Real-Time Injury Risk Assessment in Athletes Based on Relative Joint Angles
Author:
Affiliation:
1. Dwarkadas J. Sanghvi College of Engineering,Dept. of Computer Science and Engineering (Data Science),Mumbai,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10497186/10497189/10497417.pdf?arnumber=10497417
Reference23 articles.
1. An Evidence-Based Videotaped Running Biomechanics Analysis
2. A combined deep neural network and semi-supervised clustering method for sports injury risk prediction
3. Training in spikes and number of training hours correlate to injury incidence in youth athletics (track and field): A prospective 52-week study
4. The functional movement screen predicts sports injuries in Chinese college students at different levels of physical activity and sports performance
5. Cost-effectiveness and implementation process of a running-related injury prevention program (RunIn3): Protocol of a randomized controlled trial
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