Abstract
The non-invasive Fetal Electrocardiogram (FECG) signal has become a significant method for monitoring the fetus's physiological conditions, extracted from the Abdominal Electrocardiogram (AECG) during pregnancy. The current techniques are limited during delivery for detecting and analyzing fECG. The non - intrusive fECG recorded from the mother's abdomen is contaminated by a variety of noise sources, can be a more challenging task for removing the maternal ECG. These contaminated noises have become a major challenge during the extraction of fetal ECG is managed by uni-modal technique. In this research, a new method based on the combination of Wavelet Transform (WT) and Fast Independent Component Analysis (FICA) algorithm approach to extract fECG from AECG recordings of the pregnant woman is proposed. Initially, preprocessing of a signal is done by applying a Fractional Order Butterworth Filter (FBWF). To select the Direct ECG signal which is characterized as a reference signal and the abdominal signal which is characterized as an input signal to the WT, the cross-correlation technique is used to find the signal with greater similarity among the available four abdominal signals. The model performance of the proposed method shows the most frequent similarity of fetal heartbeat rate present in the database can be evaluated through MAE and MAPE is 0.6 and 0.041209 respectively. Thus the proposed methodology of de-noising and separation of fECG signals will act as the predominant one and assist in understanding the nature of the delivery on further analysis.
Highlights
Among 80% of perinatal events, 20% of pregnancies are high risk, whereas the rest are preventable as per the record of the World Health Organization (WHO)
One of the best methods of diagnosis is fetus ECG signals which assist in analyzing the fetus status in the uterus
The proposed method is developed based on Fast Independent Component Analysis (FICA) and the undecimated Wavelet Transform (WT) that is majorly focused on extracting fetal electrocardiogram (fECG) signals
Summary
Among 80% of perinatal events, 20% of pregnancies are high risk, whereas the rest are preventable as per the record of the World Health Organization (WHO). Intelligent detection and analysis of fECG signals help in identifying the preventable ones at the earlier stage. Fetal deaths worldwide are 2.65 million annually, with 45% of intra-partum deaths can occur. Heart defects are the primary cause of mortality. Using Fetal heart rate activity many scientific community has developed a brilliant technologies to control the physiological status of the fetus [2,3]. It is possible to obtain valuable knowledge about the physiological condition of the fetus by analyzing the fECG waveform. The morphological characteristics of fetal ECG can be successfully identified using an invasive approach involving an electrode
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