Assessing the complexity of short-term heartbeat interval series by distribution entropy-Reference-Cited by-同舟云学术

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Assessing the complexity of short-term heartbeat interval series by distribution entropy

Published:2014-10-29 Issue:1 Volume:53 Page:77-87
ISSN:0140-0118
Container-title:Medical & Biological Engineering & Computing
language:en
Short-container-title:Med Biol Eng Comput

Author:

Li Peng,Liu Chengyu,Li Ke,Zheng Dingchang,Liu Changchun,Hou Yinglong

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Biomedical Engineering

Link

http://link.springer.com/content/pdf/10.1007/s11517-014-1216-0.pdf

Reference40 articles.

1. Amoud H, Snoussi H, Hewson D, Doussot M, Duchene J (2007) Intrinsic mode entropy for nonlinear discriminant analysis. IEEE Signal Process Lett 14(5):297–300

2. Bandt C, Pompe B (2002) Permutation entropy: a natural complexity measure for time series. Phys Rev Lett 88(17):174102

3. Bolea J, Laguna P, Remartínez JM, Rovira E, Navarro A, Bailón R (2014) Methodological framework for estimating the correlation dimension in HRV signals. Comput Math Methods Med 2014:1–11

4. Castiglioni P, Di Rienzo M (2008) How the threshold r influences approximate entropy analysis of heart-rate variability. In: Computers in Cardiology, Bologna, Italy, pp 561–564

5. Chen W, Zhuang J, Yu W, Wang Z (2009) Measuring complexity using FuzzyEn, ApEn, and SampEn. Med Eng Phys 31(1):61–68

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