Conference Paper/Proceeding/Abstract 803 views
Robust unobtrusive fall detection using infrared array sensors
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...
| Published in: | 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI) |
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| ISBN: | 978-1-5090-6065-8 9781509060641 |
| Published: |
Daegu, South Korea
IEEE
2017
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa39370 |
| Tags: |
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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. |
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| Keywords: |
Fall Detection |
| College: |
Faculty of Science and Engineering |
| Start Page: |
194 |
| End Page: |
199 |