Detection of abnormality in the electrocardiogram without prior knowledge by using the quantisation error of a self-organising map, tested on the European ischaemia database-Reference-Cited by-同舟云学术

Detection of abnormality in the electrocardiogram without prior knowledge by using the quantisation error of a self-organising map, tested on the European ischaemia database

Published:2001-05 Issue:3 Volume:39 Page:330-337
ISSN:0140-0118
Container-title:Medical & Biological Engineering & Computing
language:en
Short-container-title:Med. Biol. Eng. Comput.

Author:

Fernández E. A.,Willshaw P.,Perazzo C. A.,Presedo R. J.,Barro S.

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Biomedical Engineering

Link

http://link.springer.com/content/pdf/10.1007/BF02345288.pdf

Reference27 articles.

1. Andrew, J., Hopkirk, J., Leader, S., Uhl, G. S., Hickman, J. R., andFischer, J. (1984): ‘Limitation of exercise-induced R wave amplitude changes in detecting coronary artery disease in asymptomatic men’,J. Amer. College Cardiol.,3, pp. 821–826

2. Bezerianos, A., Vladutu, L., andPapadimitriou, S. (2000): ‘Hierarchical state space partitioning with a network self-organizing map for recognition of ST-T segment changes’,Med. Biol. Eng. Comput.,38, pp. 406–415

3. Bonoris, P. E., Greenberg, P. S., Christison, G. W., Castellanet, M. J., andEllestad, M. H. (1978): ‘Evaluation of R wave amplitude changes versus ST-segment depression in stress testing’,Circulation,57, pp. 904–910

4. David, D., Naito, M., Michelson, E., Watanbe, Y., Chen, C. C., Morganroth, J., andShaffenburg, M. (1982): ‘Intramiocardial conduction: a major determinant of R-wave amplitude during acute myocardial ischaemia’,Circulation,65, pp. 161–167

5. Lecture Notes in Artificial Intelligence;E. A. Fernández,1999

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Parameters estimate of recurrent quantum stochastic filter for time variant frequency periodic signals;Journal of Central South University;2019-12

2. Movement Deviation Profile: A measure of distance from normality using a self-organizing neural network;Human Movement Science;2012-04

3. Auto-Regressive Processes Explained by Self-Organized Maps. Application to the Detection of Abnormal Behavior in Industrial Processes;IEEE Transactions on Neural Networks;2011-12

4. Gait quality assessment using self-organising artificial neural networks;Gait & Posture;2007-03