With the rapid development of computer science and information technology, artificial intelligence (AI) has been developed from theory to application. As a key technology in the modern society, AI is increasingly affecting all aspects of people’s daily lives, including sports training. AI can be considered as an assistive technology to provide specific support to athletes’ physical education training through various means such as data analysis and simulation of training scenarios. Although research on AI is still in the preliminary stage, it is significant to explore how AI can be applied in sports training since this emerging technology could facilitate people’s physical training to some extent. This paper first reviews the existing research on AI applications. Then, based on the fundamental concept and related research results of AI, this study explores three specific cases of AI application in sports training and explains the main principles. This research focuses on discussing the strong relationship between AI technology and physical education training and highlights the advantages of AI, including utilization, convenience, and innovation.
As a discipline created in the 1950s, artificial intelligence (AI) is defined as the ability of a system to interpret and learn from exterior data correctly and to adopt the learning results to achieve specific objectives and solve problems through flexible adaptation [
Currently, AI has also emerged in the field of sports. It has the potential of sustainable development in physical education training as long as the fundamental theoretical structure appropriate for this goal is built when integrating with other fields. As in most other areas of society, an increasing amount of data is being collected in different physical activities, and the utilization of AI for automated data analysis has become an important research direction. Since traditional statistical methods are slow and inaccurate, automated data analysis with AI has been widely used. AI can simulate human learning, thinking, perception, and actions using advanced computer algorithms and actually the AI system is self-learning [
Physical education technology belongs to many fields such as sports, education, and computer science [
In order to better apply AI technology to this area, many studies have been conducted to explore the integration of computer technology with the physical movement of the human body. For example, Lei developed a badminton technical feature statistics and pace training system, which can achieve two major functions of badminton game technical statistics and player’s pace training based on the badminton action recognition algorithm [
The above examples show that if the data of athletes’ movements and various physical indicators can be grasped in real time during physical training, then the corresponding instructional plans can be gained through computer processing, and timely feedback can be provided for better physical training. However, previous research has not systematically investigated the integrated application of AI in physical education training. Although the previous studies are specific, they lack a more complete summary of the application of AI in sports training. Also, there has been little research to explore the application of AI to physical education training although AI is significant in improving the sports training system in the future. Therefore, according to the main concepts and principles of AI, this study explores the various implementations of AI on facilitating people’s physical training and provides several real cases to analyze the main application of AI. Meanwhile, the principles of each case analysis are revealed to better explain how AI can achieve scientific and efficient work.
Wearable smart sports products refer to digital products that can take the form of accessories or clothing. They are designed to use modern information networks and various sensor technologies to record various vital data to monitor the body’s overall physical state [
The design model of wearable AI devices comes from the Internet development. The hardware core is a variety of physiological information sensors and wearable technologies, while the core technologies at the software level are wireless network transmission and statistical data processing. The technology incorporates sensors, multimedia and wireless communication technologies to enable sensing, and feedback and interactive experiences for basic human body movements. It can collect human physiological parameters during the whole physical training process and can provide athletes with feasible advice through a big data analysis system. For example, smart wearable watches can accurately measure users’ specifics in exercise such as the heart rate (Figure
Smart wearable watches.
The Wearable Devices Research Report released by the China Academy of Information and Communication Technology points out that the market size of smart wearable products in China has reached 12.5 billion yuan in 2015, with a growth rate of an astonishing 471%, and the rapid development of wearable artificial intelligence products from the world has been the trend of the development of the Internet of Things. Therefore, wearable AI devices have a quite broad market prospect and huge development potential in the field of modern physical education training.
The MySwing Professional is a golfer training auxiliary equipment that can accurately capture the player’s movement and the club’s trajectory based on whole-body movement analysis. It is an AI-based product designed and developed by the Noitom company. This device includes 17 wireless full-body sensor nodes and connected wearable retractable straps with built-in wireless antennas and preinstalled MySwing software for real-time playback and cloud storage, which is shown in Figure
Real-time playback and cloud storage functions of MySwing Professional.
The MySwing Professional has three main functions to achieve the effect of AI technology completely: motion capture, playback analysis, and storage comparison. The specific details of each function are shown below.
Before starting, the player first puts on a full-body wireless motion capture suit and simply calibrates it; then, MySwing Professional would record the player’s movements in precise details. Actually, the function of motion capture is achieved by sensors worn throughout the player’s body and sensors on the club that record every movement with precision. The sensors are key to realize this function since the data collected from the sensor coordinate frame can be transformed to the computer by estimating the sensor orientation [
Quantifying sports data is crucial to the game of golf because the analysis of data can help players improve their movements. In response to this need, MySwing Professional provides a comprehensive solution. Players can not only observe their swings in a 3D environment in real time but also analyze the angle and acceleration of their swings through playback, making the state of motion easier to grasp. Since the 3D model, analysis chart, and other auxiliary reference tools have the characteristics of data visualization, players can observe and analyze their own swings from a comprehensive perspective and compare them with more skilled professional golfers. Therefore, this function is quite essential to the improvement of player’s ability.
The MySwing Professional will upload a golfer’s movement data from every session to a cloud-based server, so they can keep track of their level changes through the data and compare it to the movement data of professional golfers. This function is reasonably practical and useful to players since each of their exercises can be stored, and then they can use these records to review the details of their previous movements.
Actually, MySwing Professional is already in use and has been adopted by many famous players in their daily training. For example, DeChambeau, a champion professional golfer in the United States, utilizes MySwing Professional to watch his shots from all angles and compare them side by side with other professionals’ movements on record to find out where his movements are lacking and continuously adjust to his best level.
In summary, MySwing Professional has many advantages such as convenience and intelligence in practical use. It can help players to perform better in their daily training in order to improve their relevant skills. Thus, it is a successful example of combining AI with physical education training.
Real-time tracking of athletes’ movement and their position as well as targeted coaching plans are vital in physical education training [
The visual target tracking system mainly consists of four parts: target detection, target recognition, target processing, and target display (Figure
Main parts of visual target tracking system.
Firstly, the visual target tracking system can detect the trajectory of the target’s movement by using an image detection module. This module is mainly composed of cameras that could capture the image of the target. In order to accurately obtain the target’s position, posture, and other information, it is necessary to install the corresponding cameras around the target following a specific topology to obtain the target’s image information in real time. In this part, the topology is essential because the topology between different regions performs a key role in obtaining various visual relationships [
In team sports, the tactical coordination and choice of tactics between athletes is an important factor in determining the game. Therefore, it is necessary to continuously track and analyze the athletes’ movements during the competition so that they can be better trained during the day. The technical and tactical analysis methods vary from sport to sport, but the basic steps are similar. Firstly, the raw data is collected, and then the valid information is extracted. The last step is to analyze the data in depth. In most official competitions, athletes are not allowed to wear additional equipment, so the information collection method is mainly visual based. Hence, the visual target tracking system based on AI can be applied in this situation.
SportVU is an intelligent basketball game analysis system that has been widely applied in NBA. It uses six cameras suspended from the ceiling of the arena to track players and basketballs to analyze every dribble, pass, distance to teammates, and distance run during the game (Figure
SportVU system.
Before the start of each basketball game, the SportVU operator has to set up the system, which includes setting the sensors to follow the players, marking the court boundaries, and assigning individual player profiles to the detected objects. The process is as follows: Three high-definition cameras or sensors are placed at the console, each recording one-third of the playing field. The live video is recorded into the computer system, where the lines of sight of the three cameras converge to form the playing field. Any object on the field (player, referee, and ball) appears as a dot on the operator’s computer screen. The software can track players’ movements through these dots.
The SportVU system could track every player’s movement on the court, and the increased access to information has led to a significant increase in the amount of data to be processed. However, SportVU users generally believe that the proportion of data used is less than 10% of the total data provided by the system, and the importance of developing AI technologies to exploit the value of the data better is further highlighted. Thus, some AI algorithms are vital to decipher the patterns of movement behind the data. For example, in the case of a pick-and-roll, the system can identify different screens and determine whether the screener is going to cut in after the screen or cut out after the screen and calculate the success rate for each tactic. All of this is based on AI algorithms to achieve this important function.
In conclusion, as a typical application of a visual target tracking system, SportVU could accurately capture athletes’ movements as well as process and analyze large amounts of data by using AI algorithms. Based on this intelligent system, the coaches are able to master athletes’ information in sports in time and provide some practical training plans which are suitable for them. With this visual target tracking system, the athletes can also train more specific to their own characteristics. Hence, the visual target tracking system based on AI plays a vital role in physical education training in the modern society.
Virtual reality (VR) is an emerging technology that brings together multiple fields such as computer graphics, sensing technology, and AI technology [
The VR simulation system includes multiple perceptual and is interactive and immersive. At the same time, physical education training requires the joint participation of multiple senses of athletes such as vision, hearing, and touch. Therefore, with the continuous development of VR technology, VR-based simulation has been widely used in physical education training (Figure
VR-based simulation system.
The following functions are necessary to VR-based sports’ simulation system.
Some sports such as basketball have special requirements for training venues, so virtual training scenarios and virtual training equipment need to be modeled. In other words, this function is the most fundamental part in the VR training system. It can simulate the real training scenes, thus providing the most basic virtual training scenes for athletes. In this virtual environment, athletes will feel as if they are training in the real world, which means that they would own a great training scenario. Meanwhile, this virtual environment allows them to train even though they do not have a real training field.
The system can provide sensor tracking devices to record data about the athlete directly and analyze it with a computer for simulation. When the athletes are training, the specific devices can automatically store their data such as heart rate and movement speed. The most important feature is that it could capture data from real human movements. The data of athletes in training is quite essential since they can summarize and overview their training state through the data. Therefore, the function of capturing motion data is a necessary part in the VR-based sports simulation system.
Physiological and psychological indicators are important reflections of the athletic state of the athlete. Depending on the type of sport, the physiological and psychological data of athletes can be collected by various sensors. For instance, the collection of physiological data includes metabolic indicators such as pulse rate, blood pressure, and functional indicators of various organs. The collection of psychological data contains the athletes’ mood fluctuations in training.
Action replay is the most significant function of the system. The traditional camera methods cannot work well under some conditions. Some training methods cannot be realized because they are in the innovative stage, but VR can deal with this issue. For example, in gymnastics, coaches can help athletes improve and innovate their movements and improve their skills by modeling the movements of real athletes, creating new movements, and then using VR to simulate the new movements.
The VR sports simulation system can be divided into immersive and nonimmersive systems. The immersive systems require helmet-based 3D stereo displays, stereo glasses, data gloves, stereo headsets, high-performance computers, and some other equipment. These devices allow users to experience realistic stereo vision and stereo hearing to interact with the virtual environment. The nonimmersive system mainly relies on software technology to create a virtual world with rich visual and auditory information. To sum up, the characteristic of immersive systems is expensive but strongly immersive, while the characteristic of nonimmersive systems is cheap and conventional.
QB SIM is a professional training simulation system based on VR, which can be used for daily repetitive training of football players (Figure
QB SIM simulation training system.
The QB SIM simulation training system is built in a real rugby stadium, and by combining OptiTrack motion capture technology and VR virtual reality technology, athletes can get the most realistic training experience. The football itself is a rigid body with motion capture marker points on its surface, and the headset worn by the athlete is also equipped with marker points on its surface. The QB SIM system then uses motion capture technology to obtain the athlete’s positions and the football and set the movements and play of the virtual player in the game, thus enabling efficient training.
By using the QB SIM simulation training system to assist with training, athletes can train more easily when faced with practical problems. For example, it is known that the football game is a team game. Namely, it becomes less realistic if the athletes still wish to train when there are not enough people to train. Nevertheless, the QB SIM simulation training system could enable them to train without other teammates because it can create many virtual people to train with the user.
This paper provides an introduction to the use of AI technology in physical education training and highlights three practical examples. The cases are analyzed carefully through explaining their principles and functions, respectively. Firstly, this study introduces the wearable AI devices and takes MySwing Professional as an example to illustrate the successful application of AI in the golf game. Then, the main parts of the visual target tracking system based on AI are described, and SportVU is chosen to suggest that this system has been widely used in the basketball game of basketball. Finally, the virtual reality sports simulation system is introduced and QB SIM is a typical application of the system in the football game. Thus, the three practical applications of combining AI technology with physical education training indicate that the AI technology can better enhance the traditional sports training. AI could provide precise data analysis and scientific plans which will improve the training efficiency for athletes. Also, some devices based on AI can create virtual training environment, and it is quite conventional for athletes to train. In terms of the impact of our research on practice, it should be noted that innovations in AI are affecting various areas of people’s lives. Therefore, the implementation of AI in other areas should be discussed more. In conclusion, as a new and rapidly developing technology, AI technology will affect more and more people in the future.
All data generated or used during the study are available within the article.
The authors declare that they have no conflicts of interest regarding the publication of this paper.