Classification of EEG signals using normal inverse Gaussian parameters in the dual-tree complex wavelet transform domain for seizure detection-Reference-Cited by-同舟云学术

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Classification of EEG signals using normal inverse Gaussian parameters in the dual-tree complex wavelet transform domain for seizure detection

Published:2014-12-31 Issue:2 Volume:10 Page:259-266
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Das Anindya Bijoy,Bhuiyan Mohammed Imamul Hassan,Alam S. M. Shafiul

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Link

http://link.springer.com/content/pdf/10.1007/s11760-014-0736-2.pdf

Reference39 articles.

1. Smith, S.J.M.: EEG in the diagnosis, classification, and management of patients with epilepsy. J. Neurol. Neurosurg. Psychiatry, 76 (Suppl II), ii2–ii7 (2005)

2. Salam, M.T., Sawan, M., Nguyen, D.K.: Low-power implantable device for onset detection and subsequent treatment of epileptic seizures. J. Healthc. Eng. 1(5), 169–184 (2010)

3. Bajaj, V., Pachori, R.B.: Classification of seizure and nonseizure EEG signals using empirical mode decomposition. IEEE Trans. Inf. Technol. Biomed. 16, 1135–1142 (2012)

4. Liu, Y., Zhou, W., Yuan, Q., Chen, S.: Automatic seizure detection using wavelet transformation and SVM in long term intra-cranial EEG. IEEE Trans. Neural Syst. Rehabil. Eng. 20(6), 749–755 (2012)

5. Shafiul Alam, S.M., Bhuiyan, M.I.H.: Detection of seizure and epilepsy using higherorder statistics in the EMD domain. IEEE J. Biomed. Health Inform. 17(2), 312–318 (2013)

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