Time-Frequency Feature Extraction of Newborn EEG Seizure Using SVD-Based Techniques

• Main Authors: Hassanpour Hamid, Mesbah Mostefa, Boashash Boualem
• Format: Article
• Language: English
• Published: SpringerOpen 2004-01-01
• Series: EURASIP Journal on Advances in Signal Processing
• Subjects: detection; time-frequency distribution; singular value decomposition; probability distribution function
• Online Access: http://dx.doi.org/10.1155/S1110865704406167

<p/> <p>The nonstationary and multicomponent nature of newborn EEG seizures tends to increase the complexity of the seizure detection problem. In dealing with this type of problems, time-frequency-based techniques were shown to outperform classical techniques. This paper presents a new time-frequency-based EEG seizure detection technique. The technique uses an estimate of the distribution function of the singular vectors associated with the time-frequency distribution of an EEG epoch to characterise the patterns embedded in the signal. The estimated distribution functions related to seizure and nonseizure epochs were used to train a neural network to discriminate between seizure and nonseizure patterns.</p>