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Robust Unobtrusive Fall Detection using Infrared Array Sensors


Authors: X. Fan, H. Zhang, C. Leung, and Z. Shen
Title: Robust Unobtrusive Fall Detection using Infrared Array Sensors
Abstract: As the world’s aging population grows, fall is becoming a major problem in public health. It is one of the most vital risk 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.
Keywords: 
Conference Name: International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI'17)
Location: Daegu, South Korea
Publisher: IEEE
Year: 2017
Accepted PDF File: Robust_Unobtrusive_Fall_Detection_using_Infrared_Array_Sensors_accepted.pdf
Permanent Link: https://doi.org/10.1109/MFI.2017.8170428
Reference: X. Fan, H. Zhang, C. Leung, and Z. Shen, “Robust unobtrusive fall detection using infrared array sensors,” in Proceedings of the International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI’17). IEEE, November 2017, pp. 194–199.
bibtex: 
@inproceedings{LILY-c138, 
    author	= {Fan, Xiuyi and Zhang, Huiguo and Leung, Cyril and Shen, Zhiqi},
    title	= {Robust Unobtrusive Fall Detection using Infrared Array Sensors},  
    booktitle	= {Proceedings of the International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI'17)}, 
    year		= {2017}, 
    month	= {November}, 
    pages	= {194-199}, 
    location	= {Daegu, South Korea},
    publisher	= {IEEE},
 }