Long-term ECG signal feature extraction.

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.