The use of the Hilbert transform in ECG signal analysis

This paper presents a new robust algorithm for QRS detection using the firs t differential of the ECG signal and its Hilbert transformed data to locate the R wave peaks in the ECG waveform. Using this method, the differentiati on of R waves from large, peaked T and P waves is achieved with a high degr ee of accuracy. In addition, problems with baseline drift, motion artifacts and muscular noise are minimised. The performance of the algorithm was tes ted using standard ECG waveform records from the MIT-BITH Arrhythmia databa se, An average detection rate of 99.87%, a sensitivity (Se) of 99.94% and a positive prediction (+P) of 99.93% have been achieved against study record s from the MIT-BITH Arrhythmia database. A detection error rate of less tha n 0.8% was achieved in every study case. The reliability of the proposed de tector compares very favorably with published results for other QRS detecto rs. (C) 2001 Elsevier Science Ltd. All rights reserved.