FPGA-based System for ECG Beat Detection and Classification

Abstract

We present a Field Programmable Gate Arraybased system for single-lead electrocardiogram signal processing which performs beat detection and classification to normal and ventricular beats. Geometrical properties of a phase-space portrait of an ECG signal are used for QRS complex detection, while classification is done with a modified classification algorithm that is a part of the Open Source ECG Analysis Software. The chosen Field Programmable Gate Array has an embedded PowerPC processor and is very suitable for mixed hardware and software designs. Beat detection is implemented in hardware and the classification is executed on the embedded PowerPC 405 core. The algorithm was developed on the MITBIH Arrhythmia Database resampled to 250 samples per second. Sensitivity of 99.80% and positive predictivity of 99.84% was achieved for QRS complex detection and sensitivity of 92.59% and positive predictivity of 95.55% was achieved for identification of premature ventricular complexes. A comparison of processing speed between a personal computer and the embedded system shows that a personal computer running at 18-times faster clock speed processes data only six times faster.