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.
Highlights
IntroductionFetal monitoring during pregnancy is very important for identifying many factors that may negatively affect the health of the fetus, may prevent intrauterine death (most commonly occurring in the home environment), or permanent damage to the fetus [1,2,3,4,5]
Fetal monitoring during pregnancy is very important for identifying many factors that may negatively affect the health of the fetus, may prevent intrauterine death, or permanent damage to the fetus [1,2,3,4,5]
This article focuses on introducing different types of non-adaptive methods of signal processing
Summary
Fetal monitoring during pregnancy is very important for identifying many factors that may negatively affect the health of the fetus, may prevent intrauterine death (most commonly occurring in the home environment), or permanent damage to the fetus [1,2,3,4,5]. Each fetal monitoring method has its advantages as well as disadvantages, and it should be emphasized that, regarding long-term measurements, a 20-min measurement is relatively short in order to obtain real information about the condition of the fetus This field attracts the attention of researchers focused on signal processing and noise removal, especially in the last 10 years. Description and comparison of these methods could produce useful material for those that are trying to find appropriate non-adaptive processing methods without going through a constantly increasing amount of research articles on this topic
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