GDTF: Generalized Detection Theoretic Framework for T-Wave Alternans Analysis

Ehsan Ullah,Asim Dilawar Bakhshi,Muhammad Majid

doi:10.1109/access.2020.3037130

Abstract

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.

Highlights

S UDDEN cardiac death (SCD) is one of the leading causes of death in countries, even with the most advanced health care facilities
In a cross-correlation approach for the T wave alternans (TWA) signal with decomposed components of empirical mode decomposition (EMD) for the identification of signal and noise components, the signal is more correlated with individual intrinsic mode functions (IMFs)
Contrary to classical signal processing framework like spectral method (SM) [41], modified moving average method (MMAM) [12], and correlation method (CM) [15] where decision is based on complet set of beats of TWA, in the proposed generalized detection theoretic framework (GDTF), each beat is mapped onto a decision regions R0 or R1 based on a threshold that maximizes Eq (8)

Summary

Introduction

S UDDEN cardiac death (SCD) is one of the leading causes of death in countries, even with the most advanced health care facilities. SCD is clinically defined as an unexpected death (within an hour of onset of symptoms) attributed to cardiac causes that may occur in a person with or without previous cardiac abnormalities. Micro-volt T wave alternans (TWA) has been identified as a risk indicator for fatal cardiovascular arrhythmia including SCD [1]. To validate the performance of TWA detection and estimation under generalized and realistic scenarios, real ECG signals with Gaussian and Laplacian noise are synthesized. A simplified simulated problems of TWA detection under noisy environment is considered. For this purpose, TWA is simulated as a Hamming window of unit amplitude immersed in WGN.

Methods

Results

Conclusion