Wavelet-based enhancement of signalaveraged electrocardiograms for late potential detection |
| |
Institution: | (1) Laboratoire Vision et Robotique, E.N.S.I de Bourges, Bourges, France;(2) Allegheny University of the Health Sciences, Pittsburgh, PA, USA |
| |
Abstract: | An optimal wavelet filter to improve the signal-to-noise ratio (SNR) of the signal-averaged electrocardiogram is described.
As the averaging technique leads to the best unbiased estimator, the challenge is to attenuate the noise while preserving
the low amplitude signals that are usually embedded in it. An optimal, in the meansquare sense, wavelet-based filter has been
derived from the model of the signal. However, such a filter needs exact knowledge of the noise statistic and the noise-free
signal. Hence, to implement such a filter, a method based on successive subaveraging and wavelet filtering is proposed. Its
performance was evaluated using simulated and real ECGs. An improvement in SNR of between 6 and 10 dB can be achieved compared
to a classical averaging technique which uses an ensemble of 64 simulated ECG beats. Tests on real ECGs demonstrate the utility
of the method as it has been shown that by using fewer beats in the filtered ensemble average, one can achieve the same noise
reduction. Clinical use of this technique would reduce the ensemble needed for averaging while obtaining the same diagnostic
result. |
| |
Keywords: | Electrocardiography Late potentials Wavelet filtering |
本文献已被 SpringerLink 等数据库收录! |
|