RESUMO
Perinatal hypoxia is a significant cause of brain injury in preterm infants. Neuroprotective treatments have proven beneficial when commenced within 6-8 hours post hypoxic-ischemic insult. However, as the exact time of injury is unknown, there are no current means to determine which infants are in the treatment phase of the evolving injury. Recent studies suggest epileptiform transients in the first 6-8 hours are predictive of outcome. To quantify this further an automated means of transient identification is required. In this paper we describe a method using Haar wavelets to detect spikes in the preterm fetal sheep EEG after asphyxia in utero. The method exhibits good sensitivity and selectivity over 3 specific time periods and demonstrates the feasibility of using wavelets for spike detection in fetal sheep.
Assuntos
Eletroencefalografia/métodos , Monitorização Fetal/métodos , Processamento de Sinais Assistido por Computador , Algoritmos , Animais , Asfixia/fisiopatologia , Gasometria , Análise por Conglomerados , Eletroencefalografia/instrumentação , Monitorização Fetal/instrumentação , Modelos Estatísticos , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Ovinos , Fatores de TempoRESUMO
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.
