Processing EEG signals for clinical interpretation in seizure-suspected patients

Aimé Lay-Ekuakille, Giuseppe Vendramin, Amerigo Trotta, Marta De Rinaldis, Antonio Trabacca

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Epilepsy is one of the most common neurological disorders, affecting around 1 in 200 of the population. However, identifying epilepsy can be difficult because seizures tend to be relatively infrequent events and an electroencephalogram (EEG) does not always show abnormalities. The aim of this project is to develop a new methods that could improve the diagnosis of epilepsy, leading to earlier treatment and to a better quality of life for epileptic patients. The above methods must be composed with a flexible hardware development in order to discriminate noise and bad signals from correct EEG, MEG (Magnetoencephalogram) and Eye Image recognition. Even if there are EEG signal classifiers, it is suitable to perform a correct signal processing according to particular clinical reference, that is, it is difficult to have a classifier for all circumstances but it is possible to adapt EEG processing on current patient. This paper deals with a new approach of developing an architecture with a an embedded coding included in a framework agreement between University and IRCCS "E. Medea".

Original languageEnglish
Title of host publicationMeMeA 2007 2nd - IEEE International Workshop on Medical Measurement and Applications
Pages29-32
Number of pages4
DOIs
Publication statusPublished - 2007
EventMeMeA 2007 2nd - IEEE International Workshop on Medical Measurement and Applications - Warsaw, Poland
Duration: May 4 2007May 5 2007

Other

OtherMeMeA 2007 2nd - IEEE International Workshop on Medical Measurement and Applications
CountryPoland
CityWarsaw
Period5/4/075/5/07

Keywords

  • Adaptive filtering
  • Beamforming
  • Biomedical instrumentation
  • EEG signals
  • Embedded systems
  • Epilepsy
  • Signal processing

ASJC Scopus subject areas

  • Software
  • Biomedical Engineering
  • Control and Systems Engineering

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