Personalized machine learning approach to injury monitoring in elite volleyball players-Reference-Cited by-同舟云学术

Personalized machine learning approach to injury monitoring in elite volleyball players

Published:2021-02-25 Issue: Volume: Page:1-10
ISSN:1746-1391
Container-title:European Journal of Sport Science
language:en
Short-container-title:European Journal of Sport Science

Author:

de Leeuw Arie-Willem¹,van der Zwaard Stephan¹²,van Baar Rick³,Knobbe Arno¹

Affiliation:

1. Leiden Institute of Advanced Computer Science (LIACS), Leiden University, Leiden, The Netherlands

2. Department of Human Movement Sciences, Faculty of Behavioral and Movement Sciences, Amsterdam Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

3. The Dutch Volleyball Federation (Nevobo), Utrecht, the Netherlands

Publisher

Informa UK Limited

Subject

Orthopedics and Sports Medicine,Physical Therapy, Sports Therapy and Rehabilitation,General Medicine

Link

https://www.tandfonline.com/doi/pdf/10.1080/17461391.2021.1887369

Reference42 articles.

1. Prediction of Overuse Injuries in Professional U18-U21 Footballers Using Metrics of Training Distance and Intensity

2. Relationships Between Internal and External Training Load in Team-Sport Athletes: Evidence for an Individualized Approach

3. Perceived exertion related to heart rate and blood lactate during arm and leg exercise

4. Accumulated workloads and the acute:chronic workload ratio relate to injury risk in elite youth football players

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