title: Multilead analysis of T-wave alternans in the ECG using principal component analysis.
abstract: T-wave alternans (TWA) is a cardiac phenomenon associated with the mechanisms leading to sudden cardiac death. Several methods exist to automatically detect and estimate TWA in the ECG on a single-lead basis, and their main drawback is their poor sensitivity to low-amplitude TWA. In this paper, we propose a multilead analysis scheme to improve the detection and estimation of TWA. It combines principal component analysis with a single-lead method based on the generalized likelihood ratio test. The proposed scheme is evaluated and compared to a single-lead scheme by means of a simulation study, in which different types of simulated and physiological noise are considered under realistic conditions. Simulation results show that the multilead scheme can detect TWA with an SNR 30 dB lower and allows the estimation of TWA with an SNR 25 dB lower than the single-lead scheme. The two analysis schemes are also applied to stress test ECG records. Results show that the multilead scheme provides a higher detection power and that TWA detections obtained with this scheme are significantly different in healthy volunteers and ischemic patients, whereas they are not with the single-lead scheme.
authors.affiliation: Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Communications Technology Group, Aragón Institute of Engineering Research, University of Zaragoza, Zaragoza 50018, Spain. violeta.monasterio@unizar.es
authors.forename: Violeta
authors.initials: V
authors.lastname: Monasterio
authors.forename: Pablo
authors.initials: P
authors.lastname: Laguna
authors.forename: Juan Pablo
authors.initials: JP
authors.lastname: Martínez
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D004562:Electrocardiography / Q000379:methods*; D005080:Exercise Test; D006801:Humans; D009010:Monte Carlo Method; D025341:Principal Component Analysis / Q000379:methods*; D012815:Signal Processing, Computer-Assisted