Long-term ECG signal feature extraction

K. K. Jen, Y. R. Hwang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This paper proposes a cepstrum coefficient method applying the dynamic time warping technique to extract the feature vectors from long-term ECG signals. Utilizing this method, one can identify the characteristics hidden in an ECG signal; and then classify the signal as well as diagnose the abnormalities. To evaluate this method, the Normal and PACED BEAT data from the MIT/BIH database are used. The results show that the proposed method successfully extracts the corresponding feature vectors, distinguishes the difference and classifies both signals.

Original languageEnglish
Pages (from-to)202-209
Number of pages8
JournalJournal of Medical Engineering and Technology
Issue number3
StatePublished - May 2007


  • Cepstrum
  • Dynamic time warping
  • ECG
  • Signal processing


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