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

• Main Authors: Chao Fang, Yamei Zhang, Mingyi Zhang, Qun Fang
• Format: Article
• Language: English
• Published: MDPI AG 2020-07-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: road safety; drive-related risks; P300; driving performance
• Online Access: https://www.mdpi.com/1660-4601/17/15/5266
• ISSN: 1661-7827; 1660-4601

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.