DocumentCode
573207
Title
Calibration of time features and frequency features in the time-frequency domain for improved detection and classification of seizure in newborn EEG signals
Author
Bahnasy, Yomna ; Saad, Noha ; Boubchir, Larbi ; Boashash, Boualem
Author_Institution
Electr. Eng. Dept., Qatar Univ., Doha, Qatar
fYear
2012
fDate
2-5 July 2012
Firstpage
1442
Lastpage
1443
Abstract
This paper presents new time-frequency features for seizure detection in newborn EEG signals. These features are obtained by calibrating relevant time features and frequency features in the joint time-frequency domain. The proposed features allow the possibility of improving the performance of the seizure detection and classification system based on multi-class SVM classifier.
Keywords
diseases; electroencephalography; medical signal processing; signal classification; support vector machines; time-frequency analysis; calibration; classification system; improved detection; multiclass SVM classifier; newborn EEG signals; seizure detection; time features; time-frequency domain; time-frequency features; Calibration; Electroencephalography; Feature extraction; Joints; Pediatrics; Time frequency analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science, Signal Processing and their Applications (ISSPA), 2012 11th International Conference on
Conference_Location
Montreal, QC
Print_ISBN
978-1-4673-0381-1
Electronic_ISBN
978-1-4673-0380-4
Type
conf
DOI
10.1109/ISSPA.2012.6310531
Filename
6310531
Link To Document