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Using Artificial Intelligence-Enhanced Smartwatches for Performance Optimization in Sports

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Resumo:The integration of artificial intelligence (AI) in sports training, specifically through smartwatch generated insights, has seen a significant change in how athletes optimize performance. This research delves into how athletes perceive and trust the recommendations provided by AI technology while exploring factors such as demographics and smartwatch usage habits that can impact long term performance enhancement, in different sports modalities. Using a quantitative methodology, an online survey was conducted with 114 athletes from diverse backgrounds, collecting data on their interaction with AI technology and adjustments in training routines. The results revealed that the level of trust in AI recommendations is more reliable on factors such as education level, frequency of use, and personal profiles of individual athletes rather than how long the athletes use the smartwatch. Moreover, athletes who frequently adjust their training plans based on AI feedback reported experiencing performance improvements. These findings suggest that, although AI can be used to maximize athletic training, its acceptance depends on how well it aligns with athlete’s individual needs, highlighting the importance of developing more personalized AI tools solutions for sports performance optimization.
Autores principais:Flôr, Rita Falcão
Assunto:Sports Artificial Intelligence Smartwatches Performance SDG 3 - Good health and well-being
Ano:2025
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
Descrição
Resumo:The integration of artificial intelligence (AI) in sports training, specifically through smartwatch generated insights, has seen a significant change in how athletes optimize performance. This research delves into how athletes perceive and trust the recommendations provided by AI technology while exploring factors such as demographics and smartwatch usage habits that can impact long term performance enhancement, in different sports modalities. Using a quantitative methodology, an online survey was conducted with 114 athletes from diverse backgrounds, collecting data on their interaction with AI technology and adjustments in training routines. The results revealed that the level of trust in AI recommendations is more reliable on factors such as education level, frequency of use, and personal profiles of individual athletes rather than how long the athletes use the smartwatch. Moreover, athletes who frequently adjust their training plans based on AI feedback reported experiencing performance improvements. These findings suggest that, although AI can be used to maximize athletic training, its acceptance depends on how well it aligns with athlete’s individual needs, highlighting the importance of developing more personalized AI tools solutions for sports performance optimization.