Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal

Abstract

Fetal electrocardiography is among the most promising methods of modern electronic fetal monitoring. However, before they can be fully deployed in the clinical practice as a gold standard, the challenges associated with the signal quality must be solved. During the last two decades, a great amount of articles dealing with improving the quality of the fetal electrocardiogram signal acquired from the abdominal recordings have been introduced. This article aims to present an extensive literature survey of different non-adaptive signal processing methods applied for fetal electrocardiogram extraction and enhancement. It is limiting that a different non-adaptive method works well for each type of signal, but independent component analysis, principal component analysis and wavelet transforms are the most commonly published methods of signal processing and have good accuracy and speed of algorithms.

A review of feature selection methods in medical applications

“…Within the field of signal processing, studies include a review of biomedical signal and image processing for biomedical engineering and clinical procedures [38] and works focused on specific types of biomedical signals: for example, EEG [39], ECG [40], and EMG [41].…”

Fetal electrocardiograms, direct and abdominal with reference heartbeat annotations

“…The value of this error estimates the usefulness of the FHR signal for assessing the clinically important fetal heart rate variability from beat to beat. The last step of the research should be the evaluation whether an FECG morphology analysis (assessment of the amplitude-time relationship between particular waves) is feasible as this provides completely new diagnostic information helpful for verifying the true fetal distress in cases of a recognized suspected or abnormal FHR signal 33,54,57,58 .…”

Synthesis of Dynamic Errors Correcting Algorithm for Auto–Balancing Bridge Methods

“…The M G and M B quantities were calculated from formulas (12) and (34), while N G and N B from formulas (38) - (41).…”

“…It would also be good to combine bioelectrical impedance spectroscopy with other measurement methods such as ECG or EEG [40]- [42]. Except measuring body structure, it would be also possible to detect stress or some serious conditions [10], [41]. Potential implementation of impedance in medicine is related with fact that it reflects also the change in blood pressure, and that the obtained results are very accurate [10].…”