By Topic

Wavelet match filtering and neural network based QRS detection

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
$31 $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

1 Author(s)
Hendija, D. ; Fakultet Elektrotehnike i Racunarstva, Zagreb, Croatia

This paper presents combination of wavelet match filtering and neural network approach in QRS detection. In development, a particular emphasis is put on low signal-to-noise ratio and low computational complexity. Morlet wavelet is used for artifact removal and MLP is then used for QRS classification. Testing on MIT/BIH arrhythmia database, with added artifacts, shows above 90% accuracy in QRS detection in worst case scenario.

Published in:

MIPRO, 2011 Proceedings of the 34th International Convention

Date of Conference:

23-27 May 2011