Separation of nonstationary EEG epileptic seizures using time-frequency-based blind signal processing techniques

Thuy-Duong, Nguyen Thi, Linh-Trung, Nguyen, Tran-Duc, Tan and Boashash, Boualem (2013). Separation of nonstationary EEG epileptic seizures using time-frequency-based blind signal processing techniques. In: Vo Van Toi, Nguyen Bao Toan, Truong Quang Dang Khoa and Tran Ha Lien Phuong, 4th International Conference on Biomedical Engineering in Vietnam. 4th International Conference on the Development of Biomedical Engineering in Vietnam, Ho Chi Minh City, Vietnam, (317-323). 8-12 January 2012. doi:10.1007/978-3-642-32183-2_79


Author Thuy-Duong, Nguyen Thi
Linh-Trung, Nguyen
Tran-Duc, Tan
Boashash, Boualem
Title of paper Separation of nonstationary EEG epileptic seizures using time-frequency-based blind signal processing techniques
Conference name 4th International Conference on the Development of Biomedical Engineering in Vietnam
Conference location Ho Chi Minh City, Vietnam
Conference dates 8-12 January 2012
Proceedings title 4th International Conference on Biomedical Engineering in Vietnam
Series IFMBE Proceedings
Place of Publication Berlin, Germany
Publisher Springer
Publication Year 2013
Sub-type Fully published paper
DOI 10.1007/978-3-642-32183-2_79
Open Access Status
ISBN 9783642321825
9783642321832
ISSN 1680-0737
1433-9277
Editor Vo Van Toi
Nguyen Bao Toan
Truong Quang Dang Khoa
Tran Ha Lien Phuong
Volume 40
Start page 317
End page 323
Total pages 7
Chapter number 79
Total chapters 95
Collection year 2014
Abstract/Summary Epilepsy is a neural disorder in which the electrical discharge in the brain is abnormal, synchronized and excessive. Scalp Electroencephalogram (EEG) is often used in the diagnosis and treatment of epilepsy by examining the epileptic seizures and epileptic spikes. By modeling the signal acquired at each electrode of the EEG measurement system as a linear combination of source signals generated in the brain, we can apply Blind Source Separation (BSS) techniques to separate the seizures from other signals. Alternating Columns - Diagonal Centers (AC-DC) and Second-Order-Blind Identification (SOBI) are well-known BSS algorithms and have been previously applied to the separation of seizures. However, the seizure signals in new-born babies exhibit nonstationary second order statistics. In this paper, we concentrate on applying two time-frequency (TF) based algorithms: TF-SOBI and TF-UBSS to seizure separation. These algorithms are more appropriate for analyzing nonstationary signals and have not been previously applied to studies of EEG-based seizures.
Keyword Epileptic seizures
EEG
Nonstationary sources
Time-frequency representations
Under-determined blind separation
Q-Index Code B1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Conference Paper
Collections: UQ Centre for Clinical Research Publications
Official 2014 Collection
 
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