The use of the Hilbert transform in ECG signal analysis

D. Benitez, P. A. Gaydecki, A. Zaidi, A. P. Fitzpatrick

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

410 Citas (Scopus)

Resumen

This paper presents a new robust algorithm for QRS detection using the first differential of the ECG signal and its Hilbert transformed data to locate the R wave peaks in the ECG waveform. Using this method, the differentiation of R waves from large, peaked T and P waves is achieved with a high degree of accuracy. In addition, problems with baseline drift, motion artifacts and muscular noise are minimised. The performance of the algorithm was tested using standard ECG waveform records from the MIT-BITH Arrhythmia database. 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 records from the MIT-BITH Arrhythmia database. A detection error rate of less than 0.8% was achieved in every study case. The reliability of the proposed detector compares very favorably with published results for other QRS detectors.

Idioma originalInglés
Páginas (desde-hasta)399-406
Número de páginas8
PublicaciónComputers in Biology and Medicine
Volumen31
N.º5
DOI
EstadoPublicada - 2001
Publicado de forma externa

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