XGBoost based machine learning approach to predict the risk of fall in older adults using gait outcomes

XGBoost based machine learning approach to predict the risk of fall in older adults using gait outcomes

Abstract This study aimed to identify the optimal features of gait parameters to predict the fall risk level in older adults. The study included 746 older adults (age: 63–89 years). Gait tests (20 m walkway) included speed modification (slower, preferred, and faster-walking) while wearing the inerti...

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Autores principales: Byungjoo Noh, Changhong Youm, Eunkyoung Goh, Myeounggon Lee, Hwayoung Park, Hyojeong Jeon, Oh Yoen Kim
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Medicine
R
Science
Q
Acceso en línea:https://doaj.org/article/17d7e71570154b499afc0ec772378862
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