NDLI: Classification of EEG signals for detection of epileptic seizure activities based on LBP descriptor of time-frequency images

Content Provider	IEEE Xplore Digital Library
Author	Boubchir, L. Al-Maadeed, S. Bouridane, A. Cherif, A.A.
Copyright Year	2015
Description	Author affiliation: Dept. of CSDT, Univ. of Northumbria, Newcastle upon Tyne, UK (Bouridane, A.) \|\| LIASD Res. Lab., Univ. of Paris 8, St. Denis, France (Boubchir, L.; Cherif, A.A.) \|\| Dept. of Comput. Sci. & Eng., Qatar Univ., Doha, Qatar (Al-Maadeed, S.)
Abstract	This paper presents novel time-frequency (t-f) feature extraction approach for the classification of EEG signals for Epileptic seizure activities detection. The proposed features are based on Local Binary Patterns (LBP) descriptor extracted from t-f representation of EEG signals processed as a textured image. Compared to most previous t-f approaches were based only on features derived from the instantaneous frequency and the energies of EEG signals generated from different spectral sub-bands, the proposed t-f features are capable to describe visually the epileptic seizure activity patterns observed in t-f image of EEG signals. The results obtained on real EEG data show that the use of t-f LBP descriptor-based features achieve an overall classification accuracy up to 99% for 150 EEG signals using 2-class SVM classifier. This is confirmed by ROC curve analysis.
Starting Page	3758
Ending Page	3762
File Size	963281
Page Count	5
File Format	PDF
e-ISBN	9781479983391
DOI	10.1109/ICIP.2015.7351507
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Feature extraction Time-frequency analysis Databases Entropy Kernel EEG Time-frequency image time-frequency feature extraction LBP descriptor seizure detection
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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