EEG-Single-Channel Envelope Synchronisation and Classification for Seizure Detection and Prediction

Brain Sci. 2021 Apr 19;11(4):516. doi: 10.3390/brainsci11040516.

Abstract

This paper tackles the complex issue of detecting and classifying epileptic seizures whilst maintaining the total calculations at a minimum. Where many systems depend on the coupling between multiple sources, leading to hundreds of combinations of electrodes, our method calculates the instantaneous phase between non-identical upper and lower envelopes of a single-electroencephalography channel reducing the workload to the total number of electrode points. From over 600 h of simulations, our method shows a sensitivity and specificity of 100% for high false-positive rates and 83% and 75%, respectively, for moderate to low false positive rates, which compares well to both single- and multi-channel-based methods. Furthermore, pre-ictal variations in synchronisation were detected in over 90% of patients implying a possible prediction system.

Keywords: Alzheimer disease; DSP; Parkinsons disease; detection; envelope; epilepsy; hilbert transform; prediction; synchronisation.