Subtractive fuzzy classifier based driver drowsiness levels classification using EEG

Proceeding of The 2nd International Conference on Communication and Signal Processing (ICCSP 2013) at Melmaruvathur, Tamilnadu, India on 3 April 2013 through 5 April 2013. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp

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Bibliographic Details
Main Authors: Murugappan, M., Dr., Wali, Mousa Kadhim, R. Badlishah, Ahmad, Prof. Dr., Murugappan, Subbulakshmi
Other Authors: murugappan@unimap.edu.my
Format: Working Paper
Language:English
Published: IEEE Conference Publications 2014
Subjects:
EEG
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/34634
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spelling my.unimap-346342014-05-22T06:59:31Z Subtractive fuzzy classifier based driver drowsiness levels classification using EEG Murugappan, M., Dr. Wali, Mousa Kadhim R. Badlishah, Ahmad, Prof. Dr. Murugappan, Subbulakshmi murugappan@unimap.edu.my musawali@yahoo.com badli@unimap.edu.my subbulakshmi@unimap.edu.my Discrete wavelet transform EEG Fast Fourier Transform Fuzzy inference system Proceeding of The 2nd International Conference on Communication and Signal Processing (ICCSP 2013) at Melmaruvathur, Tamilnadu, India on 3 April 2013 through 5 April 2013. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp Driver drowsiness is one of the major causes for several road accidents over the world. In this study, Electroencephalogram (EEG) signals were acquired using 14 electrodes from 50 subjects. All the electrodes are placed on the driver scalp based on International 10/20 standard and Butterworth 4 th order filter was used to remove the noise and artifact. Four EEG frequency bands (delta, theta, alpha, and beta) were analyzed on this work and extracted using Discrete Wavelet Packet Transform (DWPT). Fast Fourier Transform (FFT) was used to extract two statistical features such as spectral centroid and power spectral density (PSD) from the above frequency bands. Subtractive fuzzy classifier was used to map the extracted features into four different driver drowsiness levels namely, awake, drowsy, high drowsy and sleep stage1. As a result of this study points out the best average accuracy achieved by subtractive fuzzy inference classifier is 84.41% based on power spectral density feature extracted by 'db4' wavelet function. 2014-05-22T06:59:31Z 2014-05-22T06:59:31Z 2013-04 Working Paper p. 159-164 978-1-4673-4865-2 http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6577036 http://dspace.unimap.edu.my:80/dspace/handle/123456789/34634 http://dx.doi.org/10.1109/iccsp.2013.6577036 en Proceeding of The 2nd International Conference on Communication and Signal Processing (ICCSP 2013); IEEE Conference Publications
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Discrete wavelet transform
EEG
Fast Fourier Transform
Fuzzy inference system
spellingShingle Discrete wavelet transform
EEG
Fast Fourier Transform
Fuzzy inference system
Murugappan, M., Dr.
Wali, Mousa Kadhim
R. Badlishah, Ahmad, Prof. Dr.
Murugappan, Subbulakshmi
Subtractive fuzzy classifier based driver drowsiness levels classification using EEG
description Proceeding of The 2nd International Conference on Communication and Signal Processing (ICCSP 2013) at Melmaruvathur, Tamilnadu, India on 3 April 2013 through 5 April 2013. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp
author2 murugappan@unimap.edu.my
author_facet murugappan@unimap.edu.my
Murugappan, M., Dr.
Wali, Mousa Kadhim
R. Badlishah, Ahmad, Prof. Dr.
Murugappan, Subbulakshmi
format Working Paper
author Murugappan, M., Dr.
Wali, Mousa Kadhim
R. Badlishah, Ahmad, Prof. Dr.
Murugappan, Subbulakshmi
author_sort Murugappan, M., Dr.
title Subtractive fuzzy classifier based driver drowsiness levels classification using EEG
title_short Subtractive fuzzy classifier based driver drowsiness levels classification using EEG
title_full Subtractive fuzzy classifier based driver drowsiness levels classification using EEG
title_fullStr Subtractive fuzzy classifier based driver drowsiness levels classification using EEG
title_full_unstemmed Subtractive fuzzy classifier based driver drowsiness levels classification using EEG
title_sort subtractive fuzzy classifier based driver drowsiness levels classification using eeg
publisher IEEE Conference Publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/34634
_version_ 1643797550178762752
score 13.214268