VCG and ECG indexes for classification of patients with Myocardial Infarction-Reference-Cited by-同舟云学术

VCG and ECG indexes for classification of patients with Myocardial Infarction

Published:2017 Issue: Volume: Page:496-499
ISSN:1680-0737
Container-title:VII Latin American Congress on Biomedical Engineering CLAIB 2016, Bucaramanga, Santander, Colombia, October 26th -28th, 2016
language:
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Author:

Correa R.,Arini P. D.,Correa L. S.,Laciar E.

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-10-4086-3_125

Reference15 articles.

1. K. Thygesen, J. S. Alpert, A. S. Jaffe and others “Third Universal Definition of Myocardial Infarction,” Journal of the American College of Cardiology, vol. 60, no. 16, pp. 1581–1598, 2012.

2. M. Arif, I. A. Malagore, and F. A. Afsar, “Detection and localization of myocardial infarction using K-nearest neighbor classifier,” Journal of medical systems, vol. 36, no. 1, pp. 279–289, 2012.

3. G. Bakul and U. Tiwary, “Automated risk identification of myocardial infarction using relative frequency band coefficient (RFBC) features from ECG,” The open biomedical engineering journal, vol. 4, p. 217, 2010.

4. A. Keshtkar, H. Seyedarabi, P. Sheikhzadeh, and others, “discriminant analysis between myocardial infarction patients and healthy subjects using Wavelet Transformed signal averaged electrocardiogram and probabilistic neural network,” Journal of Medical Signals and Sensors, vol. 3, no. 4, 2013.

5. N. Safdarian, N. J. Dabanloo, and G. Attarodi, “A New Pattern Recognition Method for Detection and Localization of Myocardial Infarction Using T-Wave Integral and Total Integral as Extracted Features from One Cycle of ECG Signal,” Journal of Biomedical Science and Engineering, vol. 2014, 2014.