Threshold-based Fall Detection on Smart Phones

Sebastian Fudickar, Alexander Lindemann, Bettina Schnor

2014

Abstract

This paper evaluates threshold-based fall detection algorithms which use data from acceleration sensors that are part of the current smart phone technology. The evaluation was done with sampled fall records where young people simulate falls. To test the false positive rate of the algorithms, another record set with Activities of the Daily Living (ADLs) from elderlies was used. The results are very promising and show that smart phone sensors are suitable for fall detection. This will offer a new opportunity to assist elderlies in their daily living and extend their period of self-determined living.

Paper Citation

in Harvard Style

Fudickar S., Lindemann A. and Schnor B. (2014). Threshold-based Fall Detection on Smart Phones . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014) ISBN 978-989-758-010-9, pages 303-309. DOI: 10.5220/0004795803030309

in Bibtex Style

@conference{healthinf14,
author={Sebastian Fudickar and Alexander Lindemann and Bettina Schnor},
title={Threshold-based Fall Detection on Smart Phones},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014)},
year={2014},
pages={303-309},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004795803030309},
isbn={978-989-758-010-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014)
TI - Threshold-based Fall Detection on Smart Phones
SN - 978-989-758-010-9
AU - Fudickar S.
AU - Lindemann A.
AU - Schnor B.
PY - 2014
SP - 303
EP - 309
DO - 10.5220/0004795803030309