Brain ictal state characterisation through multimodal information integration

Bermudez, Thomas A.R. (2009). Brain ictal state characterisation through multimodal information integration. PHD thesis, Aston University.

Abstract

This Thesis addresses the problem of automated false-positive free detection of epileptic events by the fusion of information extracted from simultaneously recorded electro-encephalographic (EEG) and the electrocardiographic (ECG) time-series. The approach relies on a biomedical case 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. The main contributions of the Thesis include the introduction of a biomedical case for the coupling of the Brain and Heart systems during temporal lobe epileptic seizures, partially reported in the clinical literature; the investigation of measures for the characterisation of ictal events from the EEG time series towards their integration in a fusion-of-knowledge framework; the probabilistic description of arrhythmias observed during temporal lobe epileptic events towards their integration in a fusion-of-knowledge framework; and the investigation of the different levels of the fusion-of-information architecture at which to perform the combination of information extracted from the EEG and ECG time-series. The performance of the method designed in the Thesis for the false-positive free automated detection of epileptic events achieved a false-positives rate of zero on the dataset of long-term recordings used in the Thesis.

Divisions: Engineering & Applied Sciences
Additional Information: Department: Department of Information Engineering If you have discovered material in AURA which is unlawful e.g. breaches copyright, (either theirs or that of a third party) or any other law, including but not limited to those relating to patent, trademark, confidentiality, data protection, obscenity, defamation, libel, then please read our Takedown Policy and contact the service immediately.
Institution: Aston University
Uncontrolled Keywords: temporal lobe epilepsy,fusion-of-information
Completed Date: 2009
Authors: Bermudez, Thomas A.R.

Download

Export / Share Citation


Statistics

Additional statistics for this record