OBJECTIVE: To investigate whether epileptic seizure activity can be distinguished from non-epileptic background activity in the neonatal electroenceplalogram (EEG), using synchronization likelihood as a measure of synchronization between EEG channels. METHODS: Forty-two 21s EEG epochs and two complete EEGs from 21 different neonatal patients in a 12-channel bipolar recording were studied (AD-conversion 16bit; sample frequency 200Hz; filter setting 0.5-30Hz). For EEG of each patient, we selected one epoch with epileptic discharges and one without. Synchronization was calculated in all epochs. In two complete EEGs, synchronization was calculated and correlated with a visual scoring of the EEG. RESULTS: Synchronization likelihood was higher in all the epochs with epileptic seizures as compared to the epochs without epileptic activity (P<0.01). When synchronization likelihood exceeded 0.11, the sensitivity for the presence of epileptic activity was 0.85 (95% confidence limits [CL(95)]=0.69-1) and the specificity was 0.75 (CL(95)=0.56-0.94).Analysis of EEG score and synchronization likelihood of two complete EEGs revealed a high correlation between the occurrence of epileptic seizures and elevated synchronization likelihood (Spearman r=0.707, P<0.001). CONCLUSIONS: The results of this study demonstrate that synchronization likelihood is a potential tool in the automatic monitoring of high-risk infants for epileptic activity on neonatal wards.
OBJECTIVE: To investigate whether epilepticseizure activity can be distinguished from non-epileptic background activity in the neonatal electroenceplalogram (EEG), using synchronization likelihood as a measure of synchronization between EEG channels. METHODS: Forty-two 21s EEG epochs and two complete EEGs from 21 different neonatal patients in a 12-channel bipolar recording were studied (AD-conversion 16bit; sample frequency 200Hz; filter setting 0.5-30Hz). For EEG of each patient, we selected one epoch with epileptic discharges and one without. Synchronization was calculated in all epochs. In two complete EEGs, synchronization was calculated and correlated with a visual scoring of the EEG. RESULTS: Synchronization likelihood was higher in all the epochs with epileptic seizures as compared to the epochs without epileptic activity (P<0.01). When synchronization likelihood exceeded 0.11, the sensitivity for the presence of epileptic activity was 0.85 (95% confidence limits [CL(95)]=0.69-1) and the specificity was 0.75 (CL(95)=0.56-0.94).Analysis of EEG score and synchronization likelihood of two complete EEGs revealed a high correlation between the occurrence of epileptic seizures and elevated synchronization likelihood (Spearman r=0.707, P<0.001). CONCLUSIONS: The results of this study demonstrate that synchronization likelihood is a potential tool in the automatic monitoring of high-risk infants for epileptic activity on neonatal wards.
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