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Ensemble Classifier for Epileptic Seizure Detection for Imperfect EEG Data
Joint Authors
Abualsaud, Khalid
Mahmuddin, Massudi
Saleh, Mohammad
Mohamed, Amr
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-02-04
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Brain status information is captured by physiological electroencephalogram (EEG) signals, which are extensively used to study different brain activities.
This study investigates the use of a new ensemble classifier to detect an epileptic seizure from compressed and noisy EEG signals.
This noise-aware signal combination (NSC) ensemble classifier combines four classification models based on their individual performance.
The main objective of the proposed classifier is to enhance the classification accuracy in the presence of noisy and incomplete information while preserving a reasonable amount of complexity.
The experimental results show the effectiveness of the NSC technique, which yields higher accuracies of 90% for noiseless data compared with 85%, 85.9%, and 89.5% in other experiments.
The accuracy for the proposed method is 80% when SNR=1 dB, 84% when SNR=5 dB, and 88% when SNR=10 dB, while the compression ratio (CR) is 85.35% for all of the datasets mentioned.
American Psychological Association (APA)
Abualsaud, Khalid& Mahmuddin, Massudi& Saleh, Mohammad& Mohamed, Amr. 2015. Ensemble Classifier for Epileptic Seizure Detection for Imperfect EEG Data. The Scientific World Journal،Vol. 2015, no. 2015, pp.1-15.
https://search.emarefa.net/detail/BIM-1079310
Modern Language Association (MLA)
Abualsaud, Khalid…[et al.]. Ensemble Classifier for Epileptic Seizure Detection for Imperfect EEG Data. The Scientific World Journal No. 2015 (2015), pp.1-15.
https://search.emarefa.net/detail/BIM-1079310
American Medical Association (AMA)
Abualsaud, Khalid& Mahmuddin, Massudi& Saleh, Mohammad& Mohamed, Amr. Ensemble Classifier for Epileptic Seizure Detection for Imperfect EEG Data. The Scientific World Journal. 2015. Vol. 2015, no. 2015, pp.1-15.
https://search.emarefa.net/detail/BIM-1079310
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1079310