Efficient QRS Complex Detection Algorithm Implementation on Soc-Based Embedded System

Abstract

This paper studies two different Electrocardiography (ECG) preprocessing algorithms, namely Pan and Tompkins (PT) and Derivative Based (DB) algorithm, which is crucial of QRS complex detection in cardiovascular disease detection. Both algorithms are compared in terms of QRS detection accuracy and computation timing performance, with implementation on System-on-Chip (SoC) based embedded system that prototype on Altera DE2-115 Field Programmable Gate Array (FPGA) platform as embedded software. Both algorithms are tested with 30 minutes ECG data from each of 48 different patient records obtain from MIT-BIH arrhythmia database. Results show that PT algorithm achieve 98.15% accuracy with 56.33 seconds computation while DB algorithm achieve 96.74% with only 22.14 seconds processing time. Based on the study, an optimized PT algorithm with improvement on Moving Windows Integrator (MWI) has been proposed to accelerate its computation. Result shows that the proposed optimized Moving Windows Integrator algorithm achieves 9.5 times speed up than original MWI while retaining its QRS detection accuracy.

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“…[1] spends 1.92 seconds, Hashim et al [9] spends 2.97 seconds, Xiang et al [26] spends 14.53 seconds, and Karimipour et al [11] spends 18.18seconds to process 30 minutes ECG record, respectively. Also, the algorithm of Kholkhal et al [12] requires 1476 seconds to detect 15027 beats, which means that it needs 223.26 seconds to process 2273 beats.…”