Search from over 60,000 research works

Advanced Search

On the application of optimal wavelet filter banks for ECG signal classification

[thumbnail of Open Access]
Preview
1742-6596_490_1_012142.pdf - Published Version (793kB) | Preview
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Hadjiloucas, S. orcid id iconORCID: https://orcid.org/0000-0003-2380-6114, Jannah, N., Hwang, F. orcid id iconORCID: https://orcid.org/0000-0002-3243-3869 and Galvão, R. K. H. (2014) On the application of optimal wavelet filter banks for ECG signal classification. Journal of Physics: Conference Series, 490 (1). 012142. ISSN 1742-6588 doi: 10.1088/1742-6596/490/1/012142

Abstract/Summary

This paper discusses ECG signal classification after parametrizing the ECG waveforms in the wavelet domain. Signal decomposition using perfect reconstruction quadrature mirror filter banks can provide a very parsimonious representation of ECG signals. In the current work, the filter parameters are adjusted by a numerical optimization algorithm in order to minimize a cost function associated to the filter cut-off sharpness. The goal consists of achieving a better compromise between frequency selectivity and time resolution at each decomposition level than standard orthogonal filter banks such as those of the Daubechies and Coiflet families. Our aim is to optimally decompose the signals in the wavelet domain so that they can be subsequently used as inputs for training to a neural network classifier.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/38005
Item Type Article
Refereed Yes
Divisions Life Sciences > School of Biological Sciences > Department of Bio-Engineering
Publisher Institute of Physics
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar