Performance Analysis of Fetal-Phonocardiogram Signal Denoising Using The Discrete Wavelet Transform
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Abstract
The obligation for comprehensive fetal heart rate investigation had driven to improve the passive and non-invasive diagnostic instruments despite the USG or CTG method. Fetal phonocardiography (f-PCG) utilizing the auscultation method met the above criteria, but its interpretation frequently disturbed by the presence of noise. For instance, maternal heart and body organ sounds, fetal movements noise, and ambient noise from the environment where it is recording are the noise that corrupted the f-PCG signal. In this work, the use of discrete wavelet transforms (DWT) to eliminate noise in the f-PCG signal with SNR as the performance parameters observed. It was observing the effect of changes in wavelet type and threshold type on the SNR value. The test was carried out on f-PCG data taken from physio.net. Initial SNR values ranged from -26.7 dB to -4.4 dB; after application of DWT procedure to f-PCG, SNR increased significantly. Based on the test results obtained, wavelet type coif1 with the soft threshold gave the best result with 11.69 dB in SNR value. The coif1 had a superior result than other mother wavelets that use in this work, so the fPCG signal analysis for fetal heart rate investigation suggested to use it.
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[1]
I. Fuadina, J. Hendry, and D. Zulherman, “Performance Analysis of Fetal-Phonocardiogram Signal Denoising Using The Discrete Wavelet Transform”, INFOTEL, vol. 11, no. 4, pp. 99-107, Dec. 2019.
Section
Electronics
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References
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[2] P. Varady et. al., "An advanced method in fetal phonocardiography," in Computer methods and programs in biomedicine, vol. 71, no. -, pp. 283-296, 2003
[3] L. J. Spyridou, "Analysis of fetal heart rate in healthy and pathological pregnancies using wavelet-based featureÃ," in Annual International Conference of the IEEE EMBS, Lyon, 2007
[4] A. Sbrollini et. al., "Fetal phonocardiogram denoising wavelet transformation: robustness to noise," in Computing in Cardiology, vol. 44, no. -, pp. 1-4, 2017
[5] D. Gradolewski, G. Redlarski, "Wavelet-based denoising method for real phonocardiography signal recorded by mobile devices in a noisy environment," in Computers in Biology and Medicine, vol. 52, no. -, pp. 64-70, 2011
[6] F. Kovacs et. al., "Extended noninvasive fetal monitoring by detailed analysis of data measured with phonocardiography," in IEEE Transaction on Biomedical Engineering, vol. 58, no. 1, pp. 64-70, 2011
[7] R. Jaros et. al., "Comparison of fetal phonocardiogram de-noising by wavelet transform and the FIR filter," in 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom), Ostrava, 2018
[8] O. Heriana, A. M. A. Misbah, "Perbandingan unjuk kerja transformasi wavelet dalam denoising sinyal ECG," in Jurnal Elektronika dan Telekomunikasi (JET), vol. 17, no. 1, pp. 1-6, 2017
[9] M. Samieinasab dan R. Sameni, "Fetal phonocardiogram extraction using single-channel blind source separation," in 23rd Iranian Conference on Electrical Engineering, Tehran, 2015
[10] Chengyu Liu et. al., "An open-access database for the evaluation of heart sound algorithms," in Physiological Measurement, vol. 37, no. 12, pp.2181-2213, 2016
[11] A. L. Goldberger et al., "PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals," Circulation, 101(23):e215-e220, 2003.
[12] M. Cesarelli, M. Ruffo, M. Romano, and P. Bifulco, "Simulation of foetal phonocardiographic recordings for testing of FHR extraction algorithms," Comput Methods Programs Biomed, 107(3):513-23, September 2012.
[13] M Ruffo et al., "Non-Invasive Foetal Monitoring with Combined ECG - PCG System," In book: Biomedical Engineering, Trends in Electronics, Communications, and Software, 2011.
[14] A. K. Mittra, N. K. Choudhary, and A. S. Zadgaonkar, "Development of an artificial womb for acoustical simulation of mother’s abdomen," Int. J. Biomedical Engineering and Technology, Vol. 1, No. 3.
[15] H. E. Bassil and J.H. Dripps, "Real-time processing and analysis of fetal phonocardiographic signals," Clin. Phys. Physiol. Meas., Vol. 10, Suppl. B, 67 - 74, 1989.
[16] F. Kovacs, M. Torok, and I. Habermajer, "A rule-based phonocardiographic method for long-term fetal heart rate monitoring," IEEE Trans. on Biomed. Eng., vol. 47, no 1, January 2000.
[17] F. Kovács, C. Horváth, Á. T. Balogh, and G. Hosszú, "Fetal phonocardiography-Past and future possibilities," Computer methods and programs in biomedicine, 104, pp. 19 - 25, 2011.
[18] D. Donoho and I. Johnstone, "Adapting to unknown smoothness via wavelet shrinkage," Journal of the American Statistical Association, 90: 1200 - 1 224, 1995.
[19] K. P. Soman, K. I. Ramachandran, and N. G. Resmi, "Insight Into Wavelets From Theory to Practice," PHI Learning, 3rd ed, 2010.
[20] S. R. Messer, J. Agzarian, and D. Abbottt, "Optimal wavelet denoising for phono-cardiograms," Microelectron. J. 32 (2001) 931 - 941.
[21] Y. Song, W. Xie, J. F. Chen, and K. S. Phua, "Passive acoustic maternal abdominal fetal heart rate monitoring using the wavelet transform," Comput. Cardiol. 33 (2006) 581–584 (September).
[22] P. Varady, "Wavelet-based adaptive denoising of phonocardiographic records," in: Proceedings of the 23rd Annual Engineering in Medicine and Biology Society International Conference, Istanbul, Turkey, 2001, pp. 1846 - 1849.
[23] A. Sbrollini et al., Fetal Phonocardiogram Denoising by Wavelet Transformation: Robustness to Noise," Computing in Cardiology, Vol 44, 2017.
[24] Physionet, wfdb toolbox. [Online]. Available: https://physionet.org/physiotools/matlab/ wfdb-app-matlab/