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Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-17639

Fu, Z; Delbruck, T; Lichtsteiner, P; Culurciello, E (2008). An address-event fall detector for assisted living applications. IEEE Transactions on Biomedical Circuits and Systems, 2(2):88-96.

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Abstract

In this paper, we describe an address-event vision system designed to detect accidental falls in elderly home care applications. The system raises an alarm when a fall hazard is detected. We use an asynchronous temporal contrast vision sensor which features sub-millisecond temporal resolution. The sensor reports a fall at ten times higher temporal resolution than a frame-based camera and shows 84% higher bandwidth efficiency as it transmits fall events. A lightweight algorithm computes an instantaneous motion vector and reports fall events. We are able to distinguish fall events from normal human behavior, such as walking, crouching down, and sitting down. Our system is robust to the monitored person's spatial position in a room and presence of pets.

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
DDC:570 Life sciences; biology
Uncontrolled Keywords:neuromorphic
Language:English
Date:2008
Deposited On:07 Mar 2009 16:17
Last Modified:27 Nov 2013 22:30
Publisher:IEEE
ISSN:1932-4545
Additional Information:"© 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Publisher DOI:10.1109/TBCAS.2008.924448
Citations:Web of Science®. Times Cited: 16
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Scopus®. Citation Count: 24

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