

Human-centric Computing and Information Sciences volume 11, Article number: 40 (2021)
https://doi.org/10.22967/HCIS.2021.11.040

Abstract

Conventional sport climbing instructions have been made by showing a demonstration of an instructor and pointing the positions of the hands and feet one by one. Therefore, it has been consistently requested to develop a way for a learner to observe the demonstration in real-time and climb as instructed even in the absence of an instructor. The objectives of this study were to propose an augmented reality affordance suitable for the indoor sport climbing environment and evaluate its effectiveness. This study developed a projection-based augmented reality affordance system that projected character animation onto the artificial climbing structure so a novice could climb the structure based on the movement of the character. An instructor can spontaneously create and provide climbing postures and motions to the learner through this. Moreover, a learner can train repeatedly without the help of the instructor after selecting the route the learner wants to train. This study compared the performance evaluation scores before and after a lesson between the conventional group and the augmented reality affordance group to examine the effects on exercise performance. The results showed that the application of augmented reality affordance to sport climbing was as effective as the conventional instruction method.

Keywords

Augmented Reality, Affordance, Metaverse, Motor Performance, Sport Climbing

Introduction

It takes a lot of time and effort at the stage of repeating movement to acquire skills for motor learning. The meaning of motor learning is the process of experience and practice to acquire skilled movements. Therefore, it is required to develop training techniques that can lead to voluntary learning by stimulating and immersing in the stage, which repeats monotonous and tedious movement[1]. As an alternative, the augmented reality technology has been emerging [2]. It refers to a technology that can allow interactions between the virtual objects and the real world by mixing them in the real space. Moreover, it is a technology that can enhance learning efficiency by combining and showing virtual objects with the real world[3, 4]. Recent studies have revealed that virtual reality and augmented reality have positive learning effects in the sports education and training field[58]. Particularly, it can be used for beginners to learn complex movements effectively by presenting specific and clear affordance in a short time. Affordance is an intrinsic attribute that allows a perceived object or thing to induce action to the user.
Soltaniand Morice[9] argued that basketball and sports climbing would provide the most beneficial framework for developing augmented reality in the sports sector. This is because the artificial structure used in sport climbing is usually made of flat plywood or plastic panels, suitable for constructing projection-based augmented reality.
Sanchez et al. [10] revealed that examining the climbing route in advance was an important element in indoor climbing. They claimed that examining the climbing route in advance improved the results because climbers hesitated less while climbing and they could think more about the functional aspects such as connective movement during climbing rather than the structure of the wall. Wiehr et al. [11] used a self-correction projection system that allowed them to check their own movements in real-time on a small screen mounted on the wall while climbing. Kajastilaet al. [12] drew users’ participation and interest by projecting game and route guidance content onto an artificial climbing structure by utilizing a projection-based climbing system. This augmented reality content can motivate and stimulate climbers to practice by themselves even in the absence of an instructor.
If novice climbers receive a visual climbing example of the route to be used, they can have a better sport climbing experience. However, the arrangement and route of artificial climbing structures are frequently changed most times. Therefore, it takes a lot of time and resources to film the demonstration or climbing of an expert or create a virtual climbing animation for each step according to the changed route. It is believed that there is a high possibility that providing climbing content using computer simulation can provide an educational benefit through repeated training and motivation. Therefore, the objectives of this study were to propose a projection-based augmented reality affordance system allowing a user to climb along with a character in an indoor sport climbing environment and to examine the effect on performing sport climbing movements.

Background

Augmented Reality for Sports Education and Training
Augmented reality technology is used to improve sports performance because it has the advantage of providing additional information to help users decide and control their behaviors. In this case, virtual information is overlaid on the real situation to increase the user’s understanding and knowledge[07]. In particular, it was found that providing additional information to unskilled users could improve their experience, enjoyment, and immersion [13,14]. For example, Sano et al. [15] augmented the positions of players so that beginners could improve their decision-making skills in soccer. Kelly and O'Connor [16] developed a visualization tool for tennis that augmented information about technique, timing, and body posture.
Augmented reality can also help instructors explain complex sports concepts such as orientation. Wiehr et al. [11] projected climbing videos and routes onto an artificial climbing structure. The shadow-shape image helps the user adjust the posture. At this time, various routes suitable for the user’s motor ability are provided to the user in real-time. Moreover, the user’s climbing is recorded and analyzed to facilitate efficient climbing. Augmented feedback can induce faster and more efficient motor learning than video playback or coaching feedback [12].
Gradl et al. [17] revealed that 43% of athletes thought that using augmented reality could improve their performance. Athletes can receive personalized feedback from their coaches. This can integrate players quickly or shorten the time required for the entire team to improve positioning and learn new tactics.
In previous studies, the focus of augmented reality was technology. Future studies shall consider the development of augmented reality technology [9]. However, how to design a meaningful scenario and provide content suitable for the characteristics of sports are critical topics in augmented reality, in addition to technology. Additionally, it is more important to create scenarios that keep participants motivated and active [18]

Augmented Reality Affordance and Movement
Affordance is an important concept that is discussed as a characteristic in the studies on augmented reality space. An affordance is defined as the perception of an object that induces a specific behavior to the user or the intrinsic characteristic of an object. In other words, it refers to the direct relationship with the environment to which a person adapts, and it can be considered as a process of directly obtaining information about an event, an object, or the arrangement of objects including the environment [1921].
In general, a movement is automatically prepared and performed. Moreover, once such a movement is initiated, it achieves its purpose quickly and accurately. Due to the short performance time, the top-down motor control system is finitely involved. The representation of such an action or a motion must be automatically resolved. Additionally, the information of an object conducting the action also undergoes an automatic process. For example, when performing an action such as holding an object by hand, information regarding the size or shape of the object automatically processes the shape of the hand and the number of fingers to be used to hold the object. Furthermore, based on the information about the weight and texture of the object, the force shall be used to hold the object is automatically determined. Jakobson and Goodale [22] confirmed that the accuracy of movement performance decreased as the gap between the starting point of the movement and the point of presenting the target became larger. This result is because, as described above, as the start of a movement is delayed more, the information available in the processing process disappears along with it due to the characteristics of the rapidly disappearing movement representation. It is believed that the recognition of the movement performance goal and the course of processing motor performance accurately are separate. In particular, when goal-oriented motor performance is consciously controlled, it progresses slowly and incorrectly [23]. For example, it is possible to observe slow and inaccurate movements when learning a new exercise technique without experience. It is impossible to perform the movements automatically.

Climbing Movement
Previous studies on the generation of sport climbing movement have applied cost functions or gravity functions for each body part and optimized them.
Pfeil et al. [24] optimized the motion from the current position of a character to the artificial hold entered by the user by using SNOPT optimization library [25] and generated motions. In this study, the climber character had eleven joints and it set an approximate cost function for generating a sport climbing motion in real-time and optimized it by minimizing it. It realized the motion of placing the body toward the wall as close as possible while simultaneously hanging the body of the virtual climber character down. Although the study could create the animation of climbing motions quickly, the results of this study did not look natural because the climber character exhibited incomprehensible postures and movements, such as excessively flexible movements.
Kavafoglu et al. [26] proposed a method of generating the animation of sport climbing for each stage by applying an end effector state machine. The unique result of this study was to create diverse movements of a virtual climber character by organizing the order of movements for each step after dividing the movements of limbs into multiple steps. Moreover, it realistically realized the movement resisting gravity by applying a physics engine to the body parts. However, this study evaluated movements of climbing a bare wall without a specific target point. Although this study achieved various movement methods, the body movement itself was monotonous, which was different from the actual climbing movement and was a disadvantage of this study.
Naderi[27] developed a simulation that designed a route by calculating the shortest climbing route and optimizing climbing movements. The method proposed in this study generates climbing animations without reference animations and motion capture data [2729]. However, it is considerably different (visually) from the demonstration of an instructor. Therefore, it was insufficient to be used as a climbing posture reference for novice climbers.
The objective of this study was to produce a character animation that can be used as a climbing posture reference for novice climbers. Therefore, this study implemented the movements of sport climbing by estimating the approximate posture of a virtual character using relatively simple functions based on an expert’s climbing motions and supplementing them by applying a physics engine, instead of performing optimization calculations for all body parts.

Methods

Project-based Augmented Reality Affordance
This study proposed a projection-based augmented reality affordance system that projects an observation learning-based character animation on real artificial rock and helps a beginner climbs the rock along with the character (Fig. 1). An instructor can provide climbing postures and motions instantly for beginners, and beginners can choose the path they want to train repeatedly without the help of an instructor.
Fig. 1. Projection-based augmented reality climbing character animation system.

The projection-based augmented reality affordance space is composed of an artificial rock element, a beam projector element, and a character animation element. A beam projector was installed on the ceiling of the indoor rock which does not interfere with the movement radius of the user. Beginners can learn how to climb the artificial rock according to the stage of motion while it is synchronized with the actual artificial rock. Moreover, a character appears at any time, whenever necessary, and teaches how to climb alongside the user. This augmented reality space has a mechanism that induces actions so the user can imitate easily and learn motions by providing a virtual character climbing the rock for a person who is not familiar with climbing. Affordance means the attributes of an object that induces the user to act, and it is one of the important media attributes of augmented reality. In the augmented reality space, the virtual character provided to a user presents a concrete situation in front of an artificial rock in the real world. The action of a user, who climbs following actual holds in synchronization with the movement of the virtual character, is different from the behavior of a climber who checks the position of holds, comes up with a suitable route, and climbs. In other words, the climbing can be considered as an action climbing the artificial rock close in a state of consciousness close to the automatic movement.
In the error correction process, it is especially common for novice climbers not to recognize what is the appropriate sensory information, although they know that they are supposed to correct the errors in their motions. Therefore, it is possible to utilize the affordance information for accurate movement in real-time by utilizing augmented reality technologies.

Configuring Climbing Routes
It is necessary to generate artificial holds for sport climbing and a route consisting of them first before creating sport climbing movements.
First of all, it is required to determine key factors that the artificial hold should have for an expressing artificial climb structure composed of multiple climbing artificial holds. The factors of the artificial hold influencing the actual sport climbing were the angle of the wall, the position, direction, shape, and material of the artificial hold, friction coefficient, and the area in contact with hands and feet. This study chose the position, direction, and type of the artificial hold as the main factors for creating the animation of a sport climbing character and realized an artificial hold object class that possessed the data of these variables. The class contains functions that can convert and print the data in another format for calculations used while producing the character animation afterward, as well as data variables related to the main factors that each artificial hold must have. This study implemented three axes for the position and direction (six degrees of freedom) to make it suitable for the simulation of three-dimensional (3D) space. It allows a user to conduct sport climbing in various and free ways such as designing a climbing route just by selecting a few climbing artificial holds among them attached to the artificial climbing structure without a pre-determined climbing route. The objective of this study was to realize a movement close to the movement of a sport climbing expert. Therefore, it was possible to input the previously designed climbing route. The route can be entered by clicking the artificial hold visualized in the previous step. At this time, the climbing route data was configured to provide a climbing route for artificial climbing holds held by the hand and those stepped by the foot by separating them into two classes. Therefore, the implemented climbing route presents a climbing route for the hand, that for the right foot, and that for the left foot.

Climbing Character Animation
This study used the character animation based on inverse kinematics to provide affordance for conducting a performance in the augmented reality. Inverse kinematics is a technique used to control the posture of animation naturally. It can automatically configure the motion of a character’s joints according to the position. However, it is possible to distort the character’s joints while creating postures of the character using the inverse kinematics algorithm.
In order to overcome this issue, this study created the basic movement of the character by referring to the actual climbing motion of expert climbers.
The study obtained frame animation through motion capture using the Microsoft Kinect v2 sensor to produce animation for sport climbing postures (Fig. 2). The basic posture motion capture animation of a sport climbing expert also has the advantage of obtaining a solution of the inverse kinematics algorithm closer to the desired posture by limiting the starting point of the process of finding the appropriate joint rotation value before applying the inverse kinematics algorithm. In this study, the position and direction of the 3D character’s hands and feet were determined solely by the inverse kinematics algorithm, not by the animation, unlike blending the motion capture data with other body parts such as arms and legs (Fig. 3). This is because it is important to reach the correct position. The target points where the hands and feet must be reached finally are on the climbing artificial hold included in the climbing route. Therefore, the next target points of the hands and feet area are the positions of the next artificial climbing holds to be used in the next step on the climbing route.
 (a) (b)
Fig. 2. A filming environment using a transparent acrylic climbing structure (a) and the captured video screen of an expert demonstration (b).

Fig. 3. Climbing character animation.

Moreover, it considered the character’s center of gravity by calculating the center of gravity based on the position of the hands and feet. Additionally, the inclination of the torso was expressed using the angle between the holds
At this time, the gaze of the character was presented by taking the character’s head direction, moving order, and moving direction into consideration. Spherical linear interpolation was utilized to realize the smooth moving trajectory of hands and feet during climbing. Since the human body does not move at constant velocity linearly, a weight function was applied according to the distance and time in order to express the changes in the velocities of the hands and feet naturally. The data structure of the holds and routes of the artificial rock was configured to create character animation in a random order, and animation was generated from the three-point posture of the sport climbing. The character was made to move one and one foot at each time. In other words, the other hand and foot are always placed on the holds so that the body moves in the form of a triangle or inverted triangle.
An algorithm considering the moving order of each limb is needed to realize this moving method. First, the index of the next hold is received from the hold data of the start location. Afterward, the position of the hold matching with the corresponding index is transferred to determine the position of the final target. When the next hold, which is to be moved next through this process, is determined, the character looks at the target points for the legs and arms. Subsequently, the character decides which arm or which leg to be used (right or left) depending on the direction of the target location from the current location. If the target location is on the right or left side of the character, the character is supposed to move the right or left limbs, respectively. The sequence of actions should be made according to which limb has moved. For example, when one hand is moved to the target position, the foot in the opposite direction is supposed to move next. At this time, the character form an inverse triangle shape and the other limb is moved to the next hold. After this movement sequence is completed, the position of the torso is lowered and the arm is fully extended. If the movements are made continuously, the corresponding movement is not generated and a next movement is performed. When the next route does not exist, the repetition is completed (Fig. 4).
Fig. 4. Movement algorithm of a climbing character.

Experiment

Sport Climbing Performance Evaluation
This study evaluated the effects of augmented reality affordance on motor performance by applying it to actual sports climbing (Fig. 5). The process of changing the ability required to generate motor performance takes place within the learner. In other words, the changes related to actual motor performance can be directly observed at a reliable level. Therefore, the degree of changes in a learner’s motor performance can be directly observed and estimated to understand the effects of augmented reality affordance on motor performance. In other words, the objective of this study was to examine whether the effects of AR affordance on motor performance were equivalent to those of the traditional instructing-learning delivery method by comparing the pre- and post-climbing performance evaluation of the traditional climbing instruction group and that of the augmented reality affordance group.
 (a) (b)
Fig. 5. Experimental environment (a) and augmented climbing character animation (b).

Study Subjects
This study set the minimum age of the study subjects by referring to previous studies, which reported that children could perceive affordance as good as adults after 7 years old when postural control ability developed rapidly[30]. Moreover, this study examined elementary school students under 11 years old to control variables affected by the experience of learning other sports and physical ability according to the growth environment. Consequently, this study selected 40 elementary school students between the ages of 8 and 10 with no previous experience in sport climbing. The subjects were divided into a traditional climbing class (20 students) and a learning class using augmented reality affordance (20 students).

Experimental Equipment
The artificial rock wall used for the experiment had a width of 4m and a length of 3m. It had 300 hold holes at the interval of 0.2m in width and length. Safety mats were placed under artificial rock walls to prevent injury to participants in this experiment. InFocus IN5555L (InFocus Inc., Tigard, OR, USA) was used for the beam project. The application environment was based on Windows 7 Pro 64bit (Microsoft, Redmond, WA, USA) operating system and Unity Engine 4. The PC had a 3.7-GHz Intel Core i7 CPU, NVIDIA GeForce GTX 680, 16GB RAM, and 1920×1080 resolution.

Experimental Procedure
The objective of this study was to examine the effects of augmented reality affordance on motor performance by applying it to actual sport climbing. In other words, this study aimed to prove that the effect of augmented reality affordance on motor performance was equivalent to that of traditional instructing-learning delivery method on it by comparing the utilization of the traditional climbing instruction and that of augmented reality affordance (Fig. 6). Therefore, this study set the instruction method to be applied to the traditional climbing instruction group and the augmented reality affordance group as independent variables and treated the climbing performance evaluation score as a dependent variable. The number of students per class was limited to 5: the traditional climbing group was divided into four classes and the augmented reality affordance group was also divided into four classes. The same instructor instructed these classes for approximately 30 minutes per session. The traditional climbing instruction group received the traditional sport climbing instruction using a pointer. On the other hand, the augmented reality affordance group was instructed by projecting a climbing character animation that performed motions according to the hold and route desired by the instructor onto the artificial rock wall. The character animation was made to move on to the next motion when recognizing the “Go” voice order. Since the subjects did not have a sufficient understanding in augmented reality applications that they encountered for the first time, the method of interacting with the system was intensively explained [31]. The evaluation criteria for climbing performance were established in consultation with a former national team climber based on the climbing training method suggested. Accordingly, evaluation criteria were three points of contact, use of upper body, and use of lower body, which should be instructed during climbing lessons for novice climbers [32]. The climbing performance of all participants was filmed before and after the lesson. Afterward, four instructors, who were sport climbing national team players and did not participate in the experiment, discussed and evaluated each item of the performance on a scale of 1 to 5 points.
 (a) (b)
Fig. 6. (a) Traditional sport climbing lessons and (b) augmented reality sport climbing lesson.

Data Analysis
This study used SPSS Statistics version 23 for statistical analyses (IBM, Armonk, NY, USA). The statistical significance was determined at p< 0.05. The mean and standard deviation of the climbing performance evaluation scores were calculated. To minimize the effects of pre-test, ANCOVA was performed while using the pre-test score as a covariate.

Results

The results showed that the three points of contract score of the traditional climbing instruction group was 1.80 (mean) before instruction and it increased to 3.00 after instruction (1.20 points increase). Moreover, the three points of contract score of the augmented reality affordance group was 2.20 before instruction and it increased to 3.65 (1.45 points increase) (Table 1).The results also showed that the efficient use of upper body score of the traditional climbing instruction group was 1.50 (mean) before instruction and it increased to 2.30 after instruction (0.80 points increase). Moreover, the efficient use of upper body score of the augmented reality affordance group was 1.05 before instruction and it increased to 2.00 (0.95 points increase).The results revealed that the efficient use of lower body score of the traditional climbing instruction group was 2.15 (mean) before instruction and it increased to 3.05 after instruction (0.90 points increase). Moreover, the efficient use of lower body score of the augmented reality affordance group was 2.00 before instruction and it increased to 3.45 (1.45 points increase).

Table 1. Comparison of motor performance evaluations between groups

Factor Traditional climbing Augmented reality affordance
Three points of contact Pre 1.80±0.69 2.20±0.61
Post 3.00±0.21 3.65±0.15
Efficient use of upper body Pre 1.50±0.60 1.05±0.92
Post 2.30±0.22 2.00±0.72
Efficient use of lower body Pre 2.15±0.67 2.00±0.64
Post 3.05±0.75 3.45±0.68
Values are presented as mean±standard deviation.

The probability of the Levene’s test was 0.5 or higher. Therefore, equal variance was assumed (Table 2).
The sports climbing performance evaluation scores of the two groups were not significantly different. However, it was found that the three performance evaluation scores of the augmented reality affordance group increased slightly more than those of the traditional climbing instruction group (Table 3).

Table 2. Levene’s test for evaluating motor performance
Factor $F$ $df1$ $df2$ $p-value$
Three points of contact 2.348 1 38 0.134
Efficient use of upper body 0.849 1 38 0.213
Efficient use of lower body 0.302 1 38 0.586

Table 3. Covariance analysis of motor performance evaluation
Factor Source of variance Sum of square df Mean square $F$ $p-value$
Three points of contact Pre-test 5.388 1 5.388 9.420 0.004
Group 1.613 1 1.613 2.820 0.102
Error 21.162 37 0.572 - -
Efficient use of upper body Pre-test 1.132 1 1.132 1.671 0.204
Group 0.135 1 0.135 0.199 0.658
Error 25.068 37 0.678 - -
Efficient use of lower body Pre-test 4.637 1 4.637 11.300 0.002
Group 0.395 1 0.395 0.963 0.333
Error 14.772 37 0.410 - -

Discussion

This study compared the traditional climbing instruction and augmented reality affordance. This study treated the instruction method to be applied as an independent variable and three points of contact, use of upper body, and use of lower body as dependent variables to evaluate the effects on motor performance evaluation. The two groups did not show a significant difference in three points of contact, use of upper body, and use of lower body.
The following is the discussion of the results obtained by comparing and analyzing the performance of the two groups.
First, augmented reality affordance can improve understanding and application capability by visualizing complex postures and movements in a real 3D space [33]. Augmented reality affordance can draw attention for a relatively long time because it can be accessed only by sensory functions without using a special cognitive action. It will develop muscles and enhance motor performance abilities by increasing the time to focus on the physical activity itself and revealing the potential of the body.
Second, utilizing augmented reality affordance induces voluntary participation in physical activities by stimulating immersion and interest. Augmented reality enables users to enjoy multisensory immersion in a virtual character while maintaining the context of the real world. This sensory immersion makes users feel the movement of the character as real and stimulates the interest and curiosity of them to allow active participation and to increase activity immersion. In particular, the projection-based augmented reality can maximize the user’s immersion by projecting a virtual character directly on an actual artificial rock wall. It could induce natural actions to users by having them touch and grab the hold on the augmented artificial rock wall. Moreover, it was observed that projection-based augmented reality improved participation in class by having all students participating in the class share a virtual character in the real world, not like HMD or a mobile device, which provides a virtual character only to a person wearing it. This agreed with the results of previous study that increased users’ participation and interest by using games and route guidance in the projection-based interactive climbing system [34].
Third, the process of observational learning that observes the character’s demonstration in real-time while performing movements affected motor performance positively. The movement of a climbing character stimulated the cranial nerves of the experiment participants through observation and imitation. In other words, visual information in the form of animation that can be learned through observation should be appropriately utilized to effectively construct an affordance environment for performing an exercise. Particularly for complex movements, the structure of observational learning should be visualized in the same form that an observer experiences during learning, and the task of the whole movement, the nature and characteristics of the partial movement, and their relationship should be provided. Therefore, it is believed that it positively affects motor performance because users focus on the body movements in the process of mimicking the animation of the character provided by augmented reality affordance and climbing the wall and control the body to obtain knowledge about unfamiliar movements in real-time.

Conclusion

The augmented reality space has affordance that can induce people who are not familiar with the action to imitate and learn it easily by providing a virtual character. The virtual character provided to the user in the augmented reality space presents a specific situation related to climbing to a real-world rock climber. The action of the user who is synchronized with the movement of this virtual character and climbs along real holds is different from the conscious movement of climbing the wall by looking at the hold and thinking about the route. In other words, it can be observed that the user climbs the rock wall almost automatically in a state close to unconscious. In particular, it is believed that automatic movement impacted motion performance positively since unconscious processing is necessary to ensure accuracy [23].
In the field of motor learning, various studies have been conducted for effective learning using minimal effort and time. Augmented reality affordance can provide concrete and clear clues in real-time. This feature will be very effective when a novice is learning a complex motion or practicing a motion repetitively. Although affordance is one of the topics that have already been studied in various fields, affordance has not been studied sufficiently for effective learning in the field of motor learning. Therefore, this study applied it to sport climbing to evaluate its potential as a tool for motor learning in order to test the effect of augmented reality affordance on motor performance. However, it cannot be argued that the effect of AR affordance on motor performance for learning an exercise can be proved solely based on the results of this study. Therefore, suggestions for future studies are as follows. First, although this study measured motor performance, a temporary change through training, future studies are needed to evaluate the motor learning effects of augmented reality affordance as a permanent change by measuring the member and grabbing level over a long period of time according to the changes in performance levels. Second, this study presented affordance using projection-based AR technology suitable for the characteristics of sport climbing. Therefore, future studies are necessary to examine affordances that can improve motor performance by utilizing augmented reality technologies suitable for various fields. Third, this study examined the effect of augmented reality affordance on relatively large movements requiring low precision, but future studies need to evaluate augmented reality affordance for performing more sophisticated movements. It is expected that it can be used as a very effective learning tool for occupation training situations where a user needs to repeat the same situation under a realistic condition.

Acknowledgements

Not applicable.

Author’s Contributions

Conceptualization, MH, DH. Funding acquisition, MH. Investigation and methodology, MH. Project administration, MH. Resources, DH. Supervision, DH. Writing of the original draft, MH. Writing of the review and editing, MH, DH. Software, DH. Validation, MH. Data Curation, MH. Visualization, MH, DH.

Funding

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2019R1I1A1A0106373) and by the Ministry of Science and ICT, Korea, under the Information Technology Research Center support program(No. IITP-2021-2018-0-01419) supervised by the Institute for Information & Communications Technology Planning & Evaluation(IITP).

Competing Interests

The authors declare that they have no competing interests.

Author Biography

Name : Myeong-Hyeon Heo
Affiliation : Dept. of ICMC Convergence Technology, Soongsil University
Biography :
He received the B.S. degree in Physical Education from Korea National Sports University, Korea, in 2012, and M.S. degree in Department ofSports Information Technology, SoongsilUniversity in 2014, and Ph.D. degree in Department of ICMC Convergence Technology, SoongsilUniversity in 2019. He is currently a Researcherin Department of ICMC Convergence Technology, SoongsilUniversity. His research interests include mixed-reality, motor learning, and sports information technology.

Name : Dongho Kim
Affiliation : Dept. of Digital Media, Soongsil University
Biography :
He received the B.S. degree in Electronics Engineering from Seoul National University, Korea, in 1990, and M.S. degree in Electrical Engineering from KAIST, Korea, in 1992, and Ph.D. degree in Computer Science from the George Washington University, USA, in 2003. He is currently a Professor in Global School of Media, Soongsil University, Korea. His research interests include augmented reality, metaverse content, and sports information technology.

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Myeong-Hyeon Heo1 and Dongho Kim2,*, Effect of Augmented Reality Affordance on Motor Performance: In the Sport Climbing, Article number: 11:40 (2021) Cite this article 4 Accesses