This paper is focused on the design, implementation and verification of a novel method for the optimization of the control parameters (such as step size μ and filter order N) of LMS and RLS adaptive filters used for noninvasive fetal monitoring. The optimization algorithm is driven by considering the ECG electrode positions on the maternal body surface in improving the performance of these adaptive filters. The main criterion for optimal parameter selection was the Signal-to-Noise Ratio (SNR). We conducted experiments using signals supplied by the latest version of our LabVIEW-Based Multi-Channel Non-Invasive Abdominal Maternal-Fetal Electrocardiogram Signal Generator, which provides the flexibility and capability of modeling the principal distribution of maternal/fetal ECGs in the human body. Our novel algorithm enabled us to find the optimal settings of the adaptive filters based on maternal surface ECG electrode placements. The experimental results further confirmed the theoretical assumption that the optimal settings of these adaptive filters are dependent on the ECG electrode positions on the maternal body, and therefore, we were able to achieve far better results than without the use of optimization. These improvements in turn could lead to a more accurate detection of fetal hypoxia. Consequently, our approach could offer the potential to be used in clinical practice to establish recommendations for standard electrode placement and find the optimal adaptive filter settings for extracting high quality fetal ECG signals for further processing. Ultimately, diagnostic-grade fetal ECG signals would ensure the reliable detection of fetal hypoxia.

Department of Cybernetics and Biomedical Engineering Faculty of Electrical Engineering and Computer Science VSB Technical University of Ostrava 17 Listopadu 15 70833 Ostrava Czech Republic

Department of Electrical and Computer Engineering University of Texas El Paso 500 W University Ave El Paso TX 79968 USA

Department of Obstetrics and Gynecology Masaryk University and University Hospital Brno Jihlavska 20 625 00 Brno Czech Republic

Department of Telecommunications Faculty of Electrical Engineering and Computer Science VSB Technical University of Ostrava 17 Listopadu 15 70833 Ostrava Czech Republic

Institute of Medical Technology and Equipment ITAM 118 Roosevelt Str 41 800 Zabrze Poland

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