Fetal phonocardiography—Past and future possibilities

2019

JBBBE

The paper presents a comparative study of three fiber optic sensors based on the fiber Bragg grating (FBG). The basic monitored parameter is the respiratory rate of the human body. Fiber-optic sensors are immune to electromagnetic interference (EMI). This fact singles them out as ideal for use in magnetic resonance environments (typically in MRI - magnetic resonance imaging) as a prediction of hyperventilation states in patients. These patient conditions arise as a result of the closed tunnel environment in MR scanners. The results (10 volunteers with written consent) were compared with the results using the conventional respiratory belt (RB) in a laboratory environment and processed using the objective Bland-Altman (B-A) method.

Section: Introductionmentioning

confidence: 99%

Fiber-Optic Breath Sensors: A Comparison Study

Nedoma

Fajkus

2019

JBBBE

“…The other promising methods are fetal phonography (

f PCG

) [7,8,9] and fetal magnetocardiography (

f MCG

) [10,11,12]. While

f ECG

is based on recording the electrical activity of the fetal heart,

f PCG

deals with recording its mechanical (acoustical) activity, and the

f MCG

is a method that registers the associated magnetic fields of the fetal heart produced as a consequence of its electrical activity [8,9,13,14].…”

Section: Introductionmentioning

confidence: 99%

Non-Invasive Fetal Monitoring: A Maternal Surface ECG Electrode Placement-Based Novel Approach for Optimization of Adaptive Filter Control Parameters Using the LMS and RLS Algorithms

Kahánková

Nazeran

et al. 2017

Sensors

This paper is focused on the design, implementation and verification of a novel method for the optimization of the control parameters (such as step size μ and filter order N) of LMS and RLS adaptive filters used for noninvasive fetal monitoring. The optimization algorithm is driven by considering the ECG electrode positions on the maternal body surface in improving the performance of these adaptive filters. The main criterion for optimal parameter selection was the Signal-to-Noise Ratio (SNR). We conducted experiments using signals supplied by the latest version of our LabVIEW-Based Multi-Channel Non-Invasive Abdominal Maternal-Fetal Electrocardiogram Signal Generator, which provides the flexibility and capability of modeling the principal distribution of maternal/fetal ECGs in the human body. Our novel algorithm enabled us to find the optimal settings of the adaptive filters based on maternal surface ECG electrode placements. The experimental results further confirmed the theoretical assumption that the optimal settings of these adaptive filters are dependent on the ECG electrode positions on the maternal body, and therefore, we were able to achieve far better results than without the use of optimization. These improvements in turn could lead to a more accurate detection of fetal hypoxia. Consequently, our approach could offer the potential to be used in clinical practice to establish recommendations for standard electrode placement and find the optimal adaptive filter settings for extracting high quality fetal ECG signals for further processing. Ultimately, diagnostic-grade fetal ECG signals would ensure the reliable detection of fetal hypoxia.

“…Fiber-optic measurement sensors are resistant to technical artifacts such as electromagnetic interferences; therefore, they can be used in situations where it is impossible to deploy conventional EFM methods, such as during Magnetic Resonance Imaging (MRI) examination [20,21] or in wet environments. The literature shows that this sensor is demonstrably more sensitive [22,23,24,25,26] than the currently used electret microphones [27] (acoustic sensor [28,29]). These properties make fiber-optic sensors very convenient and suitable choices for the measurement of desirable (fPCG) signals.…”

Section: Introductionmentioning

confidence: 99%

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

Nedoma

Fajkus

et al. 2017

Sensors

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.