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Study on the Effect of Man-Machine Response Mode to Relieve Driving Fatigue Based on EEG and EOG
Rapid and accurate detection of driver fatigue is of great significance to improve traffic safety. In the present work, we propose the man-machine response mode (MRM) to relieve driver fatigue caused by long-term driving. In this paper, the characteristics of the complex brain network, which can eff...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891316/ https://www.ncbi.nlm.nih.gov/pubmed/31717422 http://dx.doi.org/10.3390/s19224883 |
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author | Wang, Fuwang Xu, Qing Fu, Rongrong |
author_facet | Wang, Fuwang Xu, Qing Fu, Rongrong |
author_sort | Wang, Fuwang |
collection | PubMed |
description | Rapid and accurate detection of driver fatigue is of great significance to improve traffic safety. In the present work, we propose the man-machine response mode (MRM) to relieve driver fatigue caused by long-term driving. In this paper, the characteristics of the complex brain network, which can effectively reflect brain activity information, were used to detect the change of driving fatigue over time. Combined with the traditional eye movement characteristics and a subjective questionnaire (SQ), the changes in driving fatigue characteristics were comprehensively analyzed. The results show that driving fatigue can be effectively delayed using the MRM. Additionally, the response equipment is low in cost and practical, so it will be practical to use in actual driving situations in the future. |
format | Online Article Text |
id | pubmed-6891316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68913162019-12-12 Study on the Effect of Man-Machine Response Mode to Relieve Driving Fatigue Based on EEG and EOG Wang, Fuwang Xu, Qing Fu, Rongrong Sensors (Basel) Article Rapid and accurate detection of driver fatigue is of great significance to improve traffic safety. In the present work, we propose the man-machine response mode (MRM) to relieve driver fatigue caused by long-term driving. In this paper, the characteristics of the complex brain network, which can effectively reflect brain activity information, were used to detect the change of driving fatigue over time. Combined with the traditional eye movement characteristics and a subjective questionnaire (SQ), the changes in driving fatigue characteristics were comprehensively analyzed. The results show that driving fatigue can be effectively delayed using the MRM. Additionally, the response equipment is low in cost and practical, so it will be practical to use in actual driving situations in the future. MDPI 2019-11-08 /pmc/articles/PMC6891316/ /pubmed/31717422 http://dx.doi.org/10.3390/s19224883 Text en © 2019 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 Wang, Fuwang Xu, Qing Fu, Rongrong Study on the Effect of Man-Machine Response Mode to Relieve Driving Fatigue Based on EEG and EOG |
title | Study on the Effect of Man-Machine Response Mode to Relieve Driving Fatigue Based on EEG and EOG |
title_full | Study on the Effect of Man-Machine Response Mode to Relieve Driving Fatigue Based on EEG and EOG |
title_fullStr | Study on the Effect of Man-Machine Response Mode to Relieve Driving Fatigue Based on EEG and EOG |
title_full_unstemmed | Study on the Effect of Man-Machine Response Mode to Relieve Driving Fatigue Based on EEG and EOG |
title_short | Study on the Effect of Man-Machine Response Mode to Relieve Driving Fatigue Based on EEG and EOG |
title_sort | study on the effect of man-machine response mode to relieve driving fatigue based on eeg and eog |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891316/ https://www.ncbi.nlm.nih.gov/pubmed/31717422 http://dx.doi.org/10.3390/s19224883 |
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