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Article Navigation >  Journal of University of Electronic Science and Technology of China  > 2011  >  40(1): 142-146

GUO Xing-ming, TANG Li-ping, CHEN Li-shan, CHEN Mao-mao. Empirical Mode Decomposition for QRS Complexes and T Wave Detection[J]. Journal of University of Electronic Science and Technology of China, 2011, 40(1): 142-146. doi: 10.3969/j.issn.1001-0548.2011.01.027
Citation: GUO Xing-ming, TANG Li-ping, CHEN Li-shan, CHEN Mao-mao. Empirical Mode Decomposition for QRS Complexes and T Wave Detection[J]. Journal of University of Electronic Science and Technology of China, 2011, 40(1): 142-146. doi: 10.3969/j.issn.1001-0548.2011.01.027
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Empirical Mode Decomposition for QRS Complexes and T Wave Detection

doi: 10.3969/j.issn.1001-0548.2011.01.027
  • 1.

    College of Bioengineering,Chongqing University Shapingba Chongqing 400044

  • Received Date: 2009-10-21
  • Rev Recd Date: 2010-05-21
  • Publish Date: 2011-02-15
  • In order to detect the position of QRS and T wave in a non-preprocessed ECG signal, a combination method of the empirical mode decomposition (EMD) and morphological algorithm is introduced in this paper. Firstly, a novel boundary processing method is proposed to decrease the boundary distortion of EMD by means of signal extending. Secondly, the improved EMD is used to decompose the ECG signal into stationary intrinsic mode functions (IMFs) and residual components. Next, the two IMFs of low frequencies are reconstructed after de-noising with threshold method, and then the reconstructed signal is supplied to orient QRS to morphological method. T wave is detected by residual components. This method has been validated by the data from the MIT-BIH database, and the result shows that the detection rate of QRS is up to 99%. Moreover, this method has higher accuracy and better real-time performance compared with the traditional methods.
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  • 1. 

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Empirical Mode Decomposition for QRS Complexes and T Wave Detection

doi: 10.3969/j.issn.1001-0548.2011.01.027
  • 1. College of Bioengineering,Chongqing University Shapingba Chongqing 400044
  • Received Date: 2009-10-21
  • Rev Recd Date: 2010-05-21
  • Publish Date: 2011-02-15

Abstract: In order to detect the position of QRS and T wave in a non-preprocessed ECG signal, a combination method of the empirical mode decomposition (EMD) and morphological algorithm is introduced in this paper. Firstly, a novel boundary processing method is proposed to decrease the boundary distortion of EMD by means of signal extending. Secondly, the improved EMD is used to decompose the ECG signal into stationary intrinsic mode functions (IMFs) and residual components. Next, the two IMFs of low frequencies are reconstructed after de-noising with threshold method, and then the reconstructed signal is supplied to orient QRS to morphological method. T wave is detected by residual components. This method has been validated by the data from the MIT-BIH database, and the result shows that the detection rate of QRS is up to 99%. Moreover, this method has higher accuracy and better real-time performance compared with the traditional methods.

GUO Xing-ming, TANG Li-ping, CHEN Li-shan, CHEN Mao-mao. Empirical Mode Decomposition for QRS Complexes and T Wave Detection[J]. Journal of University of Electronic Science and Technology of China, 2011, 40(1): 142-146. doi: 10.3969/j.issn.1001-0548.2011.01.027
Citation: GUO Xing-ming, TANG Li-ping, CHEN Li-shan, CHEN Mao-mao. Empirical Mode Decomposition for QRS Complexes and T Wave Detection[J]. Journal of University of Electronic Science and Technology of China, 2011, 40(1): 142-146. doi: 10.3969/j.issn.1001-0548.2011.01.027
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