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

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 inertial measur...

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Detalles Bibliográficos
Autores principales: Noh, Byungjoo, Youm, Changhong, Goh, Eunkyoung, Lee, Myeounggon, Park, Hwayoung, Jeon, Hyojeong, Kim, Oh Yoen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190134/
https://www.ncbi.nlm.nih.gov/pubmed/34108595
http://dx.doi.org/10.1038/s41598-021-91797-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190134/
https://www.ncbi.nlm.nih.gov/pubmed/34108595
http://dx.doi.org/10.1038/s41598-021-91797-w

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