J 2017

Non-Invasive Fetal Monitoring: A Maternal Surface ECG Electrode Placement-Based Novel Approach for Optimization of Adaptive Filter Control Parameters Using the LMS and RLS Algorithms

MARTINEK, Radek, Radana KAHANKOVA, Homer NAZERAN, Jaromir KONECNY, Janusz JEZEWSKI et. al.

Basic information

Original name

Non-Invasive Fetal Monitoring: A Maternal Surface ECG Electrode Placement-Based Novel Approach for Optimization of Adaptive Filter Control Parameters Using the LMS and RLS Algorithms

Authors

MARTINEK, Radek (203 Czech Republic), Radana KAHANKOVA (203 Czech Republic), Homer NAZERAN (840 United States of America), Jaromir KONECNY (203 Czech Republic), Janusz JEZEWSKI (616 Poland), Petr JANKŮ (203 Czech Republic, guarantor, belonging to the institution), Petr BILIK (203 Czech Republic), Jan ZIDEK (203 Czech Republic), Jan NEDOMA (203 Czech Republic) and Marcel FAJKUS (203 Czech Republic)

Edition

Sensors, BASEL, MDPI AG, 2017, 1424-8220

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10405 Electrochemistry

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

Impact factor

Impact factor: 2.475

RIV identification code

RIV/00216224:14110/17:00100145

Organization unit

Faculty of Medicine

UT WoS

000404553300215

Keywords in English

fetal ECG; adaptive filtering; Least Mean Squares (LMS) algorithm; Recursive Least Squares (RLS) algorithm

Tags

Tags

International impact, Reviewed
Změněno: 2/3/2018 16:27, Soňa Böhmová

Abstract

V originále

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 mu 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.