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Grant: Collaborative Health Research Projects

École de technologie supérieure

$67,000.00

Time-frequency signal processing for seizure prediction in epileptic patients

EF 2007-08

Résumé
Nearly 300,000 Canadians currently suffer from epilepsy and about 14,000 new cases are diagnosed each year. For many patients, the onset of seizures is sudden, violent and without forewarning signs to allow preventive intervention by either medicinal or other means. In this major area of mental health, increased understanding of active brain functioning (or malfunctioning) will be acquired only when research programs bringing together a variety of scientific, technological and medical specializations are given high priority, as is the case in other areas of neuroscience, such as aging. This research project proposes a methodology for intracranial EEG (electro encephalography) analysis aimed at seizure prevention. The goal is to be able to extract and quantify quasi-instantaneously as much information as possible from EEG signals to detect forewarning signs of seizures. Rather than attempting to map elementary processes involving billions of neurons interconnected in complex networks that defy any exhaustive analysis, our methodology relies on modern signal and information processing tools and implements approaches and techniques borrowed from the science of complex systems. Evaluated using real data, this software-embedded methodology, available on Internet for a large diffusion in the research community, aims to provide an EEG signal processing platform capable of quick and precise analysis allowing early warning of the onset of seizures.
Programme
Collaborative Health Research Projects
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
323490-2006
Name nom
Lina, JeanMarc
Department département
Génie électrique
Organization id
53
Institution établissement
École de technologie supérieure
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2007
Competition year année de concours
2006
Award amount
67000
Program id
CHRPJ
Program name en
Collaborative Health Research Projects
Program name fr
Projets de recherche concertée sur la santé
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
360
Committee name en
Collaborative Health Research Projects Selection Panel
Committee name fr
Comité de sélection de projets de recherche concertée sur la santé
Area of application code
1211
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Medical and health sciences
Area of application fr
Sciences médicales et de la santé
Research subject code
2514
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Digital signal processing
Research subject fr
Traitement des signaux numériques
Partie
2
Nb partie
3
Application title
Time-frequency signal processing for seizure prediction in epileptic patients
Keyword
NA
Application summary
Nearly 300,000 Canadians currently suffer from epilepsy and about 14,000 new cases are diagnosed each year. For many patients, the onset of seizures is sudden, violent and without forewarning signs to allow preventive intervention by either medicinal or other means. In this major area of mental health, increased understanding of active brain functioning (or malfunctioning) will be acquired only when research programs bringing together a variety of scientific, technological and medical specializations are given high priority, as is the case in other areas of neuroscience, such as aging. This research project proposes a methodology for intracranial EEG (electro encephalography) analysis aimed at seizure prevention. The goal is to be able to extract and quantify quasi-instantaneously as much information as possible from EEG signals to detect forewarning signs of seizures. Rather than attempting to map elementary processes involving billions of neurons interconnected in complex networks that defy any exhaustive analysis, our methodology relies on modern signal and information processing tools and implements approaches and techniques borrowed from the science of complex systems. Evaluated using real data, this software-embedded methodology, available on Internet for a large diffusion in the research community, aims to provide an EEG signal processing platform capable of quick and precise analysis allowing early warning of the onset of seizures.