Biomechanics in Sport and Ageing: Artificial Intelligence

Dear Colleagues,

The aim of this special issue is to provide a scientific platform for a state-of-the-art update on the progress of artificial intelligence, AI, in sport biomechanics and ageing. AI relies on computers to execute commands that historically required human intelligence. As we can surmise it from Turing’s seminal paper, AI builds computational units that mimic human intelligence and abilities: language, communication, comprehension of concepts, automated thinking, (machine) learning, computer vision, and movements via robotics [1]. Supervised or unsupervised machine learning, i.e., the science of coding computers to learn and behave as humans do, as a subset of AI, allows us to discern patterns and structure in data. Deep learning optimizes supervised learning and trains models to learn how to map an input to an expected output [2]. These tools of AI are also becoming ubiquitous in sport biomechanics and ageing research. Sport and ageing might appear unrelated. However, sport and ageing are complementary: assessment and training methods developed in sport science are transformed to improve diagnosis and treatment of ageing-related impairments. Along the spectrum from low to high levels of physical and cognitive function, the current special issue highlights how AI is leveraged to assess and increase top performance, predict motor and cognitive function, and ultimately deliver improved care for all individuals across the lifespan, including athletes and seniors [3].

References

1. Turing, A.M. On computable numbers, with an application to the Entscheidungsproblem. Proc. London Math Soc. 1936, 58, 230–65.
2. LeCun, et al. Deep learning. Nature 2015, 521, 436–44.
3. Zhang, et al. Leveraging physiology and artificial intelligence to deliver advancements in health care. Physiol. Rev. 2023, 103, 2423–50.

Prof. Dr. Tibor Hortobagyi
Guest Editor

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• artificial intelligence
• machine learning
• deep learning
• neural networks
• biomechanics
• wearables
• sport
• kinesiology
• ageing