Signals from real-world falls

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Abstract
Objective measurement of real-world fall events by using body-worn sensor devices can improve the understanding of falls in older people and enable new technology to prevent, predict, and automatically recognize falls. However, relative to the required recording time, these events are rare and hence challenging to capture. Therefore, the FARSEEING (FAll Repository for the design of Smart and sElf-adapaive Environments prolonging INdependent livinG) consortium and associated partners established a meta-database of signals from real-world falls. Until the end of 2014, 397 falls were measured and reported. This includes falls data from several settings and disease groups, mainly geriatric rehabilitation, Parkinson’s disease, cerebellar and sensory ataxia. Seventy-five per cent of the falls were measured with a sampling rate of 100 Hz with devices including at least accelerometers and gyroscopes. To date more than 100 of these real-world falls have been validated and finally processed for data analyses. The observed signal patterns showed a high heterogeneity and differed considerably from those of simulated falls. Preliminary analyses of the available real-world falls data with two different fall-detection approaches using wavelets as well as temporal and mechanical thresholds considerably improved the detection performance. The FARSEEING consortium will continue to increase the number of measured real-world falls in the meta-database beyond the end of the project. External users can request data access on the FARSEEING website.
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2015. Signals from real-world falls. PeerJ PrePrints 3:e1013v1 https://doi.org/10.7287/peerj.preprints.1013v1Author comment
This presentation was a contribution to the 2nd Winter Symposium of the "Human Motion Project" and is part of "PeerJ Human Motion Project collection".
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Competing Interests
The authors declare they have no competing interests.
Author Contributions
Jochen Klenk conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables.
Luca Palmerini analyzed the data, prepared figures and/or tables, reviewed drafts of the paper.
Alan K Bourke analyzed the data, prepared figures and/or tables, reviewed drafts of the paper.
Lars Schwickert performed the experiments, contributed reagents/materials/analysis tools, reviewed drafts of the paper.
Clemens Becker conceived and designed the experiments, contributed reagents/materials/analysis tools, reviewed drafts of the paper.
Funding
The research leading to these results has been partly funded by the European Union—Seventh Framework Programme (FP7/2007-2013) under grant agreement n. 288940 (FARSEEING project). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.