Neonatal seizure monitoring using non-linear EEG analysis

• Published in: Neuropediatrics Vol. 35; no. 6; p. 329
• Main Authors: Smit, L S, Vermeulen, R J, Fetter, W P F, Strijers, R L M, Stam, C J
• Format: Journal Article
• Language: English
• Published: Germany 01.12.2004
• Subjects: Cortical Synchronization - statistics & numerical data; Epilepsy, Benign Neonatal - diagnosis; Epilepsy, Benign Neonatal - physiopathology; Humans; Infant, Newborn; Likelihood Functions; Nonlinear Dynamics; Reproducibility of Results; Retrospective Studies; Sensitivity and Specificity; Signal Processing, Computer-Assisted
• ISSN: 0174-304X
• DOI: 10.1055/s-2004-830367

Birth asphyxia is a major concern in neonatal care. Epileptic seizures are associated with subsequent neurodevelopmental deficits. Eighty-five percent of these seizures remain subclinical and therefore an on-line monitoring device is needed. In an earlier study we showed that the synchronization likelihood was able to distinguish between neonatal EEG epochs with and without epileptic seizures. In this study we investigated whether the synchronization likelihood can be used in complete EEGs, without artifact removal. Twenty complete EEGs from 20 neonatal patients were studied. The synchronization likelihood was calculated and correlated with the visual scoring done by 3 experts. In addition, we determined the influence of seizure length on the likelihood of detection. Using the raw unfiltered EEG data we found a sensitivity of 65.9 % and a specificity of 89.8 % for the detection of seizure activity in each epoch. In addition, the seizure detection rate was 100 % when the seizures lasted for 100 seconds or more. The synchronization likelihood seems to be a useful tool in the automatic monitoring of epileptic seizures in infants on the neonatal ward. Due to the retrospective nature of our study, the consequences for clinical intervention cannot yet be determined and prospective studies are needed. Therefore, we will conduct a prospective study on the neonatal intensive care unit with a recently developed on-line version of the synchronization likelihood analysis.