Complete Ensemble EMD and Hilbert Transform for Heart Beat Detection

被引：1
|
作者：
Colominas, M. A. [1 ]
Schlotthauer, G. [1 ]
Torres, M. E. [1 ]
机构：
[1] Univ Nacl Entre Rios, Fac Ingn, CONICET, Oro Verde, Argentina
来源：
VI LATIN AMERICAN CONGRESS ON BIOMEDICAL ENGINEERING (CLAIB 2014) | 2014年 / 49卷
关键词：
Empirical mode decomposition; data-driven methods; noise-assisted; QRS detection; ECG analysis; EMPIRICAL MODE DECOMPOSITION;
D O I：
10.1007/978-3-319-13117-7_127
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
The problem of heart beat detection is addressed with a new noise-assisted Empirical Mode Decomposition (EMD) method. Although existing algorithms show very good performances in good conditions, they have some difficulties in the presence of complicated waveforms, high levels of noise and strong baseline drift. Here we present a fully automated and unsupervised algorithm. Hilbert transform is used for the construction of envelopes of the extracted components and an entropy-like criterion is used for mode selection. The more difficult electrocardiogram (ECG) derivations are used in this work and the results are compared with the algorithm of Afonso et al., showing a better performance for our algorithm.
引用
收藏
页码：496 / 499
页数：4
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