Despite the number of techniques developed in the literature, the extraction of a clean fetal ECG (fECG) from non-invasive recordings is still an open research issue. In this work, different wavelet-based post-processing approaches for the denoising of the fECG were evaluated. A small dataset composed of twenty signals recorded from ten pregnant women between the 21st and the 27th week of gestation was adopted. fECG extraction was accomplished by using a multireference QR-decomposition-based recursive least squares adaptive filter. Then, all signals were decomposed with the stationary wavelet transform (SWT) and stationary wavelet packet transform (SWPT), using a 7-level decomposition with Haar mother wavelet and hard-thresholding. Two different thresholds from the literature were tested: the first one is level-independent (Minimax) while the other one is level-dependent. The latter was adapted to be exploited on SWPT. The enhancement of the fetal QRS complex was analyzed by computing the improvement of the signal-to-noise ratio and the performance of a fetal QRS detector. The comparative analysis revealed how the SWT outperforms the more complex SWPT, regardless the thresholding approach.

Wavelet-Based Post-Processing Methods for the Enhancement of Non-Invasive Fetal ECG

Baldazzi G.;Sulas E.;Tumbarello R.;Raffo L.;Pani D.
2019-01-01

Abstract

Despite the number of techniques developed in the literature, the extraction of a clean fetal ECG (fECG) from non-invasive recordings is still an open research issue. In this work, different wavelet-based post-processing approaches for the denoising of the fECG were evaluated. A small dataset composed of twenty signals recorded from ten pregnant women between the 21st and the 27th week of gestation was adopted. fECG extraction was accomplished by using a multireference QR-decomposition-based recursive least squares adaptive filter. Then, all signals were decomposed with the stationary wavelet transform (SWT) and stationary wavelet packet transform (SWPT), using a 7-level decomposition with Haar mother wavelet and hard-thresholding. Two different thresholds from the literature were tested: the first one is level-independent (Minimax) while the other one is level-dependent. The latter was adapted to be exploited on SWPT. The enhancement of the fetal QRS complex was analyzed by computing the improvement of the signal-to-noise ratio and the performance of a fetal QRS detector. The comparative analysis revealed how the SWT outperforms the more complex SWPT, regardless the thresholding approach.
2019
adaptive filters, electrocardiography, medical signal processing, obstetrics, signal denoising, wavelet transforms
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/296490
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