RT Journal Article
T1 An analytical comparison of datasets of Real-World and simulated falls intended for the evaluation of wearable fall alerting systems
A1 Casilari-Pérez, Eduardo
K1 AccelerometerDatasetWearable device
K1 Sistemas informáticos
AB Automatic fall detection is one of the most promising applications of wearables in the field of mobile health. The characterization of the effectiveness of wearable fall detectors is hampered by the inherent difficulty of testing these devices with real-world falls. In fact, practically all the proposals in the literature assess the detection algorithms with ‘scripted’ falls that are simulated in a controlled laboratory environment by a group of volunteers (normally young and healthy participants). Aiming at appraising the adequacy of this method, this work systematically compares the statistical characteristics of the acceleration signals from two databases with real falls and those computed from the simulated falls provided by 18 well-known repositories commonly employed by the related works. The results show noteworthy differences between the dynamics of emulated and real-life falls, which undermines the testing procedures followed to date and forces to rethink the strategies for evaluating wearable fall detectors.
PB Elsevier
YR 2022
FD 2022-10
LK https://hdl.handle.net/10630/24944
UL https://hdl.handle.net/10630/24944
LA eng
NO Eduardo Casilari, Carlos A. Silva, An analytical comparison of datasets of Real-World and simulated falls intended for the evaluation of wearable fall alerting systems, Measurement, Volume 202, 2022, 111843, ISSN 0263-2241, Eduardo Casilari, Carlos A. Silva, An analytical comparison of datasets of Real-World and simulated falls intended for the evaluation of wearable fall alerting systems, Measurement, Volume 202, 2022, 111843, ISSN 0263-2241, https://doi.org/10.1016/j.measurement.2022.111843
NO Funding for open access charge: Universidad de Málaga / CBUA. This research was funded by FEDER Funds (under grant UMA18-FEDERJA-022), Andalusian Regional Government (-Junta de Andalucía- grant PAIDI P18-RT-1652) and Universidad de Málaga, Campus de Excelencia Internacional Andalucia Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026