A semi-automated method for epileptiform transient detection in the EEG of the fetal sheep using time-frequency analysis.
Perinatal hypoxia remains a significant cause of brain damage. Currently there are no biomarkers to detect the at risk brain. Recent research, however, suggests that the appearance of epileptiform transients in the first 6-8 hours after hypoxia (the latent phase of injury) are predictive of neural outcome. To quantify this further a key need is to automate EEG signal analysis to aid clinical staff with the vast amounts of complex data to review. In this study, we present a semi-automated method for spike detection in the fetal sheep EEG. The method utilizes the short time Fourier transform and peak separation to extract spikes. The performance of the method was found to be high in sensitivity and selectivity over 3 distinct time points.
Walbran
Anita C
AC
Department of Engineering Science, The University of Auckland, Auckland 1010, New Zealand. a.walbran@auckland.ac.nz
Unsworth
Charles P
CP
Gunn
Alistair J
AJ
Bennet
Laura
L
D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000175:diagnosis* / Q000196:embryology; D005315:Fetal Diseases / Q000175:diagnosis*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012756:Sheep / Q000196:embryology* / Q000502:physiology