Pathway of Trends and Technologies in Fall Detection: A Systematic Review.

Tanwar, Rohit; Nandal, Neha; Zamani, Mazdak; Manaf, Azizah Abdul

Tanwar, Rohit; Nandal, Neha; Zamani, Mazdak; Manaf, Azizah Abdul.

Afiliación

Tanwar R; School of Computer Science, University of Petroleum & Energy Studies, Dehradun 248007, India.
Nandal N; Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad 500090, India.
Zamani M; Department of Computer Science, New York University, New York, NY 10012, USA.
Manaf AA; Independent Researcher, Kuala Lumpur 54100, Malaysia.

Healthcare (Basel) ; 10(1)2022 Jan 17.

Article en En | MEDLINE | ID: mdl-35052335

RESUMEN

Falling is one of the most serious health risk problems throughout the world for elderly people. Considerable expenses are allocated for the treatment of after-fall injuries and emergency services after a fall. Fall risks and their effects would be substantially reduced if a fall is predicted or detected accurately on time and prevented by providing timely help. Various methods have been proposed to prevent or predict falls in elderly people. This paper systematically reviews all the publications, projects, and patents around the world in the field of fall prediction, fall detection, and fall prevention. The related works are categorized based on the methodology which they used, their types, and their achievements.

Palabras clave

fall detection; fall prediction; fall prevention; fall risk factors; gait assessment

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Idioma: En Revista: Healthcare (Basel) Año: 2022 Tipo del documento: Article País de afiliación: India Pais de publicación: Suiza

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