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Proceedings Paper

Radar fall detection using principal component analysis
Author(s): Branka Jokanovic; Moeness Amin; Fauzia Ahmad; Boualem Boashash
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Paper Abstract

Falls are a major cause of fatal and nonfatal injuries in people aged 65 years and older. Radar has the potential to become one of the leading technologies for fall detection, thereby enabling the elderly to live independently. Existing techniques for fall detection using radar are based on manual feature extraction and require significant parameter tuning in order to provide successful detections. In this paper, we employ principal component analysis for fall detection, wherein eigen images of observed motions are employed for classification. Using real data, we demonstrate that the PCA based technique provides performance improvement over the conventional feature extraction methods.

Paper Details

Date Published: 12 May 2016
PDF: 6 pages
Proc. SPIE 9829, Radar Sensor Technology XX, 982919 (12 May 2016); doi: 10.1117/12.2225106
Show Author Affiliations
Branka Jokanovic, Villanova Univ. (United States)
Moeness Amin, Villanova Univ. (United States)
Fauzia Ahmad, Villanova Univ. (United States)
Boualem Boashash, Qatar Univ. (Qatar)


Published in SPIE Proceedings Vol. 9829:
Radar Sensor Technology XX
Kenneth I. Ranney; Armin Doerry, Editor(s)

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