基于驾驶性能评估和脑电图功率谱分析监测驾驶员警觉性。
Monitoring driver's alertness based on the driving performance estimation and the EEG power spectrum analysis.
作者信息
Liang S F, Lin C T, Wu R C, Chen Y C, Huang T Y, Jung T P
机构信息
Brain Research Center, University System of Taiwan.
出版信息
Conf Proc IEEE Eng Med Biol Soc. 2005;2005:5738-41. doi: 10.1109/IEMBS.2005.1615791.
Preventing accidents caused by drowsiness behind the steering wheel is highly desirable but requires techniques for continuously estimating driver's abilities of perception, recognition and vehicle control abilities. This paper proposes methods for drowsiness estimation that combine the electroencephalogram (EEG) log subband power spectrum, correlation analysis, principal component analysis, and linear regression models to indirectly estimate driver's drowsiness level in a virtual-reality-based driving simulator. Results show that it is feasible to quantitatively monitor driver's alertness with concurrent changes in driving performance in a realistic driving simulator.
预防因驾驶时困倦而导致的事故是非常必要的，但这需要能够持续评估驾驶员感知、识别和车辆控制能力的技术。本文提出了一种困倦估计方法，该方法结合脑电图（EEG）对数子带功率谱、相关性分析、主成分分析和线性回归模型，在基于虚拟现实的驾驶模拟器中间接估计驾驶员的困倦程度。结果表明，在逼真的驾驶模拟器中，通过驾驶性能的同步变化来定量监测驾驶员的警觉性是可行的。
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