Key result
Biorthogonal wavelet transforms accurately estimated ECG parameters such as amplitudes and durations even under poor signal-to-noise ratios in simulation studies using real ECG data.
Biorthogonal wavelet transforms offer a robust computational method for accurately extracting ECG parameters even in noisy signals.
May aid noisy ECG analysis; leaves open prospective clinical validation before adoption.
The parameters of various morphologies of ECG waveform are basic in characterizing them as normal or otherwise. The use of multiscale analysis, through biorthogonal wavelets presented in this paper, appears very promising for such a characterization. This is on account of the fact that various morphologies are excited better at different scales. From these different scales, amplitudes, durations and various segments, widths can be determined more accurately. Simulation studies, with real ECG data, have shown that even when the signal-to-noise ratios are poor, the proposed technique can be used to accurately estimate the said parameters.
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Sivannarayana et al. (1999) studied ECG waveform analysis. Biorthogonal wavelet transforms was evaluated on Estimation of ECG parameters (amplitudes, durations, segments, widths). Biorthogonal wavelet transforms accurately estimated ECG parameters such as amplitudes and durations even under poor signal-to-noise ratios in simulation studies using real ECG data.
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