Video capture of the circumstances of falls in elderly people residing in long-term care: an observational study.

By S. Robinovitch, F. Feldman, Yijian Yang, R. Schonnop, P. Leung, T. Sarraf, J. Sims-Gould, M. Loughin. The Lancet, 2013

854 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Physical Therapy, Sports Therapy and Rehabilitation

View Paper: https://www.semanticscholar.org/paper/d13d7ee77d0cbb14547b5204b3759120fee1ad51

How researchers see this paper

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In Computer Vision and Pattern Recognition

1. Daniela Micucci
2. Paolo Napoletano
3. Marco Mobilio

Citations in the corpus

• UniMiB SHAR: A Dataset for Human Activity Recognition Using Acceleration Data from Smartphones (2016, background): “In-deed, we were interested in acquiring acceleration data from activities related to movements both because from them it is possible to estimate the overall physical activity performed by a person, and because people are more likely to fall during movements [41].”