Search Results for author: Geraldine Boylan

Found 6 papers, 1 papers with code

Neonatal seizure detection from raw multi-channel EEG using a fully convolutional architecture

no code implementations28 May 2021 Alison O'Shea, Gordon Lightbody, Geraldine Boylan, Andriy Temko

The system performance is assessed on a large database of continuous EEG recordings of 834h in duration; this is further validated on a held-out publicly available dataset and compared with two baseline SVM based systems.

EEG Seizure Detection

Estimation of Continuous Blood Pressure from PPG via a Federated Learning Approach

1 code implementation24 Feb 2021 Eoin Brophy, Maarten De Vos, Geraldine Boylan, Tomas Ward

To our knowledge, this framework is the first example of a GAN capable of continuous ABP generation from an input PPG signal that also uses a federated learning methodology.

Federated Learning Time Series

Investigating the Impact of CNN Depth on Neonatal Seizure Detection Performance

no code implementations8 Jun 2018 Alison O'Shea, Gordon Lightbody, Geraldine Boylan, Andriy Temko

Two deep convolutional networks are compared with a shallow SVM-based neonatal seizure detector, which relies on the extraction of hand-crafted features.

EEG Seizure Detection

Neonatal Seizure Detection using Convolutional Neural Networks

no code implementations18 Sep 2017 Alison O'Shea, Gordon Lightbody, Geraldine Boylan, Andriy Temko

This study presents a novel end-to-end architecture that learns hierarchical representations from raw EEG data using fully convolutional deep neural networks for the task of neonatal seizure detection.

EEG Seizure Detection

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