Skip to main content
. 2017 Jun 27;17(7):1513. doi: 10.3390/s17071513

Table 1.

Basic characteristics of public datasets of falls and Activities of Daily Living (ADLs).

Dataset Ref. Authors Institution City (Country) Year
DLR [29] Frank et al. German Aerospace Center (DLR) Munich (Germany) 2010
MobiFall
MobiAct
[30]
[31]
Vavoulas et al. BMI Lab (Technological Educational Institute of Crete) Heraklion (Greece) 2013
2016
TST Fall detection [32] Gasparrini et al. TST Group (Universita Politecnica delle Marche) Ancona (Italy) 2014
tFall [33] Medrano et al. EduQTech (University of Zaragoza) Teruel (Spain) 2014
UR Fall Detection [34] Kępski et al. Interdisciplinary Centre for Computational Modelling (University of Rzeszow) Krakow (Poland) 2014
Cogent Labs [35] Ojetola et al. Cogent Labs (Coventry University) Coventry (UK) 2015
Gravity Project [36] Vilarinho et al. SINTEF ICT Trondheim (Norway) 2015
Graz [37] Wertner et al. Graz University of Technology Graz (Austria) 2015
UMAFall [38] Casilari et al. Dpto. Tecnología Electrónica (University of Málaga) Málaga (Spain) 2016
SisFall [39] Sucerquia et al. SISTEMIC. Univ. of Antioquia Antioquia (Colombia) 2017
UniMiB SHAR [40] Micucci et al. Department of Informatics, Systems and Communication (University of Milano) Bicocca, Milan (Italy) 2017