<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>QRS represented the most important part of ECG signal, so different researches and studies are performed for QRS recognition. In this paper, a new technique by using wavelet transform is used for de-noising ECG signal by using adaptive threshold, then DWT used to separate the high frequency from the low component, then compute the statistical information from low frequencies to be used in threshold computation, Based on these statics features, lower and upper threshold are calculated, which are updated according to number of peaks that are detected until two thresholds give same number of peaks, also the detected peaks are updated according to average R–R time. Results of (EDB) database was (Acc = 99.366%), while (LTSTDB) database was (Acc = 98.89%). The results are compared with other work and it is show that the proposed method gave better performance and can be used for QRS detection.</p>
</abstract>

QRS represented the most important part of ECG signal, so different researches and studies are performed for QRS recognition. In this paper, a new technique by using wavelet transform is used for de-noising ECG signal by using adaptive threshold, then DWT used to separate the high frequency from the low component, then compute the statistical information from low frequencies to be used in threshold computation, Based on these statics features, lower and upper threshold are calculated, which are updated according to number of peaks that are detected until two thresholds give same number of peaks, also the detected peaks are updated according to average R–R time. Results of (EDB) database was (Acc = 99.366%), while (LTSTDB) database was (Acc = 98.89%). The results are compared with other work and it is show that the proposed method gave better performance and can be used for QRS detection.

QRS complex detection and R–R interval computation based on discrete wavelet transform

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

running-head

QRS represented the most important part of ECG signal, so different researches and studies are performed for QRS recognition. In this paper, a new technique by...

QRS complex detection and R–R interval computation based on discrete wavelet transform

Article Category: Research-Article

Publicado en línea: 03 jul 2020

Páginas: 1 - 11

Recibido: 15 abr 2020

DOI: https://doi.org/10.21307/ijssis-2020-010

Palabras clave
DWT, RR, HR, QRS, LTSTDB, EDB

© 2020 Aqeel M. Hamad Alhussainy published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

QRS complex detection and R–R interval computation based on discrete wavelet transform

Article Category: Research-Article

Publicado en línea: 03 jul 2020

Páginas: 1 - 11

Recibido: 15 abr 2020

DOI: https://doi.org/10.21307/ijssis-2020-010

Palabras claveDWT, RR, HR, QRS, LTSTDB, EDB

© 2020 Aqeel M. Hamad Alhussainy published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Palabras clave
DWT, RR, HR, QRS, LTSTDB, EDB