Fall detection with unobtrusive infrared array sensors
As the world’s aging population grows, fall is becoming a major problem in public health. It is one of the most vital risks to the elderly. Many technology based fall detection systems have been developed in recent years with hardware ranging from wearable devices to ambience sensors and video camer...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Book Chapter |
| Language: | English |
| Published: |
Springer, Cham
2019
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| Online Access: | https://hdl.handle.net/10356/81438 http://hdl.handle.net/10220/50387 |
| _version_ | 1826116649318612992 |
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| author | Fan, Xiuyi Zhang, Huiguo Leung, Cyril Shen, Zhiqi |
| author2 | Lee, Sukhan |
| author_facet | Lee, Sukhan Fan, Xiuyi Zhang, Huiguo Leung, Cyril Shen, Zhiqi |
| author_sort | Fan, Xiuyi |
| collection | NTU |
| description | As the world’s aging population grows, fall is becoming a major problem in public health. It is one of the most vital risks to the elderly. Many technology based fall detection systems have been developed in recent years with hardware ranging from wearable devices to ambience sensors and video cameras. Several machine learning based fall detection classifiers have been developed to process sensor data with various degrees of success. In this paper, 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. |
| first_indexed | 2024-10-01T04:14:50Z |
| format | Book Chapter |
| id | ntu-10356/81438 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:14:50Z |
| publishDate | 2019 |
| publisher | Springer, Cham |
| record_format | dspace |
| spelling | ntu-10356/814382020-07-02T08:30:29Z Fall detection with unobtrusive infrared array sensors Fan, Xiuyi Zhang, Huiguo Leung, Cyril Shen, Zhiqi Lee, Sukhan Ko, Hanseok Oh, Songhwai School of Electrical and Electronic Engineering Fall Detection Machine Learning Engineering::Computer science and engineering As the world’s aging population grows, fall is becoming a major problem in public health. It is one of the most vital risks to the elderly. Many technology based fall detection systems have been developed in recent years with hardware ranging from wearable devices to ambience sensors and video cameras. Several machine learning based fall detection classifiers have been developed to process sensor data with various degrees of success. In this paper, 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. 2019-11-11T08:17:17Z 2019-12-06T14:30:58Z 2019-11-11T08:17:17Z 2019-12-06T14:30:58Z 2018 Book Chapter Fan, X., Zhang, H., Leung C., & Shen, Z. (2018). Fall detection with unobtrusive infrared array sensors. Lee, S., Ko, H., & Oh, S. (Eds.), Multisensor fusion and integration in the wake of big data, deep learning and cyber physical system (pp.253-267). Springer, Cham. 978-3-319-90508-2 https://hdl.handle.net/10356/81438 http://hdl.handle.net/10220/50387 10.1007/978-3-319-90509-9_15 en © 2018 Springer, Cham. All rights reserved. This paper was published in Multisensor fusion and integration in the wake of big data, deep learning and cyber physical system and is made available with permission of Springer, Cham. 16 p. application/pdf Springer, Cham |
| spellingShingle | Fall Detection Machine Learning Engineering::Computer science and engineering Fan, Xiuyi Zhang, Huiguo Leung, Cyril Shen, Zhiqi Fall detection with unobtrusive infrared array sensors |
| title | Fall detection with unobtrusive infrared array sensors |
| title_full | Fall detection with unobtrusive infrared array sensors |
| title_fullStr | Fall detection with unobtrusive infrared array sensors |
| title_full_unstemmed | Fall detection with unobtrusive infrared array sensors |
| title_short | Fall detection with unobtrusive infrared array sensors |
| title_sort | fall detection with unobtrusive infrared array sensors |
| topic | Fall Detection Machine Learning Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/81438 http://hdl.handle.net/10220/50387 |
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