Krishna Shah, M.Optom
Optometrist, Sankara Nethralaya, Chennai, India
The term “sports vision” describes a range of services that optometrists and other eye care professionals for athletes provide. Visual performance in sports is a critical component of athletic success. Whether it is a baseball player picking up the spin on an 80-mile-per-hour curveball, or a soccer goalie trying to predict where the ball will be placed in the corner of his net by virtue of penalty kick from striker standing just twelve yards away, an athlete’s vitals skills are controlled primarily through one thing and that happens to be their vision skills. Recently, however, Artificial Intelligence (AI) has become a major technological leap in sports vision by providing new pathways to train and analyse visual performance.(1)
The Challenges Most Associated with Sports Vision
Vision is incredibly important, yet most athletes deal with a range of vision-related challenges. Poor visual acuity, inability to follow fast-moving objects, and ocular tiredness are some of the common complaints encountered. To help improve sports vision in the past, traditionally used fundamentals include eye exercises and training; specialised glasses or contact lenses; and coaching/manual techniques. These methods have been shown to work, but they undoubtedly lack the customisation and data-driven insights into an athlete’s visual performance.
AI Fundamentals in Sports Vision
Talking about Artificial Intelligence (AI) – simply means making processes performed by human intelligence available to machines, especially computer systems. Artificial Intelligence can process massive amounts of data, detect patterns, and draw conclusions with almost no human interference. With AI in the context of sports vision – it can analyse visual data from practice and competition to provide insights as well as recommendations specific to each athlete.
AI in sport vision
AI-driven software and apps provide personalised vision training programs that help in enhance particular visual skills.(2) These technologies take performance data from the athlete and adjusts difficulty levels or target weak areas.(3) So for instance, an AI app could use eye-tracking technology to see how well a baseball player is tracking pitches and then give the tools of focused exercises in order rather than simply giving them a half-second snapshot.(4)
Visual performance data that has been gathered during games, and from practices can be analysed by Performance Analysis AI. By evaluating reaction times, accuracy and visual attention), AI systems can ascertain which skills an athlete excels at -or could improve upon. This analysis helps coaches and athletes to create tailored training plans that address specific visual deficits. For instance, AI might reveal that a basketball player has slower reaction times when looking to their left, prompting focused training to address this issue. (5)
Figure 1: AI-powered Fantasy Sports for Accurate Data Analytics
(www.intuz.com/blog/ai-powered-fantasy-sports)-
For Injury Prevention and Rehabilitation AI help monitor visual strain/fatigue helping to forewarn actual or potential vision-related injuries. Likewise, customised exercises and progress monitoring by AI-driven rehabilitation programs can aid athletes in recovering from vision injuries. As a case in point, the recovery of an athlete from a concussion could be monitored based on improvements over time in their visual coordination and reaction times by an AI system.
AI-Powered, Real-time Decision-Making Incorporating AI systems directly into visual feedback impact limiters in real-time during competitions so athletes are thinking more clearly when it matters most. An augmented reality display in AI smart glasses could give a soccer player tips on where to find open teammates or which passing lane was the best approach.
Future Directions
The most interesting trend with Sport Vision is the integration of AI technology combined with upcoming technologies like virtual reality (VR) and augmented reality (AR).(6) Virtual and Augmented Reality can be used to create engaging training settings that mirror real-life conditions, helping athletes simulate a visual skill while under controlled unprompted physiological conditions. AI will change the way sports vision training and analysis are performed for greater precision, personalisation, and efficacy within 5-10 years. (7)
Conclusion
Up until recently, sports vision remained untouched by AI with little to no novel methods of improving visual performance through training and data analysis. Every player can process quickly and has a better chance of getting injured as it uses eye skills, lowering with high-quality sports devices brings advocacy.
References:
- Ferreira, J. T. (2000). Sports vision assessment manual. SISA, University of Johannesburg, Sport Vision Department.
- Qureshi, M. (2020). How AI is changing the game in sports performance analysis. Towards Data Science.
- Shellock, F. G., & Prentice, W. E. (2019). Use of artificial intelligence in monitoring and preventing sports injuries. The American Journal of Sports Medicine, 47(1), 28-35.
- Cheng, L., & Brown, M. (2020). Real-time decision making in sports: The role of AI. International Journal of Sports Science & Coaching, 15(2), 171-184.
- Zeng, Z., & Li, Y. (2019). Artificial intelligence in sports: Applications and opportunities. Springer International Publishing
- Kumar, N., & Singh, A. (2019). The impact of AI on sports: Current and future perspectives. AI Review Journal, 52(1), 91-107.
- Trauzettel-Klosinski, S., & Meigen, T. (2019). Artificial intelligence and the future of vision science. Vision Research, 159, 1-9.
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