The computation time on a 24-hour Holter recording was 6 seconds for the IIR filters, 88 seconds using the DWT and 272 seconds using the SWT.
The panel A of shows how the choice of IIR and wavelet filters can affect the improvement in SNR across noise coverage. Thresholding of wavelet coefficients was done using the method proposed by Su and Zhao [3
Panel A: Improvement in SNR as a function of noise coverage. Panel B: ECG beat before and after filtering with Symmlet 8 at 90% coverage. Panel C: The same beat at a coverage of 20%.
The SNR improvements for IIR filters were constant across noise coverage. An IIR filter with a cutoff frequency of 45 Hz had the best SNR improvement (3.1 dB). The performance of the wavelet filters depended on the noise coverage. At a low coverage the wavelet filters: Daubechies 4, Symmlet 8, Coiflets 4 and Bior 3.5 were outperformed (1 dB at 10%) by the IIR filters. At higher coverages (above 50%) these wavelet filters outperformed the IIR filters (2.5 dB at 100%). The Haar wavelet performed better than the IIR filters regardless of coverage but Haar was outperformed by the other wavelet filters when noise coverage exceeded 60%. In , beats extracted from the noise segment at 90% (panel B) and 20% (panel C) coverages are shown. At low coverage the filter did not remove the added noise. However, as the coverage increased the wavelet filter removed the noise.
, panel A, shows how the choice of wavelet affects RMSE across coverage.
Panel A: RMSE as a function of noise coverage. Panel B: An ECG beat before and after filtering with Symmlet 8 at 90% coverage. Panel C: The same beat at a coverage of 20%.
The IIR filter with a cutoff frequency of 55 Hz had the lowest RMSE of 1.2. The RMSE of the Daubechies 4, Symmlet 8, Coiflets 4 and Bior 3.5 wavelets had linear trends (RMSE ≈ 0.85 at 10% and RMSE ≈ 2.25 at 90%). The Haar wavelet had a constant RMSE up to 40% coverage after which a linear increase to 4 was seen at 90% coverage. As illustrated by the Symmlet 8 wavelet in , filtering preserved the signal information at 20% coverage, while the PR and ST-segment were distorted at 90% coverage.
shows how the choice of thresholding techniques and wavelet transformations affected the improvement in SNR.
Improvements in SNR for different coverages and thresholding methods.
Thresholding using the DWT and SWT had similar performance trends across coverages but the SWT gave better SNR improvements compared to the DWT, . There was practically no difference between hard thresholding and the method proposed by Su and Zhao [3
]. Soft thresholding performed best between 10 and 50% coverage. Above 50% coverage, the performance for soft thresholding started to decrease.
supports these findings as the RMSE of the soft thresholding increased more rapidly when reaching about 50% noise coverage. The DWT and SWT again showed similar trends with the DWT having the largest RMSE.
RMSE in the non-noise segment for different coverages and thresholding methods.
The ECG with alternating muscle transients was filtered using the IIR filter with a cutoff frequency of 55 Hz, and using the Coiflet 2 wavelet (SWT) with a hard threshold. These two were selected as they were found to be associated the best performance. The coverage of the recording was 45.3%. The RMSE of the noise and non-noise segments for the IIR filter were 1.17 and 0.72 respectively, and 1.46 and 0.93 for the wavelet filtering.