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O. T. Inan, L. Giovangrandi and K. T. A. Gregory, “Robust Neural-Network-Based Classification of Premature Ventricular Contractions Using Wavelet Transform and Timing Interval Features,” IEEE Transactions on Biomedical Engineering, Vol. 53, No. 12, December 2006, pp. 2507-2515.

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• 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.