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

DOI: 10.4236/jsea.2011.48057   PDF   HTML     4,901 Downloads   8,605 Views   Citations


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.

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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.

Conflicts of Interest

The authors declare no conflicts of interest.


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