TY - GEN
T1 - Heart arrhythmia detection using continuous wavelet transform and principal component analysis with neural network classifier
AU - Ghorbanian, Parham
AU - Ghaffari, Ali
AU - Jalali, Ali
AU - Nataraj, C.
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - The aim of this study is to develop an algorithm to detect and classify six types of electrocardiogram (ECG) signal beats including normal beats (N), atrial premature beats (A), right bundle branch block beats (R), left bundle branch block beats (L), paced beats (P), and premature ventricular contraction beats (PVC or V) using a neural network classifier. In order to prepare an appropriate input vector for the neural classifier several preprocessing stages have been applied. Continuous wavelet transform (CWT) has been applied in order to extract features from the ECG signal. Moreover, Principal component analysis (PCA) is used to reduce the size of the data. Finally, the MIT-BIH database is used to evaluate the proposed algorithm, resulting in 99.5% sensitivity (Se), 99.66% positive predictive accuracy (PPA) and 99.17% total accuracy (TA).
AB - The aim of this study is to develop an algorithm to detect and classify six types of electrocardiogram (ECG) signal beats including normal beats (N), atrial premature beats (A), right bundle branch block beats (R), left bundle branch block beats (L), paced beats (P), and premature ventricular contraction beats (PVC or V) using a neural network classifier. In order to prepare an appropriate input vector for the neural classifier several preprocessing stages have been applied. Continuous wavelet transform (CWT) has been applied in order to extract features from the ECG signal. Moreover, Principal component analysis (PCA) is used to reduce the size of the data. Finally, the MIT-BIH database is used to evaluate the proposed algorithm, resulting in 99.5% sensitivity (Se), 99.66% positive predictive accuracy (PPA) and 99.17% total accuracy (TA).
UR - http://www.scopus.com/inward/record.url?scp=79953818414&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79953818414&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:79953818414
SN - 9781424473182
T3 - Computing in Cardiology
SP - 669
EP - 672
BT - Computing in Cardiology 2010, CinC 2010
T2 - Computing in Cardiology 2010, CinC 2010
Y2 - 26 September 2010 through 29 September 2010
ER -