Feasibility of using floor vibration to detect human falls

Shao, Y., Wang, X., Song, W. et al. (3 more authors) (2021) Feasibility of using floor vibration to detect human falls. International Journal of Environmental Research and Public Health, 18 (1). 200. ISSN 1660-4601

Abstract

Metadata

Authors/Creators:
  • Shao, Y.
  • Wang, X.
  • Song, W.
  • Ilyas, S.
  • Guo, H.
  • Chang, W.-S.
Copyright, Publisher and Additional Information: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Keywords: fall detection; floor vibrations; machine learning; elderly; health and wellbeing; intelligent system
Dates:
  • Accepted: 25 December 2020
  • Published (online): 29 December 2020
  • Published: 1 January 2021
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > School of Architecture (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 09 Feb 2021 11:10
Last Modified: 09 Feb 2021 11:10
Status: Published
Publisher: MDPI AG
Refereed: Yes
Identification Number: https://doi.org/10.3390/ijerph18010200
Related URLs:

Share / Export

Statistics