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...

Full description

Saved in:
Bibliographic Details
Main Authors: Ben Dkhil, Mejdi, Wali, Ali, Alimi, Adel M.
Format: Conference Proceeding
Language:English
Subjects:
Anesthesia
Conferences
Drowsiness
EEG
Electrodes
Electroencephalography
Electronics
FFT
Fourier transforms
Fuzzy logic
Fuzzy rules
Reflection
Sleep
Systems design
Time series
Traffic accidents
Transforms
Citations: Items that cite this one
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2164-7151
DOI:10.1109/ISDA.2015.7489245