Application of the Dual-tree Complex Wavelet Transform in Biomedical Signal Denoising

Issue title: Frontiers in Biomedical Engineering and Biotechnology – Proceedings of the 2nd International Conference on Biomedical Engineering and Biotechnology, 11–13 October 2013, Wuhan, China

Article type: Research Article

Authors: Wang, Fang | Ji, Zhong^;

Affiliations: Biomedical Engineering College of Chongqing University, Chongqing, 400030, China | Key Laboratory of Biorheological Science and Technology of Ministry of Education, Biomedical Engineering College of Chongqing University, Chongqing, 400030, China

Note: [] Zhong Ji. E-mail: jizhong@cqu.edu.cn

Abstract: In biomedical signal processing, Gibbs oscillation and severe frequency aliasing may occur when using the traditional discrete wavelet transform (DWT). Herein, a new denoising algorithm based on the dual-tree complex wavelet transform (DTCWT) is presented. Electrocardiogram (ECG) signals and heart sound signals are denoised based on the DTCWT. The results prove that the DTCWT is efficient. The signal-to-noise ratio (SNR) and the mean square error (MSE) are used to compare the denoising effect. Results of the paired samples t-test show that the new method can remove noise more thoroughly and better retain the boundary and texture of the signal.

Keywords: discrete wavelet transform, dual-tree complex wavelet transform, signal-to-noise ratio, mean square error, paired samples t-test

DOI: 10.3233/BME-130790

Journal: Bio-Medical Materials and Engineering, vol. 24, no. 1, pp. 109-115, 2014