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Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation

Investigation of epileptic electroencephalogram (EEG) signal is one of the major areas of study in the field of signal processing. The ability to detect the seizure signal and its origin within the brain is of prime importance. This paper proposes a sequential blind signal separation (BSS) based sys...

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Main Authors: Moghavvemi, M., Mehrkanoon, S.
Format: Article
Published: World Scientific Publishing 2009
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.um.edu.my/9706/
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spelling my.um.eprints.97062017-11-23T03:09:02Z http://eprints.um.edu.my/9706/ Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation Moghavvemi, M. Mehrkanoon, S. TA Engineering (General). Civil engineering (General) Investigation of epileptic electroencephalogram (EEG) signal is one of the major areas of study in the field of signal processing. The ability to detect the seizure signal and its origin within the brain is of prime importance. This paper proposes a sequential blind signal separation (BSS) based system to extract the seizure signal from scalp EEG and to pinpoint the main location of seizure signal within the brain. BSS algorithm is used to demix the EEG signal into signals with independent features. Scalp time-mapping process is applied to determine the main location of the extracted seizure signal within the brain. The algorithm has been tested on epileptic EEG signals recorded from patients for detection of the onset of seizure waves and their origin within the brain. World Scientific Publishing 2009-08 Article PeerReviewed Moghavvemi, M. and Mehrkanoon, S. (2009) Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation. Biomedical Engineering - Applications, Basis and Communications, 21 (4). pp. 287-290. ISSN 10162372 DOI: 10.4015/S1016237209001301
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Moghavvemi, M.
Mehrkanoon, S.
Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation
description Investigation of epileptic electroencephalogram (EEG) signal is one of the major areas of study in the field of signal processing. The ability to detect the seizure signal and its origin within the brain is of prime importance. This paper proposes a sequential blind signal separation (BSS) based system to extract the seizure signal from scalp EEG and to pinpoint the main location of seizure signal within the brain. BSS algorithm is used to demix the EEG signal into signals with independent features. Scalp time-mapping process is applied to determine the main location of the extracted seizure signal within the brain. The algorithm has been tested on epileptic EEG signals recorded from patients for detection of the onset of seizure waves and their origin within the brain.
format Article
author Moghavvemi, M.
Mehrkanoon, S.
author_facet Moghavvemi, M.
Mehrkanoon, S.
author_sort Moghavvemi, M.
title Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation
title_short Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation
title_full Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation
title_fullStr Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation
title_full_unstemmed Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation
title_sort detection of the onset of epileptic seizure signal from scalp eeg using blind signal separation
publisher World Scientific Publishing
publishDate 2009
url http://eprints.um.edu.my/9706/
_version_ 1643688633476055040
score 13.15806

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