EEG Processing System for Detecting a State of Drowsy Driving

M. Kedir-Talha, Sid Ahmed Walid Talha, Feriel Celia Boumghar, Karim Meddah, Hadjar Zairi
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引用次数: 2

Abstract

 Abstract —By exploiting a database of 109 persons including two states to detect: sleepy or not, we have designed a system for automatically detecting drowsiness of a driver at the wheel. By filtering the alpha wave and by using the power spectral density of that same wave, our data were analyzed using the percentiles as measures of dispersion. A threshold discriminating the two states was found, which helped to highlight the area of the brain responsible for the state of drowsiness for driver. Thus, number of EEG signals to be analyzed will reduce and processing time of this system will be decreased. With cross validation technique, data are trained and tested, to get result with accuracy of 80% or higher. It shows that the EEG could be used helping experts in the development of an intelligent system for detecting state of drowsy driving with only ten signals by person.
检测疲劳驾驶状态的脑电图处理系统
摘要:利用109人的数据库,包括两种状态检测:困倦和不困倦,设计了一个自动检测驾驶员困倦状态的系统。通过过滤α波并使用同一波的功率谱密度,我们的数据使用百分位数作为色散的度量来分析。他们发现了一个区分这两种状态的阈值,这有助于突出司机大脑中负责困倦状态的区域。这样就减少了需要分析的脑电信号数量,减少了系统的处理时间。采用交叉验证技术,对数据进行训练和测试,得到准确率在80%以上的结果。研究结果表明,EEG可以帮助专家开发一种仅用10个信号就能检测人疲劳驾驶状态的智能系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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