Wearable Sensor-Based Fall Detection is a fall detection methodology that utilizes data from body-worn sensors to automatically identify accidental falls by analyzing motion and physiological signals in real time.
242
Publications
13.8K
Citations
896
Authors
354
Institutions
Publications per year
2017–2026
128
Parents
Publications
242
SisFall: A Fall and Movement Dataset
Angela Sucerquia, José David López, J. F. Vargas‐Bonilla · Sensors · 2017 · 484 citations · Full text
Wearable Sensors for Reliable Fall Detection
J. Chen, K. K. Kwong, David C. Chang et al. · 2005 · 447 citations
UP-Fall Detection Dataset: A Multimodal Approach
Lourdes Martínez-Villaseñor, Hiram Pönce, Jorge Brieva et al. · Sensors · 2019 · 386 citations · Full text
1–5 of 242
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1–5 of 896
Institutions
354
University of Limerick
Limerick, Ireland
6 h-index
30 publications
2.8K citations
Ollscoil na Gaillimhe – University of Galway
Galway, Ireland
5 h-index
8 publications
725 citations
Centre National de la Recherche Scientifique
Paris, France
5 h-index
15 publications
1K citations
Simon Fraser University
Burnaby, Canada
5 h-index
15 publications
1.1K citations
University of Michigan
Ann Arbor, United States
5 h-index
23 publications
475 citations
Chinese Academy of Sciences
Beijing, China
4 h-index
13 publications
300 citations
The University of Adelaide
Adelaide, Australia
4 h-index
15 publications
966 citations
Marche Polytechnic University
Ancona, Italy
4 h-index
21 publications
2.1K citations
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Venues
- Sensors
31 publications · 2.6K citations
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- IEEE Sensors Journal
11 publications · 1.4K citations
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- IEEE Access
6 publications · 316 citations
6
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- Measurement
5 publications · 274 citations
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- PLoS ONE
4 publications · 226 citations
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