Combination of EEG and ECG for improved automatic neonatal seizure detection.
OBJECTIVE
Neonatal seizures are the most common central nervous system disorder in newborn infants. A system that could automatically detect the presence of seizures in neonates would be a significant advance facilitating timely medical intervention.


METHODS
A novel method is proposed for the robust detection of neonatal seizures through the combination of simultaneously-recorded electroencephalogram (EEG) and electrocardiogram (ECG). A patient-specific and a patient-independent system are considered, employing statistical classifier models.


RESULTS
Results for the signals combined are compared to results for each signal individually. For the patient-specific system, 617 of 633 (97.52%) expert-labelled seizures were correctly detected with a false detection rate of 13.18%. For the patient-independent system, 516 of 633 (81.44%) expert-labelled seizures were correctly detected with a false detection rate of 28.57%.


CONCLUSIONS
A novel algorithm for neonatal seizure detection is proposed. The combination of an ECG-based classifier system with a novel multi-channel EEG-based classifier system has led to improved seizure detection performance. The algorithm was evaluated using a large data-set containing ECG and multi-channel EEG of realistic duration and quality.


CONCLUSIONS
Analysis of simultaneously-recorded EEG and ECG represents a new approach in seizure detection research and the detection performance of the proposed system is a significant improvement on previous reported results for automated neonatal seizure detection.
Greene
Barry R
BR
School of Electrical, Electronic & Mechanical Engineering, University College Dublin, Ireland. barry.greene@ee.ucd.ie
Boylan
Geraldine B
GB
Reilly
Richard B
RB
de Chazal
Philip
P
Connolly
Sean
S
D000465:Algorithms; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography; D004569:Electroencephalography; D005260:Female; D006801:Humans; D007231:Infant, Newborn; D008297:Male; D008959:Models, Neurological; D012640:Seizures / Q000175:diagnosis* / Q000503:physiopathology*; D012680:Sensitivity and Specificity