activity
20172022
most citedNeonatal seizure detection from raw multi-channel EEG using a fully convolutional architecture

145 citations · 291 across the 14 of their papers we have counts for

collaborators
Showing 2018Show all

5 papers · 1 filter

q-bio.NC2018

Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms

Mark O'Sullivan, Sergi Gomez, Alison O'Shea +6

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 neo…

q-bio.NC2018

On sound-based interpretation of neonatal EEG

Sergi Gomez, Mark O'Sullivan, Emanuel Popovici +3

Significant training is required to visually interpret neonatal EEG signals. This study explores alternative sound-based methods for EEG interpretation which are designed to allow…

stat.AP2018

Heart Rate Variability during Periods of Low Blood Pressure as a Predictor of Short-Term Outcome in Preterms

Oksana Semenova, Giorgia Carra, Gordon Lightbody +3

Efficient management of low blood pressure (BP) in preterm neonates remains challenging with a considerable variability in clinical practice. The ability to assess preterm wellbein…

physics.med-ph2018

System Level Framework for Assessing the Accuracy of Neonatal EEG Acquisition

Mark O'Sullivan, Emanuel Popovici, Andrea Bocchino +3

Significant research has been conducted in recent years to design low-cost alternatives to the current EEG monitoring systems used in healthcare facilities. Testing such systems on…

stat.ML2018★ 15 cited

Investigating the Impact of CNN Depth on Neonatal Seizure Detection Performance

Alison O'Shea, Gordon Lightbody, Geraldine Boylan +1

This study presents a novel, deep, fully convolutional architecture which is optimized for the task of EEG-based neonatal seizure detection. Architectures of different depths were…