Biology of Sport
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Biology of Sport
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Review paper

Digital twins in sports science: applications for performance enhancement, injury prevention, and rehabilitation through advanced big data analytics and deep learning methodologies – a comprehensive narrative review

Afef Sédiri
1
,
Sabri Barbaria
1
,
Halil Ibrahim Ceylan
2
,
Andrea De Giorgio
3
,
Luca Puce
4
,
Valentina Stefanica
5
,
Nicola Luigi Bragazzi
6
,
Ismail Dergaa
7
,
Hanene Boussi Rahmouni
1

  1. Laboratory of Biophysics and Medical Technologies, LR13ES07 (BTM), University of Tunis Elmanar, Higher Institute of Medical Technologies of Tunis (ISTMT), Tunis, Tunisia
  2. Physical Education and Sports Teaching Department, Faculty of Sports Sciences, Atatürk University, Erzurum 25240, Turkey
  3. Artificial Engineering, Naples 80121, Italy
  4. Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16132 Genoa, Italy
  5. Faculty of Sciences, Physical Education and Informatics, National University of Science and Technology Politehnica Bucharest, Pitesti University Center, Pitesti, Romania
  6. Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada
  7. High Institute of Sport and Physical Education of Ksar Said, University of Manouba, Mannouba 2010, Tunisia
Biol Sport. 2026;43:1271–1291
DOI: https://doi.org/10.5114/biolsport.2026.161106
Online publish date: 2026/04/20
Article file
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