Subtractive fuzzy classifier based driver distraction levels classification using EEG
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Society of Physical Therapy Science
2014
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my.unimap-346102014-05-21T23:24:42Z Subtractive fuzzy classifier based driver distraction levels classification using EEG Wali, Mousa Kadhim Murugappan, M., Dr. R. Badlishah, Ahmad, Prof. Dr. musawali@yahoo.com murugappan@unimap.edu.my badli@unimap.edu.my Discrete wavelet transform EEG Fuzzy inference system Link to publisher's homepage at https://www.jstage.jst.go.jp/ [Purpose] In earlier studies of driver distraction, researchers classified distraction into two levels (not distracted, and distracted). This study classified four levels of distraction (neutral, low, medium, high). [Subjects and Methods] Fifty Asian subjects (n=50, 43 males, 7 females), age range 20-35 years, who were free from any disease, participated in this study. Wireless EEG signals were recorded by 14 electrodes during four types of distraction stimuli (Global Position Systems (GPS), music player, short message service (SMS), and mental tasks). We derived the amplitude spectrum of three different frequency bands, theta, alpha, and beta of EEG. Then, based on fusion of discrete wavelet packet transforms and fast fourier transform yield, we extracted two features (power spectral density, spectral centroid frequency) of different wavelets (db4, db8, sym8, and coif5). Mean ± SD was calculated and analysis of variance (ANOVA) was performed. A fuzzy inference system classifier was applied to different wavelets using the two extracted features. [Results] The results indicate that the two features of sym8 posses highly significant discrimination across the four levels of distraction, and the best average accuracy achieved by the subtractive fuzzy classifier was 79.21% using the power spectral density feature extracted using the sym8 wavelet. [Conclusion] These findings suggest that EEG signals can be used to monitor distraction level intensity in order to alert drivers to high levels of distraction. 2014-05-21T23:24:42Z 2014-05-21T23:24:42Z 2013 Article Journal of Physical Therapy Science, vol. 25(9), 2013, pages 1055-1058 2187-5626 (Online) 0915-5287 (Print) https://www.jstage.jst.go.jp/article/jpts/25/9/25_jpts-2013-099/_article http://dspace.unimap.edu.my:80/dspace/handle/123456789/34610 http://dx.doi.org/10.1589/jpts.25.1055 Society of Physical Therapy Science |
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Universiti Malaysia Perlis |
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Discrete wavelet transform EEG Fuzzy inference system |
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Discrete wavelet transform EEG Fuzzy inference system Wali, Mousa Kadhim Murugappan, M., Dr. R. Badlishah, Ahmad, Prof. Dr. Subtractive fuzzy classifier based driver distraction levels classification using EEG |
| description |
Link to publisher's homepage at https://www.jstage.jst.go.jp/ |
| author2 |
musawali@yahoo.com |
| author_facet |
musawali@yahoo.com Wali, Mousa Kadhim Murugappan, M., Dr. R. Badlishah, Ahmad, Prof. Dr. |
| format |
Article |
| author |
Wali, Mousa Kadhim Murugappan, M., Dr. R. Badlishah, Ahmad, Prof. Dr. |
| author_sort |
Wali, Mousa Kadhim |
| title |
Subtractive fuzzy classifier based driver distraction levels classification using EEG |
| title_short |
Subtractive fuzzy classifier based driver distraction levels classification using EEG |
| title_full |
Subtractive fuzzy classifier based driver distraction levels classification using EEG |
| title_fullStr |
Subtractive fuzzy classifier based driver distraction levels classification using EEG |
| title_full_unstemmed |
Subtractive fuzzy classifier based driver distraction levels classification using EEG |
| title_sort |
subtractive fuzzy classifier based driver distraction levels classification using eeg |
| publisher |
Society of Physical Therapy Science |
| publishDate |
2014 |
| url |
http://dspace.unimap.edu.my:80/dspace/handle/123456789/34610 |
| _version_ |
1643797541759746048 |
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13.214268 |