A TIME-DOMAIN HYBRID ANALYSIS METHOD FOR DETECTING AND QUANTIFYING T-WAVE ALTERNANS

Abstract

T-wave alternans (TWA) in surface electrocardiograph (ECG) signals has been recognized as a marker of cardiac electrical instability, and is hypothesized to be related with patients at increased risk for ventricular arrhythmias. A novel timedomain TWA hybrid analysis method (HAM) utilizing the correlation method and least squares regression technique is described in this paper. Simulated ECGs containing artificial TWA (cases of absence of TWA and presence of stationary or time-varying or phase-reversal TWA) under different baseline wanderings are used to test the method, and the results shows the HAM has a better ability to quantifying TWA amplitude compared with the Correlation Method (CM) and Adapting Match Filter Method (AMFM). The HAM is subsequently used to analyze the clinical ECGs, and results produced by the HAM have, in general, demonstrated the consistency with those produced by the CM and the AMFM, while the quantifying TWA amplitudes by the HAM are universally higher than those by the other two methods.

Keywords

• electrocardiograph
• t-wave alternans
• hybrid analysis method
• correlation method
• adapting match filter method
• least squares regression