This paper is in the following e-collection/theme issue:

Artificial Intelligence (722) Assisted Living for the Elderly and Nursing Home Care (118) Dementia and Cognitive Decline (325) Telehealth and Telemonitoring (1234) Falls and Emergency Detection with Sensors and other Technologies (21) Falls Prevention in the Elderly (55)

Published on in Vol 23 , No 6 (2021) :June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17551, first published .
Reduction of Time on the Ground Related to Real-Time Video Detection of Falls in Memory Care Facilities: Observational Study

Reduction of Time on the Ground Related to Real-Time Video Detection of Falls in Memory Care Facilities: Observational Study

Reduction of Time on the Ground Related to Real-Time Video Detection of Falls in Memory Care Facilities: Observational Study

Authors of this article:

Eleonore Bayen 1, 2 Author Orcid Image ;   Shirley Nickels 3 Author Orcid Image ;   Glen Xiong 4 Author Orcid Image ;   Julien Jacquemot 3 Author Orcid Image ;   Raghav Subramaniam 3 Author Orcid Image ;   Pulkit Agrawal 3, 5 Author Orcid Image ;   Raheema Hemraj 3 Author Orcid Image ;   Alexandre Bayen 6 Author Orcid Image ;   Bruce L Miller 2 Author Orcid Image ;   George Netscher 3 Author Orcid Image
Article Authors Cited by (1) Tweetations (11) Metrics

Journals

  1. O'Connor S. Artificial Intelligence for Older Adult Health: Opportunities for Advancing Gerontological Nursing Practice. Journal of Gerontological Nursing 2022;48(12):3 View