TY - GEN
T1 - Adaptive technique for P and T wave delineation in electrocardiogram signals
AU - Bayasi, Nourhan
AU - Tekeste, Temesghen
AU - Saleh, Hani
AU - Khandoker, Ahsan
AU - Mohammad, Baker
AU - Ismail, Mohammed
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/2
Y1 - 2014/11/2
N2 - The T and P waves of electrocardiogram signals are excellent indicators in the analysis and interpretation of cardiac arrhythmia. As such, the need to address and develop an accurate delineation technique for the detection of these waves is necessary. In this paper, we present a novel robust and adaptive T and P wave delineation method for real-time analysis and nonstandard ECG morphologies. The proposed method is based on ECG signal filtering, value estimation of different fiducial points, applying backward and forward search windows as well as adaptive thresholds. Simulations and evaluations prove the accuracy of the proposed technique in comparison to those proposed techniques in the literature. The mean error for the T peak, T offset, P peak and P offset values are found to be 9.8, 2.3, 7.3 and 3.5 milliseconds, respectively, based on the Physionet QT database, rendering our algorithm as an excellent candidate for ECG signal analysis.
AB - The T and P waves of electrocardiogram signals are excellent indicators in the analysis and interpretation of cardiac arrhythmia. As such, the need to address and develop an accurate delineation technique for the detection of these waves is necessary. In this paper, we present a novel robust and adaptive T and P wave delineation method for real-time analysis and nonstandard ECG morphologies. The proposed method is based on ECG signal filtering, value estimation of different fiducial points, applying backward and forward search windows as well as adaptive thresholds. Simulations and evaluations prove the accuracy of the proposed technique in comparison to those proposed techniques in the literature. The mean error for the T peak, T offset, P peak and P offset values are found to be 9.8, 2.3, 7.3 and 3.5 milliseconds, respectively, based on the Physionet QT database, rendering our algorithm as an excellent candidate for ECG signal analysis.
UR - http://www.scopus.com/inward/record.url?scp=84929484202&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2014.6943536
DO - 10.1109/EMBC.2014.6943536
M3 - Conference contribution
C2 - 25569904
AN - SCOPUS:84929484202
T3 - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
SP - 90
EP - 93
BT - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Y2 - 26 August 2014 through 30 August 2014
ER -