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Sparsity enhancing wavelets design for ECG and fetal ECG compression

Publication Type : Journal Article

Publisher : Elsevier

Source : Biomedical Signal Processing and Control

Url : https://www.sciencedirect.com/science/article/abs/pii/S1746809421006790

Campus : Coimbatore

School : School of Artificial Intelligence

Center : Center for Computational Engineering and Networking

Year : 2022

Abstract : This paper details the design of a set of wavelet filters that are bi orthogonal in nature. The designed wavelets are experimented in publicly available MIT data base. In Compressed Sensing (CS) paradigm reconstruction quality can be improved by improving the sparsity. From experiments it was found that ECG records especially fetal ECGs have a better sparse representation in the newly designed domain as compared to commonly used wavelets. This paper also details the fundamentals of CS in a much easier way and briefly reviews some state of art methods in CS based on ECG reconstruction scenarios. The best state of art method in terms of reconstruction quality is selected for testing the designed wavelets. The designed wavelet is named as ‘dew2’.The design details of this bi orthogonal wavelet system are detailed in different sections with the help of standard wavelet system design rules.

Cite this Research Publication : Abhishek, S., and Shanmugham Veni. "Sparsity enhancing wavelets design for ECG and fetal ECG compression." Biomedical Signal Processing and Control 71 (2022): 103082.

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