How is AI used to prevent injuries and improve performance for athletes?

In recent years, advances in AI technology have led to the introduction of AI in various industrial fields, and the wave is also rushing to 'sports.' The Wall Street Journal, a major American economic newspaper, summarizes 'How is AI introduced and utilized in the sports field?'

How AI Could Help Predict—and Avoid—Sports Injuries, Boost Performance --WSJ

Your body is an important tool for athletes, and practice to improve performance and care to prevent injuries are indispensable for an athlete to play an active role. Stephen Smith, CEO of Kitman Lab , a data analysis solution for professional sports teams, said, 'There are athletes who treat their bodies like businesses and use data and information to manage themselves. In the future, more athletes will be able to play longer and at higher levels. '

For example, a baseball app called Mustard compares how movements differ from professional movements based on data taken from the user's play, and provides more efficient body movements and training methods. I am. Rocky Corris, co-founder and CEO of Mustard, claims that Mustard is designed to improve the performance of enthusiastic players and avoid long-term injuries and pain-causing movements.

by Mustard

Data analysis based on computer vision and AI is also widespread in sports other than baseball, such as golf and soccer.

Liverpool FC , a prestigious English Premier League football club, is collaborating with Google's AI developer DeepMind to conduct tactical analysis and uses AI to prevent athlete injuries in Zone 7 . After introducing the analysis program, the number of injured athletes has dropped to one-third of the previous year. The Zone 7 program adjusts training methods and suggests the best time to rest.

American figure skaters who participated in the 2022 Beijing Olympics also tracked fatigue using the New Jersey-based 4D Motion Sports motion analysis program. According to Lindsay Slater, sports science manager for the American figure skating team, the athletes' data was collected on a small device attached to the waist, and the athletes and coaches reviewed the motion data after practice.

'We have perfected the algorithm to the point where we can actually clearly define the takeoff and landing of the jump, and we can now estimate that the stress on the hip and trunk from the jump is quite high.1 We also found that during the day the athlete's angular speed slowed down, jump heights dropped, and more jumps were cheated, where chronic overuse was prone to injury. '.

Sports analysis experts will find out how much the athlete's joints are bent and how high they are jumping during the match as AI analysis based on ultra-high resolution video footage such as drones becomes widespread over the next few years. We anticipate that it will be possible to measure the risk of injury in real time based on factors such as how fast you are running. Unlike data collection based on wearable devices, visual data has the advantage that the accuracy of the device does not affect the data quality and it can be collected remotely without worrying about failure.

On the other hand, there are some issues to be solved when introducing algorithms for player performance analysis and injury risk calculation by AI. For example, it is not easy to measure performance because it is not only the physical condition that affects performance, but also various factors such as relationships, psychological stress such as contract negotiations, and the previous night's diet. Also, to really check the accuracy of the algorithm, 'check if you actually get injured if you don't intervene in a player flagged by AI as having a high risk of injury.' However, this test is difficult to perform due to ethical issues.

In addition, there are privacy concerns such as 'how do you manage player data and who you want to allow access to?' At the time of writing, there is no law in the United States prohibiting companies from collecting and using training data for athletes, but the White House aims to introduce rules that use AI and personal data management, and will be in the law in the future. There is a possibility that regulations will be set.

Player data analysis by AI is useful not only for preventing injuries and improving performance, but also for finding outstanding players who are worth acquiring. Based in Paris, France, Skill Corner analyzes video data from TV broadcasts of football leagues around the world and measures the performance of individual players to help scouts.

Paul Neilson, general manager of Skill Corner, believes that AI algorithms are unlikely to completely replace human coaches. 'During the match, coaches can also be there to smell, feel, and touch. I think it's still unlikely that such decision makers will listen to information from artificial intelligence. 'Neilson said.

in Software, Posted by log1h_ik