DocumentCode :
2673107
Title :
Comparison Between Neural-Network-Based Adaptive Filtering and Wavelet Transform for ECG Characteristic Points Detection
Author :
Ng, F. ; Mora, F. ; Wong, S. ; Passariello, G. ; Almeida, D.
Author_Institution :
Technical University of Budapest, Hungary
Volume :
1
fYear :
1997
fDate :
Oct. 30 1997-Nov. 2 1997
Firstpage :
272
Lastpage :
274
Abstract :
As a physiologic response during exercise, due to tachycardia effects and liberated catecholamines, reduction of left ventricle volume is produced. Based on the Brody effect, R wave amplitude lessening during the stress test is reflected in the electrocardiographic signal. In spite of the previous statements, many researches during the last decades have been unable to find any ability of this parameter to assess Coronary Artery Disease (CAD) patients. The proposed methodology considering trend series analysis allows one to approach several electrocardiographic parameters, hemodynamic responses and symptoms, allowing the correlation among them and to evaluate the behaviour of each parameter. In a sample of 17 CAD patients and 14 healthy subjects assessed by either clustering analysis or McNemar test has shown adequate ability in group discrimination
Keywords :
blood vessels; diseases; electrocardiography; medical signal processingcoronary artery disease; Brody effect; McNemar test; clustering analysis; electrocardiographic parameters; group discrimination; healthy subjects; hemodynamic responses; left ventricle volume reduction; stress test; symptoms; trend series analysis; Blood flow; Conductivity; Coronary arteriosclerosis; Heart rate; Hemodynamics; Hospitals; Ischemic pain; Myocardium; Stress; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 1997. Proceedings of the 19th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL, USA
ISSN :
1094-687X
Print_ISBN :
0-7803-4262-3
Type :
conf
DOI :
10.1109/IEMBS.1997.754522
Filename :
754522
Link To Document :
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