| Summary: | Detection and estimation of t-wave alternans (TWA) in presence of indispensable physiological artifacts is still a challenging task, as in most of the cases, the signal of interest resides well below the noise levels. In this paper, a generalized detection theoretic framework (GDFT) is proposed for the detection and estimation of TWA from the stress test ECG signal. The analytical foundations, TWA signal modeling, and finally simulations of nine TWA detectors and estimators belonging to median match filtering, empirical mode decomposition (EMD) based match filtering, and generalized likelihood ratio test (GLRT) for GDTF are presented. GLRT schemes require noise statistics for parameter estimation and are computationally efficient. GLRT detectors outperform all the detectors including the benchmark spectral method by ≥ 2 dB for a broad spectrum of SNR ranging from -15 dB to 30 dB under Gaussian noise. EMD based strategies also outperform spectral method under Gaussian and Laplacian noise by ≥ 1 dB.
|
|---|
