| MARTINEK, Radek, Radana KAHANKOVA, Homer NAZERAN, Jaromir KONECNY, Janusz JEZEWSKI, Petr JANKŮ, Petr BILIK, Jan ZIDEK, Jan NEDOMA and Marcel FAJKUS. 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. Sensors. BASEL: MDPI AG, 2017, vol. 17, No 5, p. 1-31. ISSN 1424-8220. Available from: https://dx.doi.org/10.3390/s17051154. |
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@article{1409662,
author = {Martinek, Radek and Kahankova, Radana and Nazeran, Homer and Konecny, Jaromir and Jezewski, Janusz and Janků, Petr and Bilik, Petr and Zidek, Jan and Nedoma, Jan and Fajkus, Marcel},
article_location = {BASEL},
article_number = {5},
doi = {http://dx.doi.org/10.3390/s17051154},
keywords = {fetal ECG; adaptive filtering; Least Mean Squares (LMS) algorithm; Recursive Least Squares (RLS) algorithm},
language = {eng},
issn = {1424-8220},
journal = {Sensors},
title = {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},
volume = {17},
year = {2017}
}
TY - JOUR
ID - 1409662
AU - Martinek, Radek - Kahankova, Radana - Nazeran, Homer - Konecny, Jaromir - Jezewski, Janusz - Janků, Petr - Bilik, Petr - Zidek, Jan - Nedoma, Jan - Fajkus, Marcel
PY - 2017
TI - 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
JF - Sensors
VL - 17
IS - 5
SP - 1-31
EP - 1-31
PB - MDPI AG
SN - 14248220
KW - fetal ECG
KW - adaptive filtering
KW - Least Mean Squares (LMS) algorithm
KW - Recursive Least Squares (RLS) algorithm
N2 - 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.
ER -
MARTINEK, Radek, Radana KAHANKOVA, Homer NAZERAN, Jaromir KONECNY, Janusz JEZEWSKI, Petr JANKŮ, Petr BILIK, Jan ZIDEK, Jan NEDOMA and Marcel FAJKUS. 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. \textit{Sensors}. BASEL: MDPI AG, 2017, vol.~17, No~5, p.~1-31. ISSN~1424-8220. Available from: https://dx.doi.org/10.3390/s17051154.
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