Abstract
Contrarily to adults and older children, the clinical signs of seizure in newborns are either subtle or occult. For this reason, the electroencephalogram (EEG) has been the most dependable tool used for detecting seizures in newborns. Given nonstationary and multicomponent EEG signals, time-frequency (TF) based methods were found to be very suitable for the analysis of such signals. The TF domain techniques are utilized to extract TF signatures that are characteristic of EEG seizures. In this paper, multichannel EEG signals are processed using a TF matched filter to detect and to geometrically localize neonatal EEG seizures. The threshold used to distinguish between seizure and nonseizure is data-dependent and is set using the EEG background. Multichannel geometrical correlation, based on a concept of incidence matrix, was utilized to further enhance the performance of the detector.
Original language | English |
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Title of host publication | ICSPC 2007 Proceedings - 2007 IEEE International Conference on Signal Processing and Communications |
Pages | 1567-1570 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 2007 |
Event | 2007 IEEE International Conference on Signal Processing and Communications, ICSPC 2007 - Dubai, United Arab Emirates Duration: Nov 14 2007 → Nov 27 2007 |
Other
Other | 2007 IEEE International Conference on Signal Processing and Communications, ICSPC 2007 |
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Country | United Arab Emirates |
City | Dubai |
Period | 11/14/07 → 11/27/07 |
Keywords
- EEG
- Matched filter
- Multichannel
- Seizure
- Time frequency
ASJC Scopus subject areas
- Computer Networks and Communications
- Signal Processing
- Communication