Abstract
We propose a method to extract the QRS wave in an electrocardiogram (ECG). It is extracted by detecting two characteristic points (CPs), the Q and S points. There are two main problems that make detection of CPs difficult: 1) noise contaminating the ECG and 2) individual variation of waves and complexes in the ECG. We use DP matching for overcoming the problem of noise contamination and a neural network of ART2 for overcoming the problem of individual pattern variation. These two methods are fused using a multichannel ART-based neural network (MART) for reliable detection of CPs. The method was evaluated using an MIT/BIH arrhythmia database. It was found that the rates of accuracy within 6 ms error were 99.6% for S point detection and 96.4% for Q point detection, indicating that the present method has good potential for detection of CPs on an ECG.
