The adaptive-match-filter method (AMFM) avoided false-positive T-wave alternans detections in simulated data and successfully detected TWA in all clinical subjects.
The adaptive-match-filter method (AMFM) is robust against ECG interferences and suggests TWA is a continuous phenomenon from physiological to pathological conditions.
The aim was to investigate the effect of interferences surviving preprocessing (residual noise, baseline wanderings, respiration modulation, replaced beats, missed beats and T-waves misalignment) on automatic identification of T-wave alternans (TWA), an ECG index of risk for sudden cardiac death. The procedures denominated fast-Fourier-transform spectral method (FFTSM), complex-demodulation method (CDM), modified-moving-average method (MMAM), Laplacian-likelihood-ratio method (LLRM), and adaptive-match-filter method (AMFM) were applied to interferences-corrupted synthetic ECG tracings and Holter ECG recordings from control-healthy subjects (CH-group; n=25) and acute-myocardial-infarction patients (AMI group; n=25). The presence of interferences in simulated data caused detection of false-positive TWA by all techniques but the FFTSM and AMFM. Clinical applications evidenced a discrepancy in that the FFTSM and LLRM detected no more than one TWA case in each population, whereas the CDM, MMAM, and AMFM detected TWA in all CH-subjects and AMI-patients, with significantly lower TWA amplitude in the former group. Because the AMFM is not prone to false-positive TWA detections, the latter finding suggests TWA as a phenomenon having continuously changing amplitude from physiological to pathological conditions. Only occasional detection of TWA by the FFTSM and LLRM in clinics can be ascribed to their limited ability in identifying TWA in the presence of interferences surviving preprocessing.
Burattini et al. (Sat,) conducted a other in Acute myocardial infarction and healthy controls (n=50). Automatic T-wave alternans identification methods (FFTSM, CDM, MMAM, LLRM, AMFM) vs. Comparison between different identification methods was evaluated on Detection of T-wave alternans (TWA) in the presence of ECG interferences. The adaptive-match-filter method (AMFM) avoided false-positive T-wave alternans detections in simulated data and successfully detected TWA in all clinical subjects.