J
John M. O'Toole
Researcher at University College Cork
Publications - 77
Citations - 1075
John M. O'Toole is an academic researcher from University College Cork. The author has contributed to research in topics: Electroencephalography & Medicine. The author has an hindex of 18, co-authored 66 publications receiving 833 citations. Previous affiliations of John M. O'Toole include Royal Brisbane and Women's Hospital & Queensland University of Technology.
Papers
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Journal ArticleDOI
Time-Frequency Processing of Nonstationary Signals: Advanced TFD Design to Aid Diagnosis with Highlights from Medical Applications
TL;DR: This article presents a methodical approach by designing adapted time-frequency (T-F) kernels for diagnosis applications with illustrations on three selected medical applications using the electroencephalogram (EEG), heart rate variability (HRV), and pathological speech signals.
Journal ArticleDOI
Measuring Time-Varying Information Flow in Scalp EEG Signals: Orthogonalized Partial Directed Coherence
Amir Omidvarnia,Ghasem Azemi,Boualem Boashash,John M. O'Toole,Paul B. Colditz,Sampsa Vanhatalo +5 more
TL;DR: The results suggest that the gOPDC method is able to remove common components akin to volume conduction effect in the scalp EEG, handles the potential challenge with different amplitude scaling within multichannel signals, and can detect directed information flow within a subsecond time scale in nonstationary multich channel EEG datasets.
Proceedings ArticleDOI
Assessing instantaneous energy in the EEG: a non-negative, frequency-weighted energy operator.
TL;DR: This work proposes an alternative frequency-weighted energy measure that uses the envelope of the derivative of the signal, which has the advantage of being nonnegative, which when applied to a detection application in newborn EEG improves performance over the Teager-Kaiser operator.
Journal ArticleDOI
Estimating functional brain maturity in very and extremely preterm neonates using automated analysis of the electroencephalogram
John M. O'Toole,Geraldine B. Boylan,Sampsa Vanhatalo,Nathan J. Stevenson,Nathan J. Stevenson +4 more
TL;DR: The proposed automated EMA estimator provides an accurate estimate of EMA in early preterm neonates, and provides a widely accessible, noninvasive and continuous assessment of functional brain maturity.
Journal ArticleDOI
Electrographic Seizures during the Early Postnatal Period in Preterm Infants
TL;DR: Electrographic seizures are infrequent within the first few days of birth in very preterm infants, and seizures in this population are difficult to detect accurately without continuous multichannel EEG monitoring.