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基于人体生理信号特征的驾驶技能水平判别研究

Study of driving skill level discrimination based on human physiological signal characteristics.

作者信息

Wang Fuwang, Xu Qing, Fu Rongrong, Sun Guangbin

机构信息

School of Mechanic Engineering, Northeast Electric Power University Jilin 132012 China

College of Electrical Engineering, Yanshan University Qinhuangdao 066004 China.

出版信息

RSC Adv. 2018 Dec 18;8(73):42160-42169. doi: 10.1039/c8ra08523d. eCollection 2018 Dec 12.

Abstract

The primary purpose of the study is to distinguish the differences in driving skill between novice and experienced drivers from the viewpoint of human cognitive behavior. Firstly, EEG (electroencephalogram) signals were collected using EEG acquisition equipment called Neuroscan. The δ sub-band and EOG (electrooculogram) signals were extracted from the EEG. Furthermore, the eye movement rate and the sample entropy (SampEn) values of δ sub-bands were calculated. Finally, the heart rate variability (HRV) characteristics, calculated using the SampEn algorithm, were used to analyze driving skill. The final result showed that human physiological signals (EEG, EOG and ECG (electrocardiogram)) could effectively distinguish different driving skills.

摘要

该研究的主要目的是从人类认知行为的角度区分新手和经验丰富的驾驶员在驾驶技能上的差异。首先,使用名为Neuroscan的脑电图采集设备收集脑电图(EEG)信号。从脑电图中提取δ子带和眼电图(EOG)信号。此外,计算了δ子带的眼动速率和样本熵(SampEn)值。最后,使用基于样本熵算法计算的心率变异性(HRV)特征来分析驾驶技能。最终结果表明,人体生理信号(脑电图、眼电图和心电图(ECG))能够有效区分不同的驾驶技能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42db/9092114/2c050d60bc97/c8ra08523d-f1.jpg

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