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Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG
The vigilance of the driver is important for railway safety, despite not being included in the safety management system (SMS) for high-speed train safety. In this paper, a novel fatigue detection system for high-speed train safety based on monitoring train driver vigilance using a wireless wearable...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375772/ https://www.ncbi.nlm.nih.gov/pubmed/28257073 http://dx.doi.org/10.3390/s17030486 |
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author | Zhang, Xiaoliang Li, Jiali Liu, Yugang Zhang, Zutao Wang, Zhuojun Luo, Dianyuan Zhou, Xiang Zhu, Miankuan Salman, Waleed Hu, Guangdi Wang, Chunbai |
author_facet | Zhang, Xiaoliang Li, Jiali Liu, Yugang Zhang, Zutao Wang, Zhuojun Luo, Dianyuan Zhou, Xiang Zhu, Miankuan Salman, Waleed Hu, Guangdi Wang, Chunbai |
author_sort | Zhang, Xiaoliang |
collection | PubMed |
description | The vigilance of the driver is important for railway safety, despite not being included in the safety management system (SMS) for high-speed train safety. In this paper, a novel fatigue detection system for high-speed train safety based on monitoring train driver vigilance using a wireless wearable electroencephalograph (EEG) is presented. This system is designed to detect whether the driver is drowsiness. The proposed system consists of three main parts: (1) a wireless wearable EEG collection; (2) train driver vigilance detection; and (3) early warning device for train driver. In the first part, an 8-channel wireless wearable brain-computer interface (BCI) device acquires the locomotive driver’s brain EEG signal comfortably under high-speed train-driving conditions. The recorded data are transmitted to a personal computer (PC) via Bluetooth. In the second step, a support vector machine (SVM) classification algorithm is implemented to determine the vigilance level using the Fast Fourier transform (FFT) to extract the EEG power spectrum density (PSD). In addition, an early warning device begins to work if fatigue is detected. The simulation and test results demonstrate the feasibility of the proposed fatigue detection system for high-speed train safety. |
format | Online Article Text |
id | pubmed-5375772 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-53757722017-04-10 Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG Zhang, Xiaoliang Li, Jiali Liu, Yugang Zhang, Zutao Wang, Zhuojun Luo, Dianyuan Zhou, Xiang Zhu, Miankuan Salman, Waleed Hu, Guangdi Wang, Chunbai Sensors (Basel) Article The vigilance of the driver is important for railway safety, despite not being included in the safety management system (SMS) for high-speed train safety. In this paper, a novel fatigue detection system for high-speed train safety based on monitoring train driver vigilance using a wireless wearable electroencephalograph (EEG) is presented. This system is designed to detect whether the driver is drowsiness. The proposed system consists of three main parts: (1) a wireless wearable EEG collection; (2) train driver vigilance detection; and (3) early warning device for train driver. In the first part, an 8-channel wireless wearable brain-computer interface (BCI) device acquires the locomotive driver’s brain EEG signal comfortably under high-speed train-driving conditions. The recorded data are transmitted to a personal computer (PC) via Bluetooth. In the second step, a support vector machine (SVM) classification algorithm is implemented to determine the vigilance level using the Fast Fourier transform (FFT) to extract the EEG power spectrum density (PSD). In addition, an early warning device begins to work if fatigue is detected. The simulation and test results demonstrate the feasibility of the proposed fatigue detection system for high-speed train safety. MDPI 2017-03-01 /pmc/articles/PMC5375772/ /pubmed/28257073 http://dx.doi.org/10.3390/s17030486 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Xiaoliang Li, Jiali Liu, Yugang Zhang, Zutao Wang, Zhuojun Luo, Dianyuan Zhou, Xiang Zhu, Miankuan Salman, Waleed Hu, Guangdi Wang, Chunbai Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG |
title | Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG |
title_full | Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG |
title_fullStr | Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG |
title_full_unstemmed | Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG |
title_short | Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG |
title_sort | design of a fatigue detection system for high-speed trains based on driver vigilance using a wireless wearable eeg |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375772/ https://www.ncbi.nlm.nih.gov/pubmed/28257073 http://dx.doi.org/10.3390/s17030486 |
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