Clifford Wavelet Entropy for Fetal ECG Extraction

Malika Jallouli; Sabrine Arfaoui; Anouar Ben Mabrouk; Carlo Cattani

doi:10.3390/e23070844

Clifford Wavelet Entropy for Fetal ECG Extraction

Entropy (Basel). 2021 Jun 30;23(7):844. doi: 10.3390/e23070844.

Authors

Malika Jallouli¹, Sabrine Arfaoui^{2

3}, Anouar Ben Mabrouk^{2

3

4}, Carlo Cattani⁵

Affiliations

¹ LATIS Laboratory of Advanced Technology and Intelligent Systems, Université de Sousse, Ecole Nationale d'Ingénieurs de Sousse, Sousse 4023, Tunisia.
² Laboratory of Algebra, Number Theory and Nonlinear Analysis, Department of Mathematics, Faculty of Sciences, University of Monastir, Avenue of the Environment, Monastir 5019, Tunisia.
³ Department of Mathematics, Faculty of Sciences, University of Tabuk, Tabuk 47512, Saudi Arabia.
⁴ Department of Mathematics, Higher Institute of Applied Mathematics and Computer Science, University of Kairouan, Street of Assad Ibn Alfourat, Kairouan 3100, Tunisia.
⁵ Engineering School (DEIM), Tuscia University, Largo dell'Università, 01100 Viterbo, Italy.

Abstract

Analysis of the fetal heart rate during pregnancy is essential for monitoring the proper development of the fetus. Current fetal heart monitoring techniques lack the accuracy in fetal heart rate monitoring and features acquisition, resulting in diagnostic medical issues. The challenge lies in the extraction of the fetal ECG from the mother ECG during pregnancy. This approach has the advantage of being a reliable and non-invasive technique. In the present paper, a wavelet/multiwavelet method is proposed to perfectly extract the fetal ECG parameters from the abdominal mother ECG. In a first step, due to the wavelet/mutiwavelet processing, a denoising procedure is applied to separate the noised parts from the denoised ones. The denoised signal is assumed to be a mixture of both the MECG and the FECG. One of the well-known measures of accuracy in information processing is the concept of entropy. In the present work, a wavelet/multiwavelet Shannon-type entropy is constructed and applied to evaluate the order/disorder of the extracted FECG signal. The experimental results apply to a recent class of Clifford wavelets constructed in Arfaoui, et al. J. Math. Imaging Vis. 2020, 62, 73-97, and Arfaoui, et al.Acta Appl. Math.2020, 170, 1-35.. Additionally, classical Haar-Faber-Schauder wavelets are applied for the purpose of comparison. Two main well-known databases have been applied, the DAISY database and the CinC Challenge 2013 database. The achieved accuracy over the test databases resulted in Se=100%, PPV=100% for FECG extraction and peak detection.

Keywords: Clifford wavelets/multiwavelets; ECG; Haar–Faber–Schauder wavelets/multiwavelets; abdominal ECG; entropy; fetal ECG; wavelets/multiwavelets.