Jen K-K, Hwang Y-R
Department of Mechanical Engineering, National Central University Chungli, Taiwan, 320, Republic of China.
J Med Eng Technol. 2007 May-Jun;31(3):202-9. doi: 10.1080/03091900600718675.
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.
本文提出了一种应用动态时间规整技术的倒谱系数方法，用于从长期心电图信号中提取特征向量。利用该方法，能够识别隐藏在心电图信号中的特征，进而对信号进行分类并诊断异常情况。为评估该方法，使用了麻省理工学院/贝斯以色列女执事医疗中心（MIT/BIH）数据库中的正常和起搏心跳数据。结果表明，所提方法成功提取了相应的特征向量，区分了差异并对两种信号进行了分类。
