Grant: Collaborative Health Research Projects
Ryerson University
$122,048.00
Signal analysis of T-wave alternans for predicting sudden cardiac deaths
EF 2013-14
Résumé
T-wave alternans (TWA) refers to the changes in T wave shape or amplitude appearing every second heart beaton a surface electrocardiogram (ECG). The magnitude of TWA signal is very small, in the microvolt range,but some clinical trials have recently suggested that its presence can predict sudden death in patients with heartdisease. From a signal analysis perspective, the accurate measurement of the TWA signal is challenging due tovery low signal to noise ratio (SNR), and signal non-stationarity. Several noise sources can potentiallyconfound TWA signal detection, including periodic noise from movement or respiration, andnon-periodic/spurious noise.The primary objective of this proposal will be to develop a more accurate TWA detection algorithm thattackles the signal non-stationarity and provides robust measurement of TWA signal parameters even in lowSNR conditions.In the proposed techniques the non-stationarity of the TWA signal is handled by transformingthe signal to a joint time-frequency representation (TFR) which provides the time-varying spectralrepresentation. The marginals computed as first-order and second-order moments along time or frequencydirection in a proper TFR will provide features such as instantaneous frequency (IF) and instantaneousbandwidth (IBW). IF and IBW could be used to characterize the non-stationary TWA and thereby lead to betterdetection and estimation of TWA. The secondary objective will be to evaluate the accuracy of the proposedtechniques in risk stratifying patients with heart disease. This will be achieved by measuring TWA every 6months from a 24-hour ambulatory ECG recording in 450 patients with heart disease, and then following thesepatients prospectively for 2 years to determine whether TWA predicts subsequent death or nonfatal ventriculararrhythmias. Developing accurate risk assessment algorithms is essential to identify patients at highest risk ofsudden death who will derive the greatest survival benefit from costly medical device therapy, such asimplantable defibrillators.
Programme
Collaborative Health Research Projects
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
397473-2011
Name nom
Krishnan, Sridhar
Department département
Electrical and Computer Engineering
Organization id
43
Institution établissement
Ryerson University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2013
Competition year année de concours
2011
Award amount
122048
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
1102
Area of application group en
Health, education and social services
Area of application group fr
Santé publique, éducation et services sociaux
Area of application en
Biomedical engineering
Area of application fr
Génie biomédical
Research subject code
1900
Research subject group en
Biomedical engineering
Research subject group fr
Génie biomédical
Research subject en
Biomedical engineering
Research subject fr
Génie biomédical
Partie
3
Nb partie
3
Application title
Signal analysis of T-wave alternans for predicting sudden cardiac deaths
Keyword
NSERC
Application summary
T-wave alternans (TWA) refers to the changes in T wave shape or amplitude appearing every second heart beaton a surface electrocardiogram (ECG). The magnitude of TWA signal is very small, in the microvolt range,but some clinical trials have recently suggested that its presence can predict sudden death in patients with heartdisease. From a signal analysis perspective, the accurate measurement of the TWA signal is challenging due tovery low signal to noise ratio (SNR), and signal non-stationarity. Several noise sources can potentiallyconfound TWA signal detection, including periodic noise from movement or respiration, andnon-periodic/spurious noise.The primary objective of this proposal will be to develop a more accurate TWA detection algorithm thattackles the signal non-stationarity and provides robust measurement of TWA signal parameters even in lowSNR conditions.In the proposed techniques the non-stationarity of the TWA signal is handled by transformingthe signal to a joint time-frequency representation (TFR) which provides the time-varying spectralrepresentation. The marginals computed as first-order and second-order moments along time or frequencydirection in a proper TFR will provide features such as instantaneous frequency (IF) and instantaneousbandwidth (IBW). IF and IBW could be used to characterize the non-stationary TWA and thereby lead to betterdetection and estimation of TWA. The secondary objective will be to evaluate the accuracy of the proposedtechniques in risk stratifying patients with heart disease. This will be achieved by measuring TWA every 6months from a 24-hour ambulatory ECG recording in 450 patients with heart disease, and then following thesepatients prospectively for 2 years to determine whether TWA predicts subsequent death or nonfatal ventriculararrhythmias. Developing accurate risk assessment algorithms is essential to identify patients at highest risk ofsudden death who will derive the greatest survival benefit from costly medical device therapy, such asimplantable defibrillators.
