ICU-EEG Pattern Detection by a Convolutional Neural Network.

Journal: Annals of clinical and translational neurology
Published Date: Aug 8, 2025

Abstract

OBJECTIVE: Patients in the intensive care unit (ICU) often require continuous EEG (cEEG) monitoring due to the high risk of seizures and rhythmic and periodic patterns (RPPs). However, interpreting cEEG in real time is resource-intensive and heavily relies on specialized expertise, which is not always available. This study introduces a lightweight convolutional neural network (CNN) to automatically detect key EEG patterns, including seizures and RPPs.

Authors

  • Giulio Degano
    Neuro-Intensive Care Unit, Department of Intensive Care, University Hospital of Geneva, Geneva, Switzerland.
  • HervĂ© Quintard
    Intensive Care Unit, Geneva University Hospital, Geneva, Switzerland.
  • Andreas Kleinschmidt
    Neurology Unit, Department of Clinical Neurosciences, University Hospital of Geneva, Geneva, Switzerland.
  • Nikita Francini
    Neuro-Intensive Care Unit, Department of Intensive Care, University Hospital of Geneva, Geneva, Switzerland.
  • Oana E Sarbu
    Neuro-Intensive Care Unit, Department of Intensive Care, University Hospital of Geneva, Geneva, Switzerland.
  • Pia De Stefano
    Intensive Care Unit, Geneva University Hospital, Geneva, Switzerland.

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