By Topic

Electrocardiogram characterization using wavelet analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
K. Mokrani ; Electron. Dpt, Univ. of Bejaia, Algeria ; A. Alliche

The electrocardiograph (ECG) is a graphical representation of the forces generated during cardiac activity, and is an essential tool for the diagnosis of cardiac abnormalities. An automatic ECG analyzer will provide a cardiologist with a tool allowing faster and more accurate diagnosis. The analysis consists of the measurement of the amplitudes, durations and morphologies of the P, QRS and T waves. This paper deals with the measure of QRS duration, R spikes detection (arrhythmia), and the starting and vanishing time of the T wave. A comparison of different methods based on the derivatives and filtering for the extraction of ECG characteristics is presented. We show that wavelet analysis gives better results than classical methods, and enables a finer characterization of the parameters

Published in:

Electronics, Circuits and Systems, 2001. ICECS 2001. The 8th IEEE International Conference on  (Volume:3 )

Date of Conference: