An FPGA system using fuzzy clustering and correlation to diagnose angina

In this paper, we present a signal processing method capable of detecting angina in electrocardiograms, that was implemented in FPGA. The adopted procedure is based on fuzzy clustering to reduce the amount of data sampling and correlation to compare with samples from a previously established database. By using the correlation method on the samples, it is possible to establish an initial indication of angina. The reduced number of samples of the clustering process turns the processing simpler and allows its hardware implementation in FPGA to validate it. According to the tests conducted, the method achieves 85% correct diagnoses.