Performance Analysis of Fetal-Phonocardiogram Signal Denoising Using The Discrete Wavelet Transform

Fuadina, Ipam; Hendry, Jans; Zulherman, Dodi

doi:10.20895/infotel.v11i4.458

Cited by 4 publications

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“…Sinyal fPCG hasil perekaman mengandung banyak derau yang dihasilkan oleh aktivitas ibu hamil dan fetus, sehingga dapat menyebabkan perbedaan tegangan yang cukup besar pada setiap hasil pencuplikan. Hal ini mengakibatkan peningkatan variabilitas sinyal yang menuntut untuk diperkecil agar fluktuasi pada tiap hasil pencuplikan tidak terlalu besar [12]. Normalisasi sinyal sederhana dilakukan dengan membatasi tegangan sinyal pada rentang -1 V hingga +1 V dengan menggunakan (2).…”

Section: ) Normalisasiunclassified

“…Sebuah penelitian memberikan pendapat lain terkait derau akibat aktivitas organ ibu, yaitu berada di bawah 25 Hz [18]. Di dalam penelitian ini, frekuensi -3 dB yang digunakan adalah 30 Hz-80 Hz, dengan menggunakan BPF IIR orde 10, sehingga dihasilkan hasil penapisan dengan zero phase shift [12]. Komponen bias (offset) akan hilang secara otomatis karena penggunaan penapisan tipe ini, sehingga baseline sinyal berada pada daerah asal sumbu horizontal.…”

Section: ) Normalisasiunclassified

“…Persamaan diferensial BPF IIR secara matematis diekspresikan pada (3). [12], beberapa keluarga wavelet telah diuji coba untuk mendapatkan tipe wavelet terbaik dalam ukuran SNR untuk analisis sinyal fPCG, khususnya menggunakan data simfpcgdb. Penelitian tersebut menyimpulkan bahwa coiflet dengan vanishing moment 1 adalah yang terbaik, sehingga (7) dapat ditulis ulang menjadi (8).…”

Section: ) Normalisasiunclassified

“…sehingga koefisien skala dan wavelet hasil transformasinya memiliki bentuk pada (11) dan (12). 2) Denoising: Koefisien detail mengalami proses denoising, baik dalam DTCWT ataupun DWT, tetapi terdapat sedikit perbedaan pada penerapan thresholding nilai antara DWT dan DTCWT.…”

Section: ) Lack Of Directionalityunclassified

“…Pengamatan unjuk kerja sistem dilakukan dengan membandingkan nilai SNR hasil denoising metode DTCWT terhadap nilai SNR hasil denoising metode DWT. Hasil denoising metode DWT sebelumnya telah dilakukan dengan menguji tipe mother wavelet, level dekomposisi, dan jenis teknik pengambangan (thresholding) [12]. [11].…”

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Perbandingan Real-Valued dan Complex Wavelet Transform pada Denoising Sinyal Fetal-Phonocardiograms (Comparison of Fetal-Phonocardiogram Signal Denoising based on Real- Valued and Complex Wavelet Transform)

Zulherman

Hendry

Adam

2020

JNTETI

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Monitoring of Fetal Heart Rate (FHR) in the pregnancy period commonly uses the Doppler-based instruments despite having several disadvantages, such as high-cost and complexity of the monitoring system. Implementation of the passive and non-invasive method based on fetal phonocardiogram (fPCG), the acoustic recording of fetus cardiac signal, can be used as a potentially economical long-term monitoring device for diagnosis. Because the interference signal from the maternal women exists, the matured denoising technique was needed to implement the fPCG method to diagnose the fetus' well-being condition. The denoising system based on Dual-tree Complex Wavelet Transforms (DTCWT) was proposed in this paper. The proposed method was evaluated using Signal to Noise Ratio (SNR). Based on the experiment result from 37 fPCG signals from physio.net, the DTCWT system performance was compared with the Discrete Wavelet Transform (DWT). There were 24 CWT’s denoised fPCG signals that have successfully outperformed DWT’s SNR. DTCWT has also reduced the noises in the range of 30 Hz–80 Hz. Also, it emphasized the existence of dominant frequencies in the range of 60 Hz–65 Hz.

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Section: ) Normalisasiunclassified

Section: ) Lack Of Directionalityunclassified

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Perbandingan Real-Valued dan Complex Wavelet Transform pada Denoising Sinyal Fetal-Phonocardiograms (Comparison of Fetal-Phonocardiogram Signal Denoising based on Real- Valued and Complex Wavelet Transform)

Zulherman

Hendry

Adam

2020

JNTETI

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A Review of Recent Advances and Future Developments in Fetal Phonocardiography

Kahánková

Mikolasova

Jaroš

et al. 2023

IEEE Rev. Biomed. Eng.

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Fetal phonocardiography (fPCG) is receiving attention as it is a promising method for continuous fetal monitoring due to its non-invasive and passive nature. However, it suffers from the interference from various sources, overlapping the desired signal in the time and frequency domains. This paper introduces the state-of-the-art methods used for fPCG signal extraction and processing, as well as means of detection and classification of various features defining fetal health state. It also provides an extensive summary of remaining challenges, along with the practical insights and suggestions for the future research directions.

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Fetal phonocardiogram signals denoising using improved complete ensemble (EMD) with adaptive noise and optimal thresholding of wavelet coefficients

Cheikh

Benhassine

Sbaa

2022

Biomedical Engineering / Biomedizinische Technik

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Although fetal phonocardiogram (fPCG) signals have become a good indicator for discovered heart disease, they may be contaminated by various noises that reduce the signals quality and the final diagnosis decision. Moreover, the noise may cause the risk of the data to misunderstand the heart signal and to misinterpret it. The main objective of this paper is to effectively remove noise from the fPCG signal to make it clinically feasible. So, we proposed a novel noise reduction method based on Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), wavelet threshold and Crow Search Algorithm (CSA). This noise reduction method, named ICEEMDAN-DWT-CSA, has three major advantages. They were, (i) A better suppress of mode mixing and a minimized number of IMFs, (ii) A choice of wavelet corresponding to the study signal proven by the literature and (iii) Selection of the optimal threshold value. Firstly, the noisy fPCG signal is decomposed into Intrinsic Mode Functions (IMFs) by the (ICEEMDAN). Each noisy IMFs were decomposed by the Discrete Wavelet Transform (DWT). Then, the optimal threshold value using the (CSA) technique is selected and the thresholding function is carried out in the detail’s coefficients. Secondly, each denoised (IMFs) is reconstructed by applying the Inverse Discrete Wavelet Transform (IDWT). Finally, all these denoised (IMFs) are combined to get the denoised fPCG signal. The performance of the proposed method has been evaluated by Signal to Noise Ratio (SNR), Mean Square Error (MSE) and the Correlation Coefficient (COR). The experiment gave a better result than some standard methods.

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Performance Analysis of Fetal-Phonocardiogram Signal Denoising Using The Discrete Wavelet Transform

Cited by 4 publications

References 0 publications

Perbandingan Real-Valued dan Complex Wavelet Transform pada Denoising Sinyal Fetal-Phonocardiograms (Comparison of Fetal-Phonocardiogram Signal Denoising based on Real- Valued and Complex Wavelet Transform)

Perbandingan Real-Valued dan Complex Wavelet Transform pada Denoising Sinyal Fetal-Phonocardiograms (Comparison of Fetal-Phonocardiogram Signal Denoising based on Real- Valued and Complex Wavelet Transform)

A Review of Recent Advances and Future Developments in Fetal Phonocardiography

Fetal phonocardiogram signals denoising using improved complete ensemble (EMD) with adaptive noise and optimal thresholding of wavelet coefficients

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