Key result
A two-step preprocessing tool combining CEEMDAN and SDROM-ADF successfully removed Gaussian and ectopic noise from ECG signals, achieving a high correlation coefficient of 0.846 and an RMSE of 7.69 x 10^-5.
Why the study?
Current ECG preprocessing methods primarily address ectopic beats but do not consider technical issues that degrade signal quality for heart rate variability analysis.
Does a two-step preprocessing approach using CEEMDAN and SDROM-ADF improve noise removal and preserve heart rate variability measures in ECG recordings?
Does a two-step preprocessing approach using CEEMDAN and SDROM-ADF improve noise removal and preserve heart rate variability measures in ECG recordings?
A two-step preprocessing tool using CEEMDAN and SDROM-ADF effectively removes Gaussian and ectopic noise from ECG signals, preserving the accuracy of heart rate variability analysis.
Artifacts in the Electrocardiogram (ECG) degrade the quality of the recorded signal and are not conducive to heart rate variability (HRV) analysis. The two types of noise most often found in ECG recordings are technical and physiological artifacts. Current preprocessing methods primarily attend to ectopic beats but do not consider technical issues that affect the ECG. A secondary aim of this study was to investigate the effect of increasing increments of artifacts on 24 of the most used HRV measures. A two-step preprocessing approach for denoising HRV is introduced which targets each type of noise separately. First, the technical artifacts in the ECG are eliminated by applying complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). The second step removes physiological artifacts from the HRV signal using a combination filter of single dependent rank order mean (SDROM) and an adaptive filtering algorithm (ADF). The performance of the two-step pre-processing tool showed a high correlation coefficient of 0.846 and RMSE value of 7.69 x10 − 5 for 6% of added ectopic beats and 6dB Gaussian noise. All HRV measures studied except HF peak and LF peak are significantly affected by both types of noise. Frequecy measures of Total power, HF power, and LF power and fragmentation measures; PAS, PIP, and PSS are the most sensitive to both types of noise.
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Saleem et al. (2022) studied ECG artifacts and noise in Heart Rate Variability analysis (n=129). Two-step preprocessing approach (CEEMDAN and SDROM-ADF) vs. Noisy ECG signals and other filtering methods was evaluated on Denoising performance (correlation coefficient and RMSE) at 6% added ectopic beats and 6dB Gaussian noise. A two-step preprocessing tool combining CEEMDAN and SDROM-ADF successfully removed Gaussian and ectopic noise from ECG signals, achieving a high correlation coefficient of 0.846 and an RMSE of 7.69 x 10^-5.
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