A Random Forest Machine Learning Framework to Reduce Running Injuries in Young Triathletes.

Javier Martínez-Gramage Juan Pardo AlbiachIván Nacher MoltóJuan José Amer-CuencaVanessa Huesa MorenoEva Segura-Ortí

Published in: Sensors (Basel, Switzerland) (2020)

The triathletes who had suffered the most injuries ran with increased pelvic drop and less activation in gluteus medius during the first phase of the float phase. Contralateral pelvic drop seems to be an important variable in the incidence of injuries in young triathletes.

Keyphrases

machine learning
rectal cancer
middle aged
risk factors
high intensity
deep learning
neural network