TY - GEN
T1 - Feature extraction based on Wavelet Transform using ECG signal
AU - Palacios-Enriquez, A.
AU - Ponomaryov, V.
PY - 2013
Y1 - 2013
N2 - The electrocardiographic signal (ECG) is being commonly used for diagnosis of different heart disease. A cardiac cycle consists of the P, Q, R, S and T waves [1] where the most significant ECG information is in the locations of the characteristics for these waves. The estimations of the heartbeat features are necessary in the diagnostic of several anomalies including some related arrhythmias such as tachycardia or bradycardia [2]. Different methods exist in this area [5, 6] but by now, the estimation of the ECG waves is a difficult problem because electrocardiographic signal depends on the physiological conditions of a patient to be investigated. In this paper, the feature extraction based on Wavelet Transform (WT) is applied as the first step, estimating several waveforms that can be employed for future diagnostic purposes. The proposed procedure uses different decomposition levels of WT applying the Haar wavelet function that presents the better results in the location of R-wave.
AB - The electrocardiographic signal (ECG) is being commonly used for diagnosis of different heart disease. A cardiac cycle consists of the P, Q, R, S and T waves [1] where the most significant ECG information is in the locations of the characteristics for these waves. The estimations of the heartbeat features are necessary in the diagnostic of several anomalies including some related arrhythmias such as tachycardia or bradycardia [2]. Different methods exist in this area [5, 6] but by now, the estimation of the ECG waves is a difficult problem because electrocardiographic signal depends on the physiological conditions of a patient to be investigated. In this paper, the feature extraction based on Wavelet Transform (WT) is applied as the first step, estimating several waveforms that can be employed for future diagnostic purposes. The proposed procedure uses different decomposition levels of WT applying the Haar wavelet function that presents the better results in the location of R-wave.
UR - http://www.scopus.com/inward/record.url?scp=84888580162&partnerID=8YFLogxK
U2 - 10.1109/MSMW.2013.6622145
DO - 10.1109/MSMW.2013.6622145
M3 - Contribución a la conferencia
AN - SCOPUS:84888580162
SN - 9781479910663
T3 - Proceedings - 2013 International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, MSMW 2013
SP - 632
EP - 634
BT - Proceedings - 2013 International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, MSMW 2013
T2 - 2013 International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, MSMW 2013
Y2 - 23 June 2013 through 28 June 2013
ER -