A Novel Approach in R Peak Detection Using Hybrid Complex Wavelet (Hcw)
International Journal of Cardiology 124 (2008) 250 – 253 www.elsevier.com/locate/ijcard
Letter to the Editor
A novel approach in R peak detection using Hybrid Complex Wavelet (HCW)
P. Jafari Moghadam Fard, M.H. Moradi ⁎, M.R. Tajvidi
Biomedical Faculty, Amirkabir University of Technology, Tehran, Iran Received 1 November 2006; accepted 25 November 2006 Available online 27 March 2007
Abstract In this letter, by design of Complex Morlet Wavelet and Complex Frequency B-Spline Wavelet and linearly combining them, a novel approach, Hybrid Complex Wavelet, has been proposed to identify and detect the components of ECG signal such as QRS complex and R peak. By train and test of implementing the proposed method on both clinically recorded signals from 40 patients and 30 signals of MIT BIH database, we reached better recognition accuracy in comparison to other well-known approaches. © 2007 Elsevier Ireland Ltd. All rights reserved.
Keywords: Complex wavelet; Hybrid; Detection; R peak; B-spline
1. Introduction The characteristics of Q, R, S and T, as the ECG signal components, represent the clinical status of a cardiac disease patient, among which the R wave properties have more significant importance. Different Linear, Nonlinear and Morphological algorithms have been proposed to detect QRS complex [1,2]. The morphological algorithms, such as Neural Network, although are slow, but if they are trained well, they could search for and detect a specific characteristic of ECG such as QRS complex [3]. Rapid examples of morphological methods are Wavelet Transform (WT) and Complex Wavelet Transform which do not need to be trained [4–7]. In this letter, Complex Morlet Wavelet (CMW) and Complex Frequency B-Spline Wavelet (CFBSW) are designed and linearly combined together to acquire a more efficient transform named, Hybrid Complex Wavelet
(HCW). This novel wavelet can overcome the deficit of CMW in not detecting all the available R peaks and can overcome the deficit
Letter to the Editor
A novel approach in R peak detection using Hybrid Complex Wavelet (HCW)
P. Jafari Moghadam Fard, M.H. Moradi ⁎, M.R. Tajvidi
Biomedical Faculty, Amirkabir University of Technology, Tehran, Iran Received 1 November 2006; accepted 25 November 2006 Available online 27 March 2007
Abstract In this letter, by design of Complex Morlet Wavelet and Complex Frequency B-Spline Wavelet and linearly combining them, a novel approach, Hybrid Complex Wavelet, has been proposed to identify and detect the components of ECG signal such as QRS complex and R peak. By train and test of implementing the proposed method on both clinically recorded signals from 40 patients and 30 signals of MIT BIH database, we reached better recognition accuracy in comparison to other well-known approaches. © 2007 Elsevier Ireland Ltd. All rights reserved.
Keywords: Complex wavelet; Hybrid; Detection; R peak; B-spline
1. Introduction The characteristics of Q, R, S and T, as the ECG signal components, represent the clinical status of a cardiac disease patient, among which the R wave properties have more significant importance. Different Linear, Nonlinear and Morphological algorithms have been proposed to detect QRS complex [1,2]. The morphological algorithms, such as Neural Network, although are slow, but if they are trained well, they could search for and detect a specific characteristic of ECG such as QRS complex [3]. Rapid examples of morphological methods are Wavelet Transform (WT) and Complex Wavelet Transform which do not need to be trained [4–7]. In this letter, Complex Morlet Wavelet (CMW) and Complex Frequency B-Spline Wavelet (CFBSW) are designed and linearly combined together to acquire a more efficient transform named, Hybrid Complex Wavelet
(HCW). This novel wavelet can overcome the deficit of CMW in not detecting all the available R peaks and can overcome the deficit
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