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

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

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DOI: 10.4236/jsea.2011.48057                

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.

Keywords

Cardiopathy, Heart, Correlation, Fuzzy Clustering, Electrocardiogram

Conflicts of Interest

The authors declare no conflicts of interest.

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