MARTINEK, Radek, Jan NEDOMA, Marcel FAJKUS, Radana KAHANKOVA, Jaromir KONECNY, Petr JANKŮ, Stanislav KEPAK, Petr BILIK and Homer NAZERAN. A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring. Sensors. Basel: MDPI AG, vol. 17, No 4, p. 1-26. ISSN 1424-8220. doi:10.3390/s17040890. 2017.
Other formats:   BibTeX LaTeX RIS
Basic information
Original name A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring
Authors MARTINEK, Radek (203 Czech Republic), Jan NEDOMA (203 Czech Republic), Marcel FAJKUS (203 Czech Republic), Radana KAHANKOVA (203 Czech Republic), Jaromir KONECNY (203 Czech Republic), Petr JANKŮ (203 Czech Republic, guarantor, belonging to the institution), Stanislav KEPAK (203 Czech Republic), Petr BILIK (203 Czech Republic) and Homer NAZERAN (840 United States of America).
Edition Sensors, Basel, MDPI AG, 2017, 1424-8220.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10405 Electrochemistry
Country of publisher Switzerland
Confidentiality degree is not subject to a state or trade secret
Impact factor Impact factor: 2.475
RIV identification code RIV/00216224:14110/17:00100147
Organization unit Faculty of Medicine
Doi http://dx.doi.org/10.3390/s17040890
UT WoS 000400822900231
Keywords in English interferometer; fetal heart rate (fHR); maternal heart rate (mHR); EMI-free; adaptive system; Least Mean Squares (LMS) algorithm
Tags EL OK
Tags International impact, Reviewed
Changed by Changed by: Soňa Böhmová, učo 232884. Changed: 2/3/2018 16:45.
Abstract
This paper focuses on the design, realization, and verification of a novel phonocardiographic-based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio-SNR, Root Mean Square Error-RMSE, Sensitivity-S+, and Positive Predictive Value-PPV.
PrintDisplayed: 29/3/2024 16:56