Channel selection and feature enhancement for improved epileptic seizure onset detector

This paper presents a novel architecture for a patient-specific epileptic seizure onset detector using scalp electroencephalography. The proposed architecture exploits the benefits of both channel selection and feature enhancement to improve the detector performance. The novel architecture results in higher energy difference between the pre-seizure and seizure states and hence performs better in terms of detection sensitivity and false alarm rate compared to benchmark detectors available in the literature. In detail, the proposed architecture achieves a 7% increase in sensitivity and a reduction of 9 false alarms per hour compared to the benchmark detector.