DocumentCode :
471666
Title :
Detection of Bursts in the EEG of Post Asphyctic Newborns
Author :
Lofhede, J. ; Lofgren, N. ; Thordstein, M. ; Flisberg, A. ; Kjellmer, I. ; Lindecrantz, K.
Author_Institution :
Sch. of Eng., Univ. Coll. of Boras
fYear :
2006
fDate :
Aug. 30 2006-Sept. 3 2006
Firstpage :
2179
Lastpage :
2182
Abstract :
Eight features inherent in the electroencephalogram (EEG) have been extracted and evaluated with respect to their ability to distinguish bursts from suppression in burst-suppression EEG. The study is based on EEG from six full term infants who had suffered from lack of oxygen during birth. The features were used as input in a neural network, which was trained on reference data segmented by an experienced electroencephalographer. The performance was then evaluated on validation data for each feature separately and in combinations. The results show that there are significant variations in the type of activity found in burst-suppression EEG from different subjects, and that while one or a few features seem to be sufficient for most patients in this group, some cases require specific combinations of features for good detection to be possible
Keywords :
electroencephalography; feature extraction; learning (artificial intelligence); medical signal processing; neural nets; obstetrics; burst detection; burst-suppression EEG; data segmentation; electroencephalogram; feature extraction; neural network training; post asphyctic newborns; Asphyxia; Band pass filters; Cities and towns; Electroencephalography; Hospitals; Neural networks; Neuroscience; Pediatrics; Sampling methods; USA Councils;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
ISSN :
1557-170X
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2006.260776
Filename :
4462221
Link To Document :
بازگشت