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P300 Measures and Drive-Related Risks: A Systematic Review and Meta-Analysis

Detecting signs for an increased level of risk during driving are critical for the effective prevention of road traffic accidents. The current study searched for literature through major databases such as PubMed, EBSCO, IEEE, and ScienceDirect. A total of 14 articles that measured P300 components in...

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Detalles Bibliográficos
Autores principales: Fang, Chao, Zhang, Yamei, Zhang, Mingyi, Fang, Qun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7432745/
https://www.ncbi.nlm.nih.gov/pubmed/32707766
http://dx.doi.org/10.3390/ijerph17155266
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author Fang, Chao
Zhang, Yamei
Zhang, Mingyi
Fang, Qun
author_facet Fang, Chao
Zhang, Yamei
Zhang, Mingyi
Fang, Qun
author_sort Fang, Chao
collection PubMed
description Detecting signs for an increased level of risk during driving are critical for the effective prevention of road traffic accidents. The current study searched for literature through major databases such as PubMed, EBSCO, IEEE, and ScienceDirect. A total of 14 articles that measured P300 components in relation to driving tasks were included for a systematic review and meta-analysis. The risk factors investigated in the reviewed articles were summarized in five categories, including reduced attention, distraction, alcohol, challenging situations on the road, and negative emotion. A meta-analysis was conducted at both behavioral and neural levels. Behavioral performance was measured by the reaction time and driving performance, while the neural response was measured by P300 amplitude and latency. A significant increase in reaction time was identified when drivers were exposed to the risk factors. In addition, the significant effects of a reduced P300 amplitude and prolonged P300 latency indicated a reduced capacity for cognitive information processing. There was a tendency of driving performance decrement in relation to the risk factors, however, the effect was non-significant due to considerable variations and heterogeneity across the included studies. The results led to the conclusion that the P300 amplitude and latency are reliable indicators and predictors of the increased risk in driving. Future applications of the P300-based brain–computer interface (BCI) system may make considerable contributions toward preventing road traffic accidents.
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spelling pubmed-74327452020-08-27 P300 Measures and Drive-Related Risks: A Systematic Review and Meta-Analysis Fang, Chao Zhang, Yamei Zhang, Mingyi Fang, Qun Int J Environ Res Public Health Article Detecting signs for an increased level of risk during driving are critical for the effective prevention of road traffic accidents. The current study searched for literature through major databases such as PubMed, EBSCO, IEEE, and ScienceDirect. A total of 14 articles that measured P300 components in relation to driving tasks were included for a systematic review and meta-analysis. The risk factors investigated in the reviewed articles were summarized in five categories, including reduced attention, distraction, alcohol, challenging situations on the road, and negative emotion. A meta-analysis was conducted at both behavioral and neural levels. Behavioral performance was measured by the reaction time and driving performance, while the neural response was measured by P300 amplitude and latency. A significant increase in reaction time was identified when drivers were exposed to the risk factors. In addition, the significant effects of a reduced P300 amplitude and prolonged P300 latency indicated a reduced capacity for cognitive information processing. There was a tendency of driving performance decrement in relation to the risk factors, however, the effect was non-significant due to considerable variations and heterogeneity across the included studies. The results led to the conclusion that the P300 amplitude and latency are reliable indicators and predictors of the increased risk in driving. Future applications of the P300-based brain–computer interface (BCI) system may make considerable contributions toward preventing road traffic accidents. MDPI 2020-07-22 2020-08 /pmc/articles/PMC7432745/ /pubmed/32707766 http://dx.doi.org/10.3390/ijerph17155266 Text en © 2020 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
Fang, Chao
Zhang, Yamei
Zhang, Mingyi
Fang, Qun
P300 Measures and Drive-Related Risks: A Systematic Review and Meta-Analysis
title P300 Measures and Drive-Related Risks: A Systematic Review and Meta-Analysis
title_full P300 Measures and Drive-Related Risks: A Systematic Review and Meta-Analysis
title_fullStr P300 Measures and Drive-Related Risks: A Systematic Review and Meta-Analysis
title_full_unstemmed P300 Measures and Drive-Related Risks: A Systematic Review and Meta-Analysis
title_short P300 Measures and Drive-Related Risks: A Systematic Review and Meta-Analysis
title_sort p300 measures and drive-related risks: a systematic review and meta-analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7432745/
https://www.ncbi.nlm.nih.gov/pubmed/32707766
http://dx.doi.org/10.3390/ijerph17155266
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