Enhanced wavelet transformation for feature extraction in highly variated ECG signal

C. L.P. Lim, W. L. Woo, S. S. Dlay

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Citations (Scopus)

Abstract

This paper proposes an adaptive signal extraction method that uses Discrete Wavelet Transformation coupled with adaptive parameters to address variated heartwave signal due to varying heartrates. The characteristic features of the heartwave signal comprises of the P-wave, QRS-complex, Twave, onset and offset of P-wave and T-wave. Using statistically deduced parameters, the PR and QT interval parameters were incorporated where the signal extraction method can be made adaptive to varying heartrate that resulted in a very reliable signal extraction methods. Work was tested on the public database where individuals underwent treadmill testing and 95% of the heartwave signal characteristics were successfully extracted.

Original languageEnglish
Title of host publication2nd IET International Conference on Intelligent Signal Processing 2015 (ISP)
PublisherIEEE
ISBN (Electronic)978-1-78561-137-7
ISBN (Print)978-1-78561-136-0
DOIs
Publication statusPublished - 17 Nov 2016
Externally publishedYes
Event2nd IET International Conference on Intelligent Signal Processing 2015, ISP 2015 - London, United Kingdom
Duration: 1 Dec 20152 Dec 2015

Conference

Conference2nd IET International Conference on Intelligent Signal Processing 2015, ISP 2015
CountryUnited Kingdom
CityLondon
Period1/12/152/12/15

Fingerprint Dive into the research topics of 'Enhanced wavelet transformation for feature extraction in highly variated ECG signal'. Together they form a unique fingerprint.

Cite this