  This paper proposes and implements an intuitive and pervasive solution for
neonatal EEG monitoring assisted by sonification and deep learning AI that
provides information about neonatal brain health to all neonatal healthcare
professionals, particularly those without EEG interpretation expertise. The
system aims to increase the demographic of clinicians capable of diagnosing
abnormalities in neonatal EEG. The proposed system uses a low-cost and
low-power EEG acquisition system. An Android app provides single-channel EEG
visualization, traffic-light indication of the presence of neonatal seizures
provided by a trained, deep convolutional neural network and an algorithm for
EEG sonification, designed to facilitate the perception of changes in EEG
morphology specific to neonatal seizures. The multifaceted EEG interpretation
framework is presented and the implemented mobile platform architecture is
analyzed with respect to its power consumption and accuracy.
