Fall risk prediction using temporal gait features and machine learning approaches

IntroductionFalls have been acknowledged as a major public health issue around the world. Early detection of fall risk is pivotal for preventive measures. Traditional clinical assessments, although reliable, are resource-intensive and may not always be feasible.MethodsThis study explores the efficac...

詳細記述

書誌詳細

出版年:	Frontiers in Artificial Intelligence
主要な著者:	Zhe Khae Lim, Tee Connie, Michael Kah Ong Goh, Nor ‘Izzati Binti Saedon
フォーマット:	論文
言語:	英語
出版事項:	Frontiers Media S.A. 2024-08-01
主題:	fall risk prediction human pose estimation machine learning computer vision gait features
オンライン･アクセス:	https://www.frontiersin.org/articles/10.3389/frai.2024.1425713/full