Study of Denoising Method to Detect Valvular Heart Disease Using Phonocardiogram (PCG)
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Keywords:
VHD, PCG, Denoising, DWT, STFT, Low-Pass Filter
Abstract
Heart sound is a very weak acoustic signal, very susceptible to external acoustic signals and
electrical disturbances, especially friction caused by the subject's breathing or body movements.
The heart sound signal will be recorded in a phonocardiogram (PCG) and produce heart sounds,
noise, and extra sounds. The purpose of this work is to denoise the signal from the heart sounds
recorded on the PCG and determine valvular heart disease (VHD). Several methods have been
proposed for denoising heart sound signals, both in the time domain and in the frequency domain.
Most of these methods still have problems for denoising results. In this paper, the techniques used
to denoise the heart sound signal are Discrete Wavelet Transform (DWT), Short Term Fourier
Transform (STFT), and Low-Pass filter.
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References
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[14] Velayudhan, Aswathy, and Soniya Peter. "Noise analysis and different denoising techniques of ECG signal-a survey." IOSR journal of electronics and communication engineering 1.1 (2016): 40-44.
[15] Son, Gui-Young, and Soonil Kwon. "Classification of heart sound signal using multiple features." Applied Sciences 8.12 (2018): 2344.
[2] Srivastava, Madhur, C. Lindsay Anderson, and Jack H. Freed. "A new wavelet denoising method for selecting decomposition levels and noise thresholds." IEEE access 4 (2016): 3862-3877.
[3] Jain, Puneet Kumar, and Anil Kumar Tiwari. "An adaptive thresholding method for the wavelet based denoising of phonocardiogram signal." Biomedical Signal Processing and Control 38 (2017): 388-399.
[4] Ali, Mohammed Nabih, EL-Sayed A. El-Dahshan, and Ashraf H. Yahia. "Denoising of heart sound signals using discrete wavelet transform." Circuits, Systems, and Signal Processing 36.11 (2017): 4482-4497.
[5] Rouis, Mohamed, Abdelkrim Ouafi, and Salim Sbaa. "Optimal level and order detection in wavelet decomposition for PCG signal denoising." Biomedical Engineering/Biomedizinische Technik 64.2 (2019): 163-176.
[6] Chowdhury, Md Tanzil Hoque, Khem Narayan Poudel, and Yating Hu. "Automatic phonocardiography analysis using discrete wavelet transform." Proceedings of the 3rd International Conference on Vision, Image and Signal Processing. 2019.
[7] Chowdhury, Tanzil Hoque, Khem Narayan Poudel, and Yating Hu. "Time-frequency analysis, denoising, compression, segmentation, and classification of pcg signals." IEEE Access 8 (2020): 160882-160890.
[8] Parchami, Mahdi, et al. "Recent developments in speech enhancement in the short-time Fourier transform domain." IEEE Circuits and Systems Magazine 16.3 (2016): 45-77.
[9] Yusoff, Nur Afifah, et al. "Denoising technique for partial discharge signal: A comparison performance between artificial neural network, fast fourier transform and discrete wavelet transform." 2016 IEEE International Conference on Power and Energy (PECon). IEEE, 2016.
[10] Ashwin, J. S., and N. Manoharan. "Audio Denoising Based on Short Time Fourier Transform." Indonesian Journal of Electrical Engineering and Computer Science 9.1 (2018): 89-92.
[11] Pham, Duong-Hung, et al. "Phonocardiogram signal denoising based on nonnegative matrix factorization and adaptive contour representation computation." IEEE Signal Processing Letters 25.10 (2018): 1475-1479.
[12] Bhaskar, P. C., and M. D. Uplane. "High frequency electromyogram noise removal from electrocardiogram using FIR low pass filter based on FPGA." Procedia Technology 25 (2016): 497-504.
[13] Sharma, Bharati, and Jenkin Suji. "Analysis of various window techniques used for denoising ECG signal." 2016 Symposium on Colossal Data Analysis and Networking (CDAN). IEEE, 2016.
[14] Velayudhan, Aswathy, and Soniya Peter. "Noise analysis and different denoising techniques of ECG signal-a survey." IOSR journal of electronics and communication engineering 1.1 (2016): 40-44.
[15] Son, Gui-Young, and Soonil Kwon. "Classification of heart sound signal using multiple features." Applied Sciences 8.12 (2018): 2344.
Published
2022-04-01
How to Cite
Ihza, M. Y. I., Satria Mandala, & Miftah Pramudyo. (2022). Study of Denoising Method to Detect Valvular Heart Disease Using Phonocardiogram (PCG). Indonesia Journal on Computing (Indo-JC), 7(1), 31-38. https://doi.org/10.34818/INDOJC.2022.7.1.610
Section
Computer Science
Copyright (c) 2022 Muhammad Yaumil Ihza Ihza, Satria Mandala, Miftah Pramudyo
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