Fetal electrocardiogram (FECG) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during labor. The ultimate reason for the interest in FECG signal analysis is in clinical diagnosis and biomedical applications. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies are becoming very important requirements in fetal monitoring. The purpose of this review paper is to illustrate the various methodologies and developed algorithms on FECG signal detection and analysis to provide efficient and effective ways of understanding the FECG signal and its nature for fetal monitoring. A comparative study has been carried out to show the performance and accuracy of various methods of FECG signal analysis for fetal monitoring. Finally, this paper further focused some of the hardware implementations using electrical signals for monitoring the fetal heart rate. This paper opens up a passage for researchers, physicians, and end users to advocate an excellent understanding of FECG signal and its analysis procedures for fetal heart rate monitoring system.

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Detection and Processing Techniques of FECG Signal for Fetal Monitoring

We present in this paper an algorithm of filtering the noisy real ECG signal. The classical wavelet denoising process, based on the Donoho et al. algorithm, at the 4th level, appears clearly the P and T waves whereas the R waves undergo considerable distortion. This is due to the interference of the WGN and the free noise ECG detail sequences at level 4. To overcome this drawback, our key idea is to estimate the corrupted WGN and consequently remove the noise interfering R waves at the 4th level detail sequence. Our denoising algorithm was applied to a set of the MIT-BIH arrhythmia database ECG records corrupted with a 0 dB WGN which provided an output SNR of around 6 dB and an MSE value of around 0.0011. A comparative analysis using the low pass Butterworth filter and the 4th level classical wavelet denoising provides the output SNR values of around 3 dB and MSE value of around 0.0018; which demonstrates the superior performance of our proposed denoising algorithm

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Wavelet denoising of the electrocardiogram signal based on the corrupted noise estimation

Apparatus for monitoring fetal health during labour detects the occurrence of a fetal ECG in digital signals derived from electrodes on a fetus using a matched filter routine 36 to detect a QRS complex. The peaks of successive R waves are then found (operation 38) and used to determine fetal heart rate (operation 41). After time coherent filtering of digital samples representing the fetal ECG (operation 45) the P-R interval and the elevation of the S-T interval are found (operations 47 and 48) and a correlation coefficient between the fetal heart rate and the P-R interval is derived (operation 49). The elevation and the coefficient are displayed. If the correlation coefficient becomes positive for about half an hour and a significant fall in the elevation of the S-T interval also occurs it is an indication of acidosis of the fetus.

Fetal monitoring during labour

The normal condition of the fetal electrocardiogram during labour

This paper presents a new method for extracting the Foetal Electrocardiogram (FECG) signal form the two ECG signals recorded at the thoracic and abdominal areas of the mother's skin. The thoracic ECG is assumed to be completely maternal ECG (MECG) while the abdominal ECG is assumed to be a combination of mother's and foetus's ECG signals and random noise. The maternal component of the in the abdominal ECG is a nonlinearly transformed version of the MECG. The method uses Adaptive Nero-Fuzzy Inference System (ANFIS) structure for identifying the nonlinear transformation. We have used Particle Swarm Optimization (PSO) as a new tool for training the ANFIS structure. By identifying the nonlinear transformation, we have extracted FECG by subtracting the aligned version of the MECG signal from the abdominal ECG (AECG) signal. We validate our new method on both real and synthetic ECG signals. For synthetic signals, we have used a subjective criterion in addition to objective criteria. The results of extracting the FECG are promising comparing with conventional methods.

J.E.A. Sheild

Papers

The use of digital filters in enhancing the fetal electrocardiogram