title: T-wave alternans detection by a combined method of principal component analysis and T-wave amplitude.
abstract: The detection of T-wave alternans (TWA) has been studied, considering various algorithms based on parameters in the temporal domain. The PhysioNet/Computers in Cardiology Challenge 2008 ('Detecting and quantifying T-wave alternans') provided a dataset consisting of 100 electrocardiographic (ECG) records for the detection or estimation of T-wave alternans. The dataset consists of 68 records from real patients (56 subjects with known risk factors for sudden cardiac death and 12 healthy subjects) and 32 synthetic ECG with calibrated amount of artificial TWA. The participation to this Challenge allowed us to test different algorithms based on two kinds of parameters: (1) the T-wave amplitude computed in a combined lead, and (2) the principal component analysis for quantifying the complexity index of the T-waves. The measurements were made for every beat, and the presence of significant differences between odd and even samples (alternans) was statistically analyzed. Two global indices (considering the beats of the entire record), two local indices (considering sets of sub-intervals) and a proper combination of them are the five indices used for the analysis of TWA detection. Our study proved a high correlation between alternans of T-amplitude and the TWA complexity index. The Challenge scores of our proposed algorithms are all higher than 0.80, and the combined method obtained the highest score among the official participants: 0.890. The PhysioNet/Challenge database was a pilot tentative to build a reference database, which allowed us to make a valuable test of our algorithms.
authors.affiliation: Institute of Biomedical Engineering ISIB - CNR, Padova, Italy. Bortolan@isib.cnr.it
authors.forename: G
authors.initials: G
authors.lastname: Bortolan
authors.forename: I
authors.initials: I
authors.lastname: Christov
mesh_terms: D000465:Algorithms; D016757:Death, Sudden, Cardiac / Q000453:epidemiology; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D025341:Principal Component Analysis; D012307:Risk Factors; D012815:Signal Processing, Computer-Assisted