Previous techniques for seizure detection in newborn are inefficient. The main reason for their relative poor performance resides in their assumption of stationarity of the EEG. To remedy this problem, we use time-frequency distributions (TFD) to analyse and characterise the newborn EEG seizure patterns as a first step toward a time-frequency (TF) based seizure detection and classification scheme. This paper presents the results of the analysis of these time-frequency patterns for two abnormal newborn EEGs. We demonstrate that the newborn EEG seizures are well described by a class of mono- and multi-component linear FM signals. This result is novel and contradicts the simplistic assumptions routinely made in the field.
|Number of pages||4|
|Journal||ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|
|Publication status||Published - 2001|
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering