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Conference Paper/Proceeding/Abstract 439 views

Robust unobtrusive fall detection using infrared array sensors

Xiuyi Fan, Huiguo Zhang, Cyril Leung, Zhiqi Shen

2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), Pages: 194 - 199

Swansea University Author: Xiuyi Fan

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DOI (Published version): 10.1109/mfi.2017.8170428

Abstract

We present a fall detection system using infrared array sensors with several deep learning methods, including long-short-term-memory and gated recurrent unit models. Evaluated with fall data collected in two different sets of configurations, we show that our approach gives significant improvement ov...

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Published in: 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)
ISBN: 978-1-5090-6065-8 9781509060641
Published: Daegu, South Korea IEEE 2017
URI: https://cronfa.swan.ac.uk/Record/cronfa39370
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Abstract: We present a fall detection system using infrared array sensors with several deep learning methods, including long-short-term-memory and gated recurrent unit models. Evaluated with fall data collected in two different sets of configurations, we show that our approach gives significant improvement over existing works using the same infrared array sensor.
Keywords: Fall Detection
College: College of Science
Start Page: 194
End Page: 199