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@article{1334725,
author = {Martinek, R. and Kelnar, M. and Koudelka, P. and Vanus, J. and Bilik, P. and Janků, Petr and Nazeran, H. and Zidek, J.},
article_location = {Hertford},
article_number = {22},
doi = {http://dx.doi.org/10.1049/el.2015.2222},
keywords = {diagnostic quality; electrocardiogram; extraction},
language = {eng},
issn = {0013-5194},
journal = {Electronics letters},
title = {Enhanced processing and analysis of multi-channel non-invasive abdominal foetal ECG signals during labor and delivery},
volume = {51},
year = {2015}
}
TY - JOUR
ID - 1334725
AU - Martinek, R. - Kelnar, M. - Koudelka, P. - Vanus, J. - Bilik, P. - Janků, Petr - Nazeran, H. - Zidek, J.
PY - 2015
TI - Enhanced processing and analysis of multi-channel non-invasive abdominal foetal ECG signals during labor and delivery
JF - Electronics letters
VL - 51
IS - 22
SP - 1744-1745
EP - 1744-1745
PB - Institution of Engineering and Technology
SN - 00135194
KW - diagnostic quality
KW - electrocardiogram
KW - extraction
N2 - Here the authors explore, implement and verify the potential utility of hybrid intelligent adaptive systems for processing and analysis of multi-channel non-invasive abdominal foetal electrocardiogram (fECG) signals. This approach allows clinicians to enhance non-invasive cardiotocography (CTG) with continuous ST waveform analysis (STAN) of fECG signals to improve intrapartum monitoring during labuor. The system uses a multi-channel adaptive neuro-fuzzy interference system with a new hybrid learning algorithm based on uniquely synthesised data, which comports well with real data acquired from clinical practice. The system allows the user to obtain a reference signal for objective verification. The functionality of the system has been evaluated not only by subjective criteria (an fECG morphology study by a gynaecologist), but also by objective criteria using quantitative performance metrics such as input and output signal-to-noise ratios, root mean square error, sensitivity S+, and positive predictive value among others. Experimental results indicate that hybrid neuro-fuzzy systems have the potential to improve the diagnostic and monitoring qualities (sensitivity and specificity) of fECG signals while preserving their clinically important features by leveraging the combined utility of non-invasive CTG and STAN.
ER -
MARTINEK, R., M. KELNAR, P. KOUDELKA, J. VANUS, P. BILIK, Petr JANKŮ, H. NAZERAN a J. ZIDEK. Enhanced processing and analysis of multi-channel non-invasive abdominal foetal ECG signals during labor and delivery. \textit{Electronics letters}. Hertford: Institution of Engineering and Technology, roč.~51, č.~22, s.~1744-1745. ISSN~0013-5194. doi:10.1049/el.2015.2222. 2015.
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