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Authors: Sebastian Fudickar ; Alexander Lindemann and Bettina Schnor

Affiliation: Potsdam University, Germany

ISBN: 978-989-758-010-9

Keyword(s): Fall detection, Development of Assistive Technology, Sensors-based Applications.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Biomedical Signal Processing ; Devices ; Distributed and Mobile Software Systems ; Evaluation and Use of Healthcare IT ; Health Engineering and Technology Applications ; Health Information Systems ; Human-Computer Interaction ; Mobile Technologies ; Mobile Technologies for Healthcare Applications ; Motion Tracking Technologies ; Neural Rehabilitation ; Neurotechnology, Electronics and Informatics ; Pervasive Health Systems and Services ; Physiological Computing Systems ; Sensors-Based Applications ; Software Engineering ; Wearable Sensors and Systems

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.

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Paper citation in several formats:
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

@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},
}

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

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