EEG/ECG information fusion for epileptic event detection

Thomas Bermudez*, David Lowe, Anne Marie Arlaud-Lamborelle

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication


This paper addresses the automated false positives- free detection of epileptic events by the fusion of information extracted from simultaneously recorded electroencephalographic- and electrocardiographic time-series. The approach relies on the biomedical prior knowledge for the coupling of the Brain- and Heart systems through the central autonomic network during temporal lobe epileptic events: neurovegetative manifestations associated with temporal lobe epileptic events consist of alterations to the cardiac rhythm. From a neurophysiological perspective, epileptic episodes are characterised by a loss of complexity of the state of the brain. The description of arrhythmias, from a probabilistic perspective, observed during temporal lobe epileptic events and the description of the complexity of the state of the brain, from an information theory perspective, are integrated in a fusion-of-information framework towards temporal lobe epileptic seizure detection. We show that the biomedical data fusion of simultaneously recorded EEG and ECG time-series leads to the detection of genuine epileptic events and to the dramatic reduction of false-positives.

Original languageEnglish
Title of host publicationDSP 2009: 16th International Conference on Digital Signal Processing, Proceedings
Place of PublicationPiscataway (US)
Number of pages8
ISBN (Electronic)978-1-4244-3297-4
ISBN (Print)978-1-4244-3298-1
Publication statusPublished - 20 Nov 2009
Event16th International Conference on Digital Signal Processing - Santorini, Greece
Duration: 5 Jul 20097 Jul 2009


Conference16th International Conference on Digital Signal Processing
Abbreviated titleDSP 2009


  • fusion-of-information
  • temporal lobe epilepsy


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