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Conference Paper/Proceeding/Abstract 747 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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first_indexed 2018-04-11T19:34:04Z
last_indexed 2018-04-23T19:31:33Z
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spelling 2018-04-23T14:29:44.1624495 v2 39370 2018-04-11 Robust unobtrusive fall detection using infrared array sensors a88a07c43b3e80f27cb96897d1bc2534 Xiuyi Fan Xiuyi Fan true false 2018-04-11 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. Conference Paper/Proceeding/Abstract 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI) 194 199 IEEE Daegu, South Korea 978-1-5090-6065-8 9781509060641 Fall Detection 11 12 2017 2017-12-11 10.1109/mfi.2017.8170428 COLLEGE NANME COLLEGE CODE Swansea University 2018-04-23T14:29:44.1624495 2018-04-11T18:32:34.1870668 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Xiuyi Fan 1 Huiguo Zhang 2 Cyril Leung 3 Zhiqi Shen 4
title Robust unobtrusive fall detection using infrared array sensors
spellingShingle Robust unobtrusive fall detection using infrared array sensors
Xiuyi Fan
title_short Robust unobtrusive fall detection using infrared array sensors
title_full Robust unobtrusive fall detection using infrared array sensors
title_fullStr Robust unobtrusive fall detection using infrared array sensors
title_full_unstemmed Robust unobtrusive fall detection using infrared array sensors
title_sort Robust unobtrusive fall detection using infrared array sensors
author_id_str_mv a88a07c43b3e80f27cb96897d1bc2534
author_id_fullname_str_mv a88a07c43b3e80f27cb96897d1bc2534_***_Xiuyi Fan
author Xiuyi Fan
author2 Xiuyi Fan
Huiguo Zhang
Cyril Leung
Zhiqi Shen
format Conference Paper/Proceeding/Abstract
container_title 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)
container_start_page 194
publishDate 2017
institution Swansea University
isbn 978-1-5090-6065-8
9781509060641
doi_str_mv 10.1109/mfi.2017.8170428
publisher IEEE
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 0
active_str 0
description 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.
published_date 2017-12-11T03:49:59Z
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score 10.99342