Next Article in Journal
Influence of WC-Based Pin Tool Profile on Microstructure and Mechanical Properties of AA1100 FSW Welds
Previous Article in Journal
Electrical Discharge Machining Non-Conductive Ceramics: Combination of Materials
Open AccessArticle

Investigation of Methods to Extract Fetal Electrocardiogram from the Mother’s Abdominal Signal in Practical Scenarios

1
Department of Electrical Engineering and Computer Science, University of California, Irvine, CA 92697, USA
2
Department of Electronics and Computer Engineering, Hanoi University of Science and Technology, Hanoi 10000, Vietnam
3
Division of Engineering and Mathematics, University of Washington, Bothell Campus, Bothell, WA 98011, USA
4
Sensoriis, Inc., Edmonds, WA 98026, USA
5
Department of Biomedical Engineering, University of California, Irvine, CA 92697, USA
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Technologies 2020, 8(2), 33; https://doi.org/10.3390/technologies8020033
Received: 2 May 2020 / Revised: 30 May 2020 / Accepted: 3 June 2020 / Published: 5 June 2020
Monitoring of fetal electrocardiogram (fECG) would provide useful information about fetal wellbeing as well as any abnormal development during pregnancy. Recent advances in flexible electronics and wearable technologies have enabled compact devices to acquire personal physiological signals in the home setting, including those of expectant mothers. However, the high noise level in the daily life renders long-entrenched challenges to extract fECG from the combined fetal/maternal ECG signal recorded in the abdominal area of the mother. Thus, an efficient fECG extraction scheme is a dire need. In this work, we intensively explored various extraction algorithms, including template subtraction (TS), independent component analysis (ICA), and extended Kalman filter (EKF) using the data from the PhysioNet 2013 Challenge. Furthermore, the modified data with Gaussian and motion noise added, mimicking a practical scenario, were utilized to examine the performance of algorithms. Finally, we combined different algorithms together, yielding promising results, with the best performance in the F1 score of 92.61% achieved by an algorithm combining ICA and TS. With the data modified by adding different types of noise, the combination of ICA–TS–ICA showed the highest F1 score of 85.4%. It should be noted that these combined approaches required higher computational complexity, including execution time and allocated memory compared with other methods. Owing to comprehensive examination through various evaluation metrics in different extraction algorithms, this study provides insights into the implementation and operation of state-of-the-art fetal and maternal monitoring systems in the era of mobile health. View Full-Text
Keywords: fetal ECG extraction; independent component analysis (ICA); extended Kalman filter (EKF); blind source separation (BSS); fetal home monitoring fetal ECG extraction; independent component analysis (ICA); extended Kalman filter (EKF); blind source separation (BSS); fetal home monitoring
Show Figures

Figure 1

MDPI and ACS Style

Sarafan, S.; Le, T.; Naderi, A.M.; Nguyen, Q.-D.; Kuo, B. .-Y.; Ghirmai, T.; Han, H.-D.; Lau, M.P.H.; Cao, H. Investigation of Methods to Extract Fetal Electrocardiogram from the Mother’s Abdominal Signal in Practical Scenarios. Technologies 2020, 8, 33.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop