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Proceedings Paper

Detection of the electrocardiogram P-wave using wavelet analysis
Author(s): Kanwaldip S. Anant; Farid U. Dowla; Garry H. Rodrigue
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Paper Abstract

Since wavelet analysis is an effective tool for analyzing transient signals, we studied its feature extraction and representation properties for events in electrocardiogram (EKG) data. Significant features of the EKG include the P-wave, the QRS complex, and the T-wave. For this paper the feature that we chose to focus on was the P-wave. Wavelet analysis was used as a preprocessor for a backpropagation neural network with conjugate gradient learning. The inputs to the neural network were the wavelet transforms of EKGs at a particular scale. The desired output was the location of the P-wave. The results were compared to results obtained without using the wavelet transform as a preprocessor.

Paper Details

Date Published: 15 March 1994
PDF: 6 pages
Proc. SPIE 2242, Wavelet Applications, (15 March 1994); doi: 10.1117/12.170073
Show Author Affiliations
Kanwaldip S. Anant, Univ. of California/Davis and Lawrence Livermore National Lab. (United States)
Farid U. Dowla, Lawrence Livermore National Lab. (United States)
Garry H. Rodrigue, Univ. of California/Davis and Lawrence Livermore National Lab. (United States)


Published in SPIE Proceedings Vol. 2242:
Wavelet Applications
Harold H. Szu, Editor(s)

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