ECG Denoising by Modeling Wavelet Sub-Band Coefficients using Kernel Density Estimation


Shubhada Ardhapurkar, Ramch, ra Manthalkar, Suhas Gajre, Journal of Information Processing Systems Vol. 8, No. 4, pp. 669-684, Dec. 2012  

10.3745/JIPS.2012.8.4.669
Keywords: Kernel Density Estimation, Discrete Wavelet Transform, Probability Density Function (PDF), Signal to Noise Ratio
Fulltext:

Abstract

Discrete wavelet transforms are extensively preferred in biomedical signal processing for denoising, feature extraction, and compression. This paper presents a new denoising method based on the modeling of discrete wavelet coefficients of ECG in selected sub-bands with Kernel density estimation. The modeling provides a statistical distribution of information and noise. A Gaussian kernel with bounded support is used for modeling sub-band coefficients and thresholds and is estimated by placing a sliding window on a normalized cumulative density function. We evaluated this approach on offline noisy ECG records from the Cardiovascular Research Centre of the University of Glasgow and on records from the MIT-BIH Arrythmia database. Results show that our proposed technique has a more reliable physical basis and provides improvement in the Signal-to-Noise Ratio (SNR) and Percentage RMS Difference (PRD). The morphological information of ECG signals is found to be unaffected after employing denoising. This is quantified by calculating the mean square error between the feature vectors of original and denoised signal. MSE values are less than 0.05 for most of the cases.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from November 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.




Cite this article
[APA Style]
Ardhapurkar, S., , Manthalkar, r., & Gajre, S. (2012). ECG Denoising by Modeling Wavelet Sub-Band Coefficients using Kernel Density Estimation. Journal of Information Processing Systems, 8(4), 669-684. DOI: 10.3745/JIPS.2012.8.4.669.

[IEEE Style]
S. Ardhapurkar, Ramch, r. Manthalkar, S. Gajre, "ECG Denoising by Modeling Wavelet Sub-Band Coefficients using Kernel Density Estimation," Journal of Information Processing Systems, vol. 8, no. 4, pp. 669-684, 2012. DOI: 10.3745/JIPS.2012.8.4.669.

[ACM Style]
Shubhada Ardhapurkar, Ramch, ra Manthalkar, and Suhas Gajre. 2012. ECG Denoising by Modeling Wavelet Sub-Band Coefficients using Kernel Density Estimation. Journal of Information Processing Systems, 8, 4, (2012), 669-684. DOI: 10.3745/JIPS.2012.8.4.669.