Takes Two to Tango: Digital Twins and AI Revolutionize Sports Science and Medicine
Purpose: Technological advancements are transforming the field of sports science and medicine, leading to a new era of performance improvement and injury prevention. Digital twins and artificial intelligence (AI) are at the forefront of these innovations, working together to redefine athletic traini...
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| Published in | Acta kinesiologica Vol. 18; no. N2 2024; p. 56 |
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| Main Author | |
| Format | Journal Article |
| Language | Croatian English |
| Published |
Ljubuski
DPTZK
01.06.2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1840-2976 1840-3700 |
| DOI | 10.51371/issn.1840-2976.2024.18.2.7 |
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| Abstract | Purpose: Technological advancements are transforming the field of sports science and medicine, leading to a new era of performance improvement and injury prevention. Digital twins and artificial intelligence (AI) are at the forefront of these innovations, working together to redefine athletic training and monitoring. This editorial offers a comprehensive overview of the integration of digital twins and AI in sports science, with a focus on their potential applications, challenges, and future developments. By utilizing sensor data, AI algorithms, and biometrics, digital twins create virtual replicas of athletes, enabling precise performance monitoring and personalized training programs.
Conclusions: Large datasets generated by AI can be used to predict and prevent injuries, as well as to enhance communication among stakeholders. Despite the promises, challenges such as privacy concerns and data accuracy need to be addressed. Future advancements will concentrate on sensor accuracy, AI algorithm refinement, and broader applications. The editorial highlights exciting research opportunities, including predictive injury models, real-time performance monitoring, and
longitudinal health studies. Ultimately, the collaboration between digital twins and AI represents a paradigm shift in sports science, with the potential to revolutionize athlete well-being and performance optimization. |
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| AbstractList | Purpose: Technological advancements are transforming the field of sports science and medicine, leading to a new era of performance improvement and injury prevention. Digital twins and artificial intelligence (AI) are at the forefront of these innovations, working together to redefine athletic training and monitoring. This editorial offers a comprehensive overview of the integration of digital twins and AI in sports science, with a focus on their potential applications, challenges, and future developments. By utilizing sensor data, AI algorithms, and biometrics, digital twins create virtual replicas of athletes, enabling precise performance monitoring and personalized training programs.
Conclusions: Large datasets generated by AI can be used to predict and prevent injuries, as well as to enhance communication among stakeholders. Despite the promises, challenges such as privacy concerns and data accuracy need to be addressed. Future advancements will concentrate on sensor accuracy, AI algorithm refinement, and broader applications. The editorial highlights exciting research opportunities, including predictive injury models, real-time performance monitoring, and
longitudinal health studies. Ultimately, the collaboration between digital twins and AI represents a paradigm shift in sports science, with the potential to revolutionize athlete well-being and performance optimization. Purpose: Technological advancements are transforming the field of sports science and medicine, leading to a new era of performance improvement and injury prevention. Digital twins and artificial intelligence (AI) are at the forefront of these innovations, working together to redefine athletic training and monitoring. This editorial offers a comprehensive overview of the integration of digital twins and AI in sports science, with a focus on their potential applications, challenges, and future developments. By utilizing sensor data, AI algorithms, and biometrics, digital twins create virtual replicas of athletes, enabling precise performance monitoring and personalized training programs. Conclusions: Large datasets generated by AI can be used to predict and prevent injuries, as well as to enhance communication among stakeholders. Despite the promises, challenges such as privacy concerns and data accuracy need to be addressed. Future advancements will concentrate on sensor accuracy, AI algorithm refinement, and broader applications. The editorial highlights exciting research opportunities, including predictive injury models, real-time performance monitoring, and longitudinal health studies. Ultimately, the collaboration between digital twins and AI represents a paradigm shift in sports science, with the potential to revolutionize athlete well-being and performance optimization. |
| Author | Nobari, Hadi |
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| Title | Takes Two to Tango: Digital Twins and AI Revolutionize Sports Science and Medicine |
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