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This paper proposes and implements an intuitive and pervasive solution forneonatal EEG monitoring assisted by sonification and deep learning AI thatprovides information about neonatal brain health to all neonatal healthcareprofessionals, particularly those without EEG interpretation expertise. Thesystem aims to increase the demographic of clinicians capable of diagnosingabnormalities in neonatal EEG. The proposed system uses a low-cost andlow-power EEG acquisition system. An Android app provides single-channel EEGvisualization, traffic-light indication of the presence of neonatal seizuresprovided by a trained, deep convolutional neural network and an algorithm forEEG sonification, designed to facilitate the perception of changes in EEGmorphology specific to neonatal seizures. The multifaceted EEG interpretationframework is presented and the implemented mobile platform architecture isanalyzed with respect to its power consumption and accuracy.

Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms