FPGA-Based Decision Support System for ECG Analysis

The high mortality rate associated with cardiac abnormalities highlights the need of accurately detecting heart disorders in early stage so to avoid severe health consequence for patients. Health trackers have become popular form wearable devices. They are aimed perform monitoring outside medical clinics during peoples’ daily lives. Our paper proposes a new diagnostic algorithm and its implementation adopting FPGA-based design. conceived system automatically detects most common arrhythmias is also able evaluate QT-segment lengthening pulmonary embolism risk often caused by myocarditis. Debug simulations been carried out firstly Matlab environment then Quartus IDE Intel. hardware embedded test functional accuracy verification performed DE1_SoC development board Terasic, which equipped Cyclone V 5CSEMA5F31C6 FPGA Properly modified real ECG signals corrupted mixture muscle noise, electrode movement artifacts, baseline wander used as bench. A value 99.20% achieved taking into account 0.02 mV root mean square noise voltage. implemented low-power circuit suitable decision support device.