Evaluation of a BSS algorithm for artifacts rejection in epileptic seizure detection

Author

Liu, Hui ; Hild, Kenneth E., II ; Gao, J.B. ; Erdogmus, Deniz ; Príncipe, José C. ; Sackellares, J. Chris

Author_Institution

Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA

Volume

1

fYear

2004

fDate

1-5 Sept. 2004

Firstpage

91

Lastpage

94

Abstract

A data efficient blind sources separation (BSS) algorithm has been applied to preprocess intracranial EEG (ECoG) for artifact rejection. After artifacts correction a recurrence time statistics T1 feature was evaluated from the ´cleaned´ data. Seizure detection performance was compared between BSS preprocessing and without preprocessing. Test results show that in a data set, for a detection rate of 96%, the false alarm rate dropped from 0.13 per hour without BSS preprocessing to 0.08 with preprocessing. For the other set of data, the false alarm rate dropped from 0.34 to 0.21 at a detection rate of 100%.

Keywords

blind source separation; electroencephalography; medical signal detection; medical signal processing; artifacts rejection; data efficient blind sources separation; epileptic seizure detection; intracranial EEG signal processing; Blind source separation; Electroencephalography; Electrooculography; Epilepsy; Independent component analysis; Signal processing; Signal processing algorithms; Source separation; Statistics; Testing; blind source separation (BSS); epileptic seizure; independent component analysis (ICA); recurrence time statistic;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE

Conference_Location

San Francisco, CA

Print_ISBN

0-7803-8439-3

Type

conf

DOI

10.1109/IEMBS.2004.1403098

Filename

1403098