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Fall detection - Principles and Methods

Noury, N., Fleury, A., Rumeau, P., Bourke, A.K., Laighin, G. O, Rialle, V., Lundy, J.E.·2007·2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
DOI 10.1109/iembs.2007.4352627
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Abstract

Fall detection of the elderly is a major public health problem. Thus it has generated a wide range of applied research and prompted the development of telemonitoring systems to enable the early diagnosis of fall conditions. This article is a survey of systems, algorithms and sensors, for the automatic early detection of the fall of elderly persons. It points out the difficulty to compare the performances of the different systems due to the lack of a common framework. It then proposes a procedure for this evaluation.

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Metadata

Authors
Noury, N., Fleury, A., Rumeau, P., Bourke, A. K., Laighin, G. O., Rialle, V., & Lundy, J. E.
Venue
2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Publisher
IEEE
Published
2007-08
Volume
2007
Pages
1663-1666
ISSN
1557-170X (ISSN-L)
DOI
10.1109/iembs.2007.4352627
OpenAlex
W2170672895
Cited by
615
References
0
FWCI
19.71
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Fall detection - Principles and Methods. https://app.cochat.ai/papers/10.1109/iembs.2007.4352627
The paper
Noury, N., Fleury, A., Rumeau, P., Bourke, A. K., Laighin, G. O., Rialle, V., & Lundy, J. E. (2007). Fall detection - Principles and Methods. 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. https://doi.org/10.1109/iembs.2007.4352627

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.