Infrared–ultrasonic sensor fusion for support vector machine–based fall detection

Chen, Zhangjie; Wang, Ya

doi:10.1177/1045389X18758183

Infrared–ultrasonic sensor fusion for support vector machine–based fall detection

Journal Article · Wed Feb 28 23:00:00 EST 2018 · Journal of Intelligent Material Systems and Structures

DOI:https://doi.org/10.1177/1045389X18758183· OSTI ID:1507201

Chen, Zhangjie ^[1]; ^[1]

Department of Mechanical Engineering, Stony Brook University, Stony Brook, NY, USA

This article presents an infrared–ultrasonic sensor fusion approach for support vector machine–based fall detection, often required by elderly healthcare. Its detection algorithms and performance evaluation are detailed. The location, size, and temperature profile of the user can be estimated based on a novel sensory fusion algorithm. Different feature sets of the support vector machine–based machine learning algorithm are analyzed and their impact on fall detection accuracy is evaluated and compared empirically. Experiments study three non-fall activities, standing, sitting, and stooping, and two fall actions, forward falling and sideway falling, to simulate daily activities of the elderly. Fall detection accuracy studies are performed based on discretely and continuously (closer to reality) recorded experimental data, respectively. For the discrete data recording, an average accuracy of 92.2% is achieved when the stand-alone Grid-EYE is used and the accuracy is increased to 96.7% when sensor fusion is used. For the continuous data recording (180 training sets, 60 test sets at each distance), an average accuracy less than 70.0% is achieved when the stand-alone Grid-EYE is used and the accuracy is increased to around 90.3% after sensor fusion. New features will be explored in the next step to further increase detection accuracy.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: NONE; AR0000531

OSTI ID:: 1507201

Alternate ID(s):: OSTI ID: 1541874

Journal Information:: Journal of Intelligent Material Systems and Structures, Journal Name: Journal of Intelligent Material Systems and Structures Journal Issue: 9 Vol. 29; ISSN 1045-389X

Publisher:: SAGE PublicationsCopyright Statement

Country of Publication:: United States

Language:: English

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Infrared–ultrasonic sensor fusion for support vector machine–based fall detection

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