Technical data sheet: Adaptive Match Filter Method (AMFM) to T-wave alternans detection


Language: Matlab, exe




TWA is, by definition, characterized by a specific frequency, that is fTWA. To account for physiological variations of the RR interval, a narrow frequency band, instead of a single frequency, was assumed by Adaptive Match Filter method to characterize the TWA phenomenon. On this basis, the Adaptive Match Filter (AMF) was implemented as a 6th order bidirectional Butterworth pass-band filter having the passing band 2·dfTWA=0.12 Hz wide and centered in fTWA. In particular, the AMF consisted of a cascade of a low pass filter (LPF) with cut-off frequency fLPF= fTWA+ dfTWA, and a high pass filter (HPF) with a cut-off frequency fHPF= fTWA-dfTWA.


The inputs of the method are a prefiltered ECG signal and an ‘annotations matrix’ having information about some parameters like R-Peaks sequence, J time-series ( end of QRS complexes ) and Ton , Tmax  e Toff  time-series that are respectively the beginning, the apex and the end of each T-wave. The output is a sinusoidal signal, shown in Fig.1, characterized by a possibly amplitude modulation, with its maxima and minima occurring in correspondence of the T waves. Thus, the TWA amplitude ATWA is obtained as the mean TWA-signal amplitude whereas the minima/maxima location, driven  by the TWA-signal phase as shown in Fig.2, provides the TWA location or delay DTWA (measured with respect to the previous R peak).



       Fig.1. Simulated ECG with TWA (filter input) and corresponding TWA signal (filter output).




Fig. 2. ECG signal with overlapping the TWA signal (dotted) with different phases : “Early TWA” (localized along the ST segment and the first half of the T-wave), “Central TWA” (occurring around the T-wave apex) and “Late TWA” (involving the last part of the T-wave).




Block diagram









+ capable to provide a correct detection of time-varying TWA-amplitude signals;

+ preprocessing stage not required;

+ not significantly affected by all interferences (residual noise, baseline wandering and respiration modulation ) due to the fact that  the heart-rate adaptive match filter, which receives the ECG tracing as input  yields the suppression of all ECG and interferences frequency components;

+ it is not affected by the presence of misalignments because it does not rely on T-wave windowing.





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