Author(s)

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

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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.

Cardiopathy, Heart, Correlation, Fuzzy Clustering, Electrocardiogram

E. Cintra, T. Pimenta and R. Moreno, "The Use of Fuzzy Clustering and Correlation to Implement an Heart Disease Diagnosing System in FPGA," Journal of Software Engineering and Applications, Vol. 4 No. 8, 2011, pp. 491-496. doi: 10.4236/jsea.2011.48057.