A Novel Method for Fetal ECG Extraction using ICA based Wavelet Transform
A Novel Method for Fetal ECG Extraction using ICA based Wavelet Transform |
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| © 2023 by IJETT Journal | ||
| Volume-71 Issue-8 |
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| Year of Publication : 2023 | ||
| Author : P. Darsana, Vaegae Naveen Kumar |
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| DOI : 10.14445/22315381/IJETT-V71I8P211 | ||
How to Cite?
P. Darsana, Vaegae Naveen Kumar, "A Novel Method for Fetal ECG Extraction using ICA based Wavelet Transform," International Journal of Engineering Trends and Technology, vol. 71, no. 8, pp. 131-142, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I8P211
Abstract
Developing an intelligent technique to monitor fetal heart function at the beginning stages of pregnancy is crucial, and the research aims to achieve that by proposing two hybrid algorithms. The proposed algorithms integrate independent component analysis (ICA) and stationary wavelet transform (SWT) to extract fetal electrocardiogram (FECG) signals. The objective is to improve the clarity of the FECG signal, reduce noise and artifacts, and accurately detect the R-peaks using an improved spatially selective noise filtration (ISSNF) method or a threshold-based algorithm (TBA) in the wavelet domain. Accurate detection of fetal R-peaks can provide valuable clinical information for diagnosing and treating fetal heart conditions. In order to isolate the FECG signal from the mixed abdominal signal, the study utilizes ICA to separate the maternal ECG (MECG) and FECG signals. The signals with high noise levels are subsequently broken down into multiscale components utilizing SWT, with the choice of wavelet decomposition scale determined by the noise level. Either the ISSNF or TBA methods are utilized for denoising in the wavelet domain. The performance of the proposed methodology is assessed by making use of three clinical databases through qualitative and quantitative measures, including visual inspection, computation of signal-to-noise ratio (SNR), and recognition of the QRS complex. The analysis findings suggest that the proposed system, especially when utilizing the TBA, surpasses conventional techniques for FECG extraction in terms of performance. The experimental findings demonstrate that the proposed system has the potential to extract clear FECG signals with good SNR results and minimal disturbances.
Keywords
Fetal ecg, Improved spatially selective noise filtration, Independent component analysis, Stationary wavelet transforms, Threshold-based algorithm.
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