Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Martinek, Radeka; * | Kahankova, Radanaa | Martin, Borisb | Nedoma, Janc | Fajkus, Marcelc
Affiliations: [a] Department of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, Ostrava 70833, Czech Republic | [b] Polytech Grenoble, Saint-Martin-d’Hres 38400, France | [c] Department of Telecommunications, VSB-Technical University of Ostrava, Ostrava 70833, Czech Republic
Correspondence: [*] Corresponding author: Radek Martinek, Department of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, Ostrava 70833, Czech Republic. Tel.: +123 45 678910; E-mail: [email protected].
Abstract: This paper introduces a comprehensive fetal Electrocardiogram (fECG) Signal Extraction and Analysis Virtual Instrument that integrates various methods for detecting the R-R Intervals (RRIs) as a means to determine the fetal Heart Rate (fHR) and therefore facilitates fetal Heart Rate Variability (HRV) signal analysis. Moreover, it offers the capability to perform advanced morphological fECG signal analysis called ST segment Analysis (STAN) as it seamlessly allows the determination of the T-wave to QRS complex ratio (also called T/QRS) in the fECG signal. The integration of these signal processing and analytical modules could help clinical researchers and practitioners to noninvasively monitor and detect the life threatening hypoxic conditions that may arise in different stages of pregnancy and more importantly during delivery and could therefore lead to the reduction of unnecessary C-sections. In our experiments we used real recordings from a Fetal Scalp Electrode (FSE) as well as maternal abdominal electrodes. This Virtual Instrument (Toolbox) not only serves as a desirable platform for comparing various fECG extraction signal processing methods, it also provides an effective means to perform STAN and HRV signal analysis based on proven ECG morphological as well as Autonomic Nervous System (ANS) indices to detect hypoxic conditions.
Keywords: Fetal ECG (fECG), maternal ECG (mECG), abdominal ECG (aECG), feature extraction, STAN analysis (T:QRS ratio), fetal Heart Rate (fHR), fetal Heart Rate Variability (HRV)
DOI: 10.3233/THC-181375
Journal: Technology and Health Care, vol. 27, no. 3, pp. 257-287, 2019
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]