Issue |
E3S Web Conf.
Volume 188, 2020
The 4th International Conference on Electrical Systems, Technology and Information (ICESTI 2019)
|
|
---|---|---|
Article Number | 00013 | |
Number of page(s) | 7 | |
DOI | https://doi.org/10.1051/e3sconf/202018800013 | |
Published online | 08 September 2020 |
Denoising of Fetal Phonocardiogram Signal by Wavelet Transformation
1
Electrical Engineering Department, Institut Teknologi Sepuluh Nopember, Jl. Teknik Kimia, Surabaya 60111, East Java, Indonesia
2
Electrical Engineering Department, Institut Teknologi Nasional Malang, Jl. Sigura Gura No.2, Malang 65152, East Java, Indonesia
3
School of Mathematics, Computer Science and Engineering, City, University of London, Northampton Square, Clerkenwell, London EC1V 0HB, United Kingdom
* Corresponding author: irmalia15@mhs.ee.its.ac.id
Auscultation is still one of the most basic analytical tools used to determine the fetal heart’s functional state as well as the first fetal well-being measure. It is called fetal phonocardiography (fPCG) in its modern form. The technique of fPCG is passive and can be used to track long-term. Robust signal processing techniques are required to denoise the signals in order to improve the diagnostic capabilities of fPCG. A linear filter is used to eliminate distortion and interference from the fPCG signals through conventional denoising techniques. This paper searched for optimal configuration of the wavelet based denoising system. Based on the experimental results, can be conclude that the signal should be decomposed on six levels. From this it can be seen that the lowest MSE (mean square error) value is the use of coiflets three with SURE threshold algorithm with hard threshold parameters.
Key words: Auscultation / decomposition / fetal heart sounds / threshold / mean square error
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.