title: Long-term ECG signal feature extraction.
abstract: 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.
authors: Department of Mechanical Engineering, National Central University Chungli, Taiwan, 320, Republic of China. rgg@ms7.hinet.net
authors: K-K
authors: KK
authors: Jen
authors: Y-R
authors: YR
authors: Hwang
mesh_terms: D000465:Algorithms; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods; D012815:Signal Processing, Computer-Assisted