标题: 驾驶在不同瞌睡程度下大脑讯号传递网络的变化
The research of the brain networks in different drowsiness stages of drivers
作者: 陈佳铃
Chen, Chia-Lin
林进灯
Lin, Chin-Teng
多媒体工程研究所
关键字: 瞌睡;驾驶行为表现;脑电波;讯号传递网络;Granger causality;独立成份分析;Drowsiness;Driving performance;Electroencephalograph (EEG),;Brain network;Granger causality analysis;Independent component analysis (ICA)
公开日期: 2010
摘要: 在车祸事故的原因当中,驾驶者瞌睡普遍被认为是主要因素。过去我们研究团队层探讨驾驶者瞌睡的脑电波现象,设计利用脑电波侦测瞌睡之演算法,并且开发成为驾使者的无线可携式瞌睡侦测设备。纵使我们已经有良好的瞌睡侦测指标,然而过去的方法中并不能解决从清醒到瞌睡渐进程度上的侦测。本研究探讨的是,受测者从清醒到瞌睡过程中脑内讯号传递网络是如何改变,以及真实生活中动态刺激造成的讯号传递。一共有六位受测者参与模拟夜间高速公路动态及非动态的虚拟实境开车实验,并且利用此环境给与受测者事件相关开车偏移任务。受测者的脑电波会经过独立讯号分析、Granger因果关系分析、时域频谱转换等方法进行分析比较。结果显示,从驾驶者清醒到瞌睡的过程中,讯号传递的目的地会从脑中前面的区域移动至后面的区域。此外在动态模拟下驾驶脑内掌管视觉和运动区域会比非动态的情况还要活跃。未来可利用这样的结果,在适当的脑区位置侦测驾驶目前的瞌睡状态,并且于进入瞌睡前就给与警示,使驾驶者的行车表现能保持良好水平。
Driver drowsiness was generally regarded as a main reason of causing car accidents. Our team had investigated EEG signals in drowsy state of driver, designed the algorithm that detecting drowsiness by EEG signals, and developed the wireless and portable application of detecting drowsiness for drivers. Although we already had the good indicators of detecting drowsiness by EEG signals, detecting the levels of drowsiness remained unsolved nowadays. The aim of this study is to explore the changes of brain signal transferring network from alertness to drowsiness and those signal flows generated by kinetic stimulation in real life. Six subjects participated in virtual-reality (VR)-based highway driving experiments on motion and motionless platform, and the event-related lane-departure task was used in the VR environment to simulate the long-term highway driving. The task-related EEG was analyzed using independent component analysis, Granger causality, and time-frequency. Results demonstrated the destination of signal flow was from anterior brain region shifting to posterior region respective alert to drowsy state. Furthermore, the EEG transferring dynamics were more active in occipital area and motor area on motion platform. In the future, the results can be used for detecting drowsiness in proper brain region, and warn the driver before drowsiness to make the performance of driver keep at a good level.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT079757540
http://hdl.handle.net/11536/46078
显示于类别:Thesis


文件中的档案:

  1. 754001.pdf

If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.