Drowsy Driver Detection by EEG Analysis Using Fast Fourier Transform

In this paper, we try to analyze drowsiness which is a major factor in many traffic accidents due to the clear decline in the attention and recognition of danger drivers. The object of this work is to develop an automatic method to evaluate the drowsiness stage by analysis of EEG signals records. Th...

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Published in:arXiv.org 2018-06
Main Authors: Mejdi Ben Dkhil, Wali, Ali, Alimi, Adel M
Format: Article
Language:English
Subjects:
Algorithms
Electroencephalography
Fast Fourier transformations
Fourier transforms
Hazards
Object recognition
Sleep
Traffic accidents
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Wali, Ali
Alimi, Adel M
description In this paper, we try to analyze drowsiness which is a major factor in many traffic accidents due to the clear decline in the attention and recognition of danger drivers. The object of this work is to develop an automatic method to evaluate the drowsiness stage by analysis of EEG signals records. The absolute band power of the EEG signal was computed by taking the Fast Fourier Transform (FFT) of the time series signal. Finally, the algorithm developed in this work has been improved on eight samples from the Physionet sleep-EDF database.
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subjects Algorithms
Electroencephalography
Fast Fourier transformations
Fourier transforms
Hazards
Object recognition
Sleep
Traffic accidents
title Drowsy Driver Detection by EEG Analysis Using Fast Fourier Transform
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