J 2017

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring

MARTINEK, Radek, Jan NEDOMA, Marcel FAJKUS, Radana KAHANKOVA, Jaromir KONECNY et. al.

Základní údaje

Originální název

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring

Autoři

MARTINEK, Radek (203 Česká republika), Jan NEDOMA (203 Česká republika), Marcel FAJKUS (203 Česká republika), Radana KAHANKOVA (203 Česká republika), Jaromir KONECNY (203 Česká republika), Petr JANKŮ (203 Česká republika, garant, domácí), Stanislav KEPAK (203 Česká republika), Petr BILIK (203 Česká republika) a Homer NAZERAN (840 Spojené státy)

Vydání

Sensors, Basel, MDPI AG, 2017, 1424-8220

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10405 Electrochemistry

Stát vydavatele

Švýcarsko

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 2.475

Kód RIV

RIV/00216224:14110/17:00100147

Organizační jednotka

Lékařská fakulta

UT WoS

000400822900231

Klíčová slova anglicky

interferometer; fetal heart rate (fHR); maternal heart rate (mHR); EMI-free; adaptive system; Least Mean Squares (LMS) algorithm

Štítky

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 2. 3. 2018 16:45, Soňa Böhmová

Anotace

V originále

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.