ECG R-Wave Detection and Its Application in Left Ventricular Assist Device

Abstract

Heart failure is one of the major diseases endangering human life. As a transitional support treatment before heart transplantation, the left ventricular assist device (LVAD) has significantly improved the quality of life and survival rate of patients with end-stage heart failure. In the automatic detection of electrocardiogram (ECG), the detection of QRS wave groups is the most critical aspect, which affects the correctness and accuracy of subsequent data analysis and processing. The paper used the data from the MIT-BIH database and the data collected from human ECG as the original number of samples for further processing. It processed the data through a high-order finite impulse response (FIR) low-pass filter and Shannon energy algorithm, and added the use of a high-order adaptive median filter algorithm on a field programmable gate array (FPGA) to minimize the noise of the processed real-time data. Finally, the tested ECG R-wave was used to drive the LVAD. After successful simulation by MATLAB and Modelsim software, the scheme of the real-time ECG signal controlling blood pump system was realized on the FPGA platform. The experiment showed that the method proposed could accurately extract the R-wave and control the LVAD to pump blood simultaneously.