Establishing a standardised approach for the measurement of neonatal noxious-evoked brain activity in response to an acute somatic nociceptive heel lance stimulus

Authors: Aspbury, Marianne ^{a, 1}, Mansfield, Roshni C. ^{a, b, ⁎, 1}, Baxter, Luke ^a, Bhatt, Aomesh ^a, Cobo, Maria M. ^{a, c}, Fitzgibbon, Sean P. ^d, Hartley, Caroline ^a, Hauck, Annalisa ^a, Marchant, Simon ^a, Monk, Vaneesha ^a, Pillay, Kirubin ^a, Poorun, Ravi ^{e, f}, van der Vaart, Marianne ^{a, 2}, Slater, Rebeccah ^{a, d, 2}

Source: In Cortex October 2024 179:215-234

Resting state electroencephalographic brain activity in neonates can predict age and is indicative of neurodevelopmental outcome

Authors: Ansari, Amir, Pillay, Kirubin, Arasteh, Emad, Dereymaeker, Anneleen, Mellado, Gabriela Schmidt, Jansen, Katrien, Winkler, Anderson M., Naulaers, Gunnar, Bhatt, Aomesh, Huffel, Sabine Van, Hartley, Caroline, Vos, Maarten De, Slater, Rebeccah, Baxter, Luke

Source: In Clinical Neurophysiology July 2024 163:226-235

A Bayesian parametric model for quantifying brain maturation from sleep-EEG in the vulnerable newborn baby

Authors: Pillay, Kirubin, Dereymaeker, Anneleen, Jansen, Katrien, Naulaers, Gunnar, Vos, Maarten De

Source: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) IEEE Engineering in Medicine and Biology Society (EMBC), 2018 40th Annual International Conference of the. :1-4 Jul, 2018

Relation: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

A unifying Bayesian approach for preterm brain-age prediction that models EEG sleep transitions over age

Authors: Pillay, Kirubin, De Vos, Maarten

Subject Terms: Statistics - Machine Learning, Computer Science - Machine Learning, Quantitative Biology - Quantitative Methods

Access URL: http://arxiv.org/abs/1809.07102

Functional brain maturation and sleep organisation in neonates with congenital heart disease

Authors: Hermans, Tim, Thewissen, Liesbeth, Gewillig, Marc, Cools, Bjorn, Jansen, Katrien, Pillay, Kirubin, De Vos, Maarten, Van Huffel, Sabine, Naulaers, Gunnar, Dereymaeker, Anneleen

Source: European journal of paediatric neurology. 36:115-122

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCvdc_100153306260.0x000001&indx=1&recIds=ETOCvdc_100153306260.0x000001

A Deep Shared Multi-Scale Inception Network Enables Accurate Neonatal Quiet Sleep Detection With Limited EEG Channels

Authors: Ansari, Amir H., Pillay, Kirubin, Dereymaeker, Anneleen, Jansen, Katrien, Van Huffel, Sabine, Naulaers, Gunnar, De Vos, Maarten

Source: IEEE journal of biomedical and health informatics. 26(3):1023-1033

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCvdc_100143626593.0x000001&indx=1&recIds=ETOCvdc_100143626593.0x000001

The impact of premature extrauterine exposure on infants’ stimulus-evoked brain activity across multiple sensory systems

Authors: Schmidt Mellado, Gabriela, Pillay, Kirubin, Adams, Eleri, Alarcon, Ana, Andritsou, Foteini, Cobo, Maria M., Evans Fry, Ria, Fitzgibbon, Sean, Moultrie, Fiona, Baxter, Luke, Slater, Rebeccah

Source: In NeuroImage: Clinical 2022 33

The PiNe box: Development and validation of an electronic device to time-lock multimodal responses to sensory stimuli in hospitalised infants.

Authors: Worley, Alan¹ (AUTHOR), Pillay, Kirubin² (AUTHOR), Cobo, Maria M.² (AUTHOR), Mellado, Gabriela Schmidt² (AUTHOR), van der Vaart, Marianne² (AUTHOR), Bhatt, Aomesh² (AUTHOR), Hartley, Caroline² (AUTHOR) caroline.hartley@paediatrics.ox.ac.uk

Source: PLoS ONE. 7/13/2023, Vol. 18 Issue 7, p1-13. 13p.

Subject Terms: *ELECTRONIC equipment, *NEURAL development, *INFANTS, *HOSPITAL supplies, *AUDITORY perception

Review of sleep-EEG in preterm and term neonates

Authors: Dereymaeker, Anneleen, Pillay, Kirubin, Vervisch, Jan, De Vos, Maarten, Van Huffel, Sabine, Jansen, Katrien, Naulaers, Gunnar

Source: Early human development. 113:87-103

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCvdc_100061902770.0x000001&indx=1&recIds=ETOCvdc_100061902770.0x000001

Applying a data-driven approach to quantify EEG maturational deviations in preterms with normal and abnormal neurodevelopmental outcomes.

Authors: Pillay, Kirubin^1,2 kirubin.pillay@paediatrics.ox.ac.uk, Dereymaeker, Anneleen³, Jansen, Katrien^3,4, Naulaers, Gunnar³, De Vos, Maarten¹

Source: Scientific Reports. 4/29/2020, Vol. 10 Issue 1, p1-14. 14p.

Subject Terms: *ELECTROENCEPHALOGRAPHY, *MENSTRUAL cycle, *NEONATAL intensive care units, *NEURODEVELOPMENTAL treatment, *BIOMARKERS

Neonatal EEG sleep stage classification based on deep learning and HMM.

Authors: Ghimatgar, Hojat, Kazemi, Kamran, Helfroush, Mohammad Sadegh, Pillay, Kirubin, Dereymaker, Anneleen, Jansen, Katrien, De Vos, Maarten, Aarabi, Ardalan

Source: Journal of Neural Engineering; Jun2020, Vol. 17 Issue 3, p1-17, 17p

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A convolutional neural network outperforming state-of-the-art sleep staging algorithms for both preterm and term infants.

Authors: Ansari, Amir H, De Wel, Ofelie, Pillay, Kirubin, Dereymaeker, Anneleen, Jansen, Katrien, Van Huffel, Sabine, Naulaers, Gunnar, De Vos, Maarten

Source: Journal of Neural Engineering; Feb2020, Vol. 17 Issue 1, p1-11, 11p

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