NDLI: Seizure detection exploiting EMD-wavelet analysis of EEG signals

Content Provider	IEEE Xplore Digital Library
Author	Shahnaz, C. Rafi, R.H.M. Fattah, S.A. Zhu, W.-P. Ahmad, M.O.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. & Electron. Eng., Bangladesh Univ. of Eng. & Technol., Dhaka, Bangladesh (Shahnaz, C.; Rafi, R.H.M.; Fattah, S.A.) \|\| Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, QC, Canada (Zhu, W.-P.; Ahmad, M.O.)
Abstract	In his paper a method of seizure detection has been proposed based on the Discrete Wavelet Transform (DWT) analysis of the dominant Intrinsic mode function(IMF) resulting from the Empirical Mode Decomposition(EMD) of the EEG signals. Considering the normalized energy, Fourier spectrum and cross-correlation coefficient analysis, only the 4th Level DWT coefficients of the dominant IMF is found reasonable for feature computation. In order to reduce the dimension of the feature vector, Higher order statistics of these coefficients are employed to form he feature vector. The reduced feature vector thus formed is found effective for distinguishing seizure and non-seizure EEG signals when fed to a k-nearest neighborhood (k-NN) classifier. Extensive simulations are carried out using a benchmark EEG dataset. It is shown that the proposed method is capable of producing greater sensitivity, specificity and accuracy in comparison to that obtained by a sate-of-the-art method using the same EEG dataset and classifier.
Starting Page	57
Ending Page	60
File Size	1387613
Page Count	4
File Format	PDF
ISBN	9781479983919
DOI	10.1109/ISCAS.2015.7168569
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-24
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Discrete wavelet transforms Training Higher order statistics Sensitivity Accuracy Feature extraction k-Nearest Neighbors EEG Signal Analysis seizure empirical mode decomposition Discrete Wavelet Transform
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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