Proceedings ArticleDOI
An adaptive method for shrinking of wavelet coefficients for phonocardiogram denoising
Puneet Kumar Jain,Anil Kumar Tiwari +1 more
- pp 1-5
TLDR
An adaptive method is proposed to estimate the threshold value for the shrinking of the wavelet coefficients of the PCG signal and the results are compared with the results of state-of-the-art methods and show the superiority of the proposed method.Abstract:
Noise suppression from the phonocardiogram (PCG) signal is important to improve the diagnostic efficiency. For the PCG signal, Discrete Wavelet Transform (DWT) based denoising method has been used extensively due to its good performance. However, the performance of this method depends on the threshold value and the way to apply it on the wavelet coefficients. Therefore, in this paper, an adaptive method is proposed to estimate the threshold value for the shrinking of the wavelet coefficients of the PCG signal. For this purpose, a new statistical parameter is obtained by incorporating medical domain knowledge about the PCG. The threshold value is estimated based on the statistical analysis of the wavelet coefficients and the present level of noise. Further, to overcome the issues related to existing threshold functions, soft and hard, new threshold functions, mid and non-linear mid are presented. The proposed method is applied to the PCG signal contaminated with simulated white Gaussian noise, red noise, and pink noise. The obtained results of the proposed method are compared with the results of state-of-the-art methods and they show the superiority of the proposed method.read more
Citations
More filters
Journal ArticleDOI
Localization and classification of heart beats in phonocardiography signals —a comprehensive review
TL;DR: A comprehensive survey of different methods proposed for automatic analysis of PCG signals in time, frequency, and time-frequency domains is presented to evaluate the current state of the art and to determine the potential domains of effective analysis.
Journal ArticleDOI
Localization and classification of heartbeats using robust adaptive algorithm
TL;DR: The proposed technique is evaluated on publicly available Pascal Heart Sound Challenge dataset and reports smaller average error for localization and has high sensitivity and accuracy for heart beat classification.
Proceedings ArticleDOI
Research on Underwater Image Denoising Based on Wavelet Threshold Method
TL;DR: Wang et al. as discussed by the authors proposed an improved wavelet denoising method, which can not only effectively filter the noise signal, but also retain the edge information of the image to the maximum extent, making the denoised image more conducive to subsequent stereo matching and target positioning.
Journal ArticleDOI
Fiber-Optic Interferometry-Based Heart Rate Monitoring
TL;DR: In this article , the determination of a patient's heart rate (HR) as a basic parameter determining his or her state of health was performed using the wavelet transform (WT).
References
More filters
Journal ArticleDOI
A theory for multiresolution signal decomposition: the wavelet representation
TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
Journal ArticleDOI
Optimal wavelet denoising for phonocardiograms
TL;DR: Which wavelet families, levels of decomposition, and thresholding techniques best remove the noise in a PCG are addressed and possible applications of the Hilbert transform to heart sound analysis are discussed.
Journal ArticleDOI
The electronic stethoscope
Shuang Leng,Ru San Tan,Ru San Tan,Kevin T. C. Chai,Chao Wang,Dhanjoo N. Ghista,Liang Zhong,Liang Zhong +7 more
TL;DR: The paper provides the technological and medical basis for the development and commercialization of a real-time integrated heart sound detection, acquisition and quantification system.
Journal ArticleDOI
Heart sound analysis for symptom detection and computer-aided diagnosis
TL;DR: A simple model for the production of heart sounds is developed, and its utility in identifying features useful in diagnosis is demonstrated, and a prototype system intended to aid in heart sound analysis is presented.