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A. Armato, E. Nardini, A. Lanatà, G. Valenza, C. Mancuso, E. P. Scilingo and D. De Rossi, “An FPGA Based Arrhythmia Recognition System for Wearable Applications,” Ninth International Conference on Intelligent Systems Design and Applications, Pisa, 30 November - 2 December 2009. doi:10.1109/ISDA.2009.246

has been cited by the following article:

• TITLE: The Use of Fuzzy Clustering and Correlation to Implement an Heart Disease Diagnosing System in FPGA

  AUTHORS: Evaldo Renó Faria Cintra, Tales Cleber Pimenta, Robson Luiz Moreno

  KEYWORDS: Cardiopathy, Heart, Correlation, Fuzzy Clustering, Electrocardiogram

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.4 No.8, August 2, 2011

  ABSTRACT: In this paper we present a signal processing method capable of detecting cardiopathies in electrocardiograms that was implemented in FPGA. The adopted procedure is based on fuzzy clustering to reduce the amount of data sampling, and a comparison with samples from a previously established database. By using the correlation method on the samples, it is possible to establish an initial indication of a cardiopathy. The reduced number of samples of the clustering process turns the processing simpler and allows its hardware implementation. According to the tests conducted, the method achieves 91% correct diagnoses.