Department of Pharmacology, Fourth Military Medical University, Xi'an 710032, China.
College of Architecture and Urban Planning, Qingdao University of Technology, Qingdao 266033, China.
Int J Environ Res Public Health. 2020 Jul 22;17(15):5266. doi: 10.3390/ijerph17155266.
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.
检测驾驶过程中风险水平升高的迹象对于有效预防道路交通事故至关重要。本研究通过 PubMed、EBSCO、IEEE 和 ScienceDirect 等主要数据库搜索文献。对与驾驶任务相关的 P300 成分进行了系统评价和荟萃分析，共纳入了 14 篇测量 P300 成分的文章。综述文章中总结了五类研究的风险因素，包括注意力降低、分心、酒精、道路上的挑战情况和负面情绪。在行为和神经水平上进行了荟萃分析。行为表现通过反应时间和驾驶表现来衡量，而神经反应则通过 P300 幅度和潜伏期来衡量。当驾驶员暴露于风险因素时，反应时间显著增加。此外，P300 幅度减小和潜伏期延长的显著影响表明认知信息处理能力降低。与风险因素有关的驾驶表现有下降的趋势，但由于纳入研究的差异和异质性较大，效果不显著。研究结果表明，P300 幅度和潜伏期是驾驶风险增加的可靠指标和预测指标。基于 P300 的脑机接口 (BCI) 系统的未来应用可能会对预防道路交通事故做出重大贡献。
