Real-time detection of electrocardiogram wave features using template matching and implementation in FPGA

Electrocardiogram (ECG) can provide valuable clinical information on cardiac functions. This paper illustrates an algorithm for real–time detection of wave peaks and their features from single lead ECG data. At first, the ECG data was filtered for power line interference and high frequency noise. Then, a set of slope and polarity–based rule bases were generated from the first 6000 samples, which define templates of R–peak, P–and T–wave detection from the following beats. The algorithm was implemented on Xilinx Spartan III Field Programmable Gate Array (FPGA). For testing of the algorithm, ECG data was quantised at 8–bit resolution and delivered to the FPGA using synchronous transfer mechanism using parallel port of computer. Xilinx implementation results provided 97.58%, 98.4% and 97.78% detection sensitivity for P–, R– and T–waves, respectively. Different wave features (height, polarity and duration) were detected with an average error rate of 9.3%. The detected wave signatures were clinically validated by medical expert.