Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: May 10, 2026

Application of an Amplitude-integrated EEG Monitor (Cerebral Function Monitor) to Neonates
05:58

Application of an Amplitude-integrated EEG Monitor (Cerebral Function Monitor) to Neonates

Published on: September 6, 2017

Robust neonatal EEG seizure detection through adaptive background modeling.

Andriy Temko1, Geraldine Boylan, William Marnane

  • 1Neonatal Brain Research Group, Department of Electrical and Electronic Engineering, University College Cork, Ireland. atemko@ucc.ie

International Journal of Neural Systems
|June 11, 2013
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Defining neonatal encephalopathy: an international real-time Delphi consensus process.

The Lancet. Child & adolescent health·2026
Same author

Efficient Edge AI for Neonatal Care: Implementing HIE Grading on Snapdragon Edge Device.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

A Deep Learning Approach to Grading Neonatal Hypoxic-Ischemic Encephalopathy Using ECG Spectrograms<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Proceedings of the 15<sup>th</sup> International Newborn Brain Conference: Neonatal Neurocritical Care, seizures, and continuous aEEG and /or EEG monitoring: Fota Island, Cork, Ireland, February 28<sup>th</sup> - March 2<sup>nd</sup> 2024.

Journal of neonatal-perinatal medicine·2025
Same author

Proceedings of the 15<sup>th</sup> International Newborn Brain Conference: Other forms of brain monitoring, such as NIRS, fMRI, biochemical, etc.: Fota Island, Cork, Ireland, February 28<sup>th</sup> - March 2<sup>nd</sup> 2024.

Journal of neonatal-perinatal medicine·2025
Same author

Proceedings of the 15<sup>th</sup> International Newborn Brain Conference: Neuro-imaging studies: Fota Island, Cork, Ireland, February 28<sup>th</sup> - March 2<sup>nd</sup> 2024.

Journal of neonatal-perinatal medicine·2025

This study introduces an adaptive probabilistic model for detecting seizures in newborns with hypoxic ischemic encephalopathy. The improved system enhances accuracy and reduces false alarms, aiding in better clinical diagnosis.

Area of Science:

  • Biomedical Engineering
  • Neonatal Neurology
  • Signal Processing

Background:

  • Hypoxic ischemic encephalopathy (HIE) poses significant risks to neonates.
  • Electroencephalogram (EEG) monitoring is crucial for detecting seizures in HIE.
  • Existing seizure detection methods face challenges with artifacts and background variability.

Purpose of the Study:

  • To develop and validate an adaptive probabilistic modeling system for neonatal seizure detection.
  • To improve the robustness of seizure detection against artifacts, particularly respiratory ones.
  • To enhance the accuracy and reduce false detections in EEG-based seizure identification.

Main Methods:

  • Adaptive probabilistic modeling of EEG background activity.
  • Utilizing the temporal derivative of seizure probability relative to background activity.

More Related Videos

Continuous Video Electroencephalogram during Hypoxia-Ischemia in Neonatal Mice
09:29

Continuous Video Electroencephalogram during Hypoxia-Ischemia in Neonatal Mice

Published on: June 11, 2020

Recording EEG in Freely Moving Neonatal Rats Using a Novel Method
08:03

Recording EEG in Freely Moving Neonatal Rats Using a Novel Method

Published on: May 29, 2017

Related Experiment Videos

Last Updated: May 10, 2026

Application of an Amplitude-integrated EEG Monitor (Cerebral Function Monitor) to Neonates
05:58

Application of an Amplitude-integrated EEG Monitor (Cerebral Function Monitor) to Neonates

Published on: September 6, 2017

Continuous Video Electroencephalogram during Hypoxia-Ischemia in Neonatal Mice
09:29

Continuous Video Electroencephalogram during Hypoxia-Ischemia in Neonatal Mice

Published on: June 11, 2020

Recording EEG in Freely Moving Neonatal Rats Using a Novel Method
08:03

Recording EEG in Freely Moving Neonatal Rats Using a Novel Method

Published on: May 29, 2017

  • Performance assessment via leave-one-patient-out cross-validation on a large clinical dataset (38 patients, 1479 h).
  • Prospective validation on an independent dataset (51 neonates, 2540 h).

    • Main Results:

    • The adaptive system increased the ROC area from 93.4% to 96.1% (41% relative improvement).
    • False detection rate decreased from 0.42 to 0.24 per hour.
    • Maintained 70% correct detection of seizure burden.
    • Results on unseen data aligned with leave-one-patient-out predictions.

    Conclusions:

    • The proposed adaptive probabilistic modeling significantly improves neonatal seizure detection accuracy.
    • The algorithm demonstrates robustness against artifacts and effective generalization to unseen data.
    • This validated approach offers a promising tool for clinical management of HIE-related seizures.