145 citations · 257 across the 14 of their papers we have counts for
15 papers
Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy
John M O'Toole, Sean R Mathieson, Sumit A Raurale +4
This report describes a set of neonatal electroencephalogram (EEG) recordings graded according to the severity of abnormalities in the background pattern. The dataset consists of 1…
Classification of fetal compromise during labour: signal processing and feature engineering of the cardiotocograph
M. O'Sullivan, T. Gabruseva, G. Boylan +3
Cardiotocography (CTG) is the main tool used for fetal monitoring during labour. Interpretation of CTG requires dynamic pattern recognition in real time. It is recognised as a diff…
Tracé alternant detector for grading hypoxic-ischemic encephalopathy in neonatal EEG
Sumit A. Raurale, Geraldine B. Boylan, Sean R. Mathieson +3
Electroencephalography (EEG) is an important clinical tool to capture sleep-wake cycling. It can also be used for grading injury, known as hypoxic-ischaemic encephalopathy(HIE), ca…
Deep Learning for EEG Seizure Detection in Preterm Infants
Alison OShea, Rehan Ahmed, Gordon Lightbody +7
EEG is the gold standard for seizure detection in the newborn infant, but EEG interpretation in the preterm group is particularly challenging; trained experts are scarce and the ta…
Neonatal seizure detection from raw multi-channel EEG using a fully convolutional architecture
Alison O'Shea, Gordon Lightbody, Geraldine Boylan +1
A deep learning classifier for detecting seizures in neonates is proposed. This architecture is designed to detect seizure events from raw electroencephalogram (EEG) signals as opp…
Grading the severity of hypoxic-ischemic encephalopathy in newborn EEG using a convolutional neural network
Sumit A. Raurale, Geraldine B. Boylan, Gordon Lightbody +1
Electroencephalography (EEG) is a valuable clinical tool for grading injury caused by lack of blood and oxygen to the brain during birth. This study presents a novel end-to-end arc…
Identifying trace alternant activity in neonatal EEG using an inter-burst detection approach
Sumit A. Raurale, Geraldine B. Boylan, Gordon Lightbody +1
Electroencephalography (EEG) is an important clinical tool for reviewing sleep-wake cycling in neonates in intensive care. Trace alternant (TA)-a characteristic pattern of EEG acti…
Suitability of an inter-burst detection method for grading hypoxic-ischemic encephalopathy in newborn EEG
Sumit A. Raurale, Saif Nalband, Geraldine B. Boylan +2
Electroencephalography (EEG) is an important clinical tool for grading injury caused by lack of oxygen or blood to the brain during birth. Characteristics of low-voltage waveforms,…
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…
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…
Decentralised L1 Adaptive Primary Controllers and Distributed Consensus-Based Secondary Control for DC Microgrids with Constant-Power Loads
Daniel O'Keeffe, Stefano Riverso, Laura Albiol-Tendillo +1
Constant-power loads are notoriously known to destabilise power systems, such as DC microgrids, due to their negative incremental impedance. This paper equips distributed generatio…
A Distributed Scalable Architecture using L1 Adaptive Controllers for Primary Voltage Control of DC Microgrids
Daniel O'Keeffe, Stefano Riverso, Laura Albiol-Tendillo +1
This paper proposes a new distributed control architecture for distributed generation units in heterogeneous DC islanded microgrids. Each unit is equipped with state-feedback basel…
Voltage Control of DC Islanded Microgrids: Scalable Decentralised L1 Adaptive Controllers
Daniel O'Keeffe, Stefano Riverso, Laura Albiol-Tendillo +1
Voltage stability is a critical feature of an efficiently operating power distribution system such as a DC islanded microgrid. Large-scale autonomous power systems can be defined b…
Global Asymptotic Stability for General Linear MIMO Distributed Systems: An Approach Based on Robust-Adaptive Controllers
Daniel O'Keeffe, Stefano Riverso, Laura Albiol-Tendillo +1
Stability is a critical feature of distributed linear multi-input-multi-output systems. Global asymptotic stability usually can be guaranteed when using decentralised or distribute…
Neonatal Seizure Detection using Convolutional Neural Networks
Alison O'Shea, Gordon Lightbody, Geraldine Boylan +1
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 neonat…