TY - GEN
T1 - New adaptive thresholding-based ECG R-peak detection technique
AU - Khriji, Lazhar
AU - Al-Busaidi, Asiya M.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/3
Y1 - 2018/7/3
N2 - The QRS complexes (R-peaks) in the electrocardiogram (ECG) signals are essential features as they provide information for the diagnosis of heart diseases. Because detection accuracy is a major concern in clinical practices, most of the detection methods are complex and computationally expensive. However, in ubiquitous healthcare (u-healthcare), the energy consumption is a question; thus, detection time has to be minimized. In this paper, we propose a new intelligent detection algorithm, which minimizes detection time while maintaining a good level of detection performance. Experimental results, in detecting the R-peaks in 30 minutes long records, showed that the proposed algorithm has achieved an Se (sensitivity) of 99.63% and a +P (positive predictivity) of 99.50% outperforming the well-known algorithms from literature.
AB - The QRS complexes (R-peaks) in the electrocardiogram (ECG) signals are essential features as they provide information for the diagnosis of heart diseases. Because detection accuracy is a major concern in clinical practices, most of the detection methods are complex and computationally expensive. However, in ubiquitous healthcare (u-healthcare), the energy consumption is a question; thus, detection time has to be minimized. In this paper, we propose a new intelligent detection algorithm, which minimizes detection time while maintaining a good level of detection performance. Experimental results, in detecting the R-peaks in 30 minutes long records, showed that the proposed algorithm has achieved an Se (sensitivity) of 99.63% and a +P (positive predictivity) of 99.50% outperforming the well-known algorithms from literature.
KW - ECG
KW - QRS complex
KW - R-peak
KW - u-healthcare
UR - http://www.scopus.com/inward/record.url?scp=85050024498&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050024498&partnerID=8YFLogxK
U2 - 10.1109/MECBME.2018.8402423
DO - 10.1109/MECBME.2018.8402423
M3 - Conference contribution
AN - SCOPUS:85050024498
T3 - Middle East Conference on Biomedical Engineering, MECBME
SP - 147
EP - 152
BT - 4th IEEE Middle East Conference on Biomedical Engineering, MECBME 2018
PB - IEEE Computer Society
T2 - 4th IEEE Middle East Conference on Biomedical Engineering, MECBME 2018
Y2 - 28 March 2018 through 30 March 2018
ER -