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Approximate entropy analysis of short-term HFECG based on wave mode

Author

Listed:
  • Ning, Xinbao
  • Xu, Yinlin
  • Wang, Jun
  • Ma, Xiaofei

Abstract

An improved approximate entropy (ApEn) algorithm based on wave mode is proposed by analyzing and modifying ApEn, so that the irregular analysis can be applied to analyze the short-term series, which contain a great deal of detailed information and fluctuate slowly but in a wide range, such as high-frequency electrocardiogram (HFECG). By analyzing the complexity of HFECG, a conclusion can be drawn that ApEn algorithm based on wave mode can obviously distinguish heart diseases from the healthy group. Therefore, it is of significance for diagnosing myocardial infarction in time.

Suggested Citation

  • Ning, Xinbao & Xu, Yinlin & Wang, Jun & Ma, Xiaofei, 2005. "Approximate entropy analysis of short-term HFECG based on wave mode," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(3), pages 475-483.
    • Handle: RePEc:eee:phsmap:v:346:y:2005:i:3:p:475-483
    DOI: 10.1016/j.physa.2004.07.040
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    Cited by:

    1. Tamara Skoric & Olivera Sarenac & Branislav Milovanovic & Nina Japundzic-Zigon & Dragana Bajic, 2017. "On Consistency of Cross-Approximate Entropy in Cardiovascular and Artificial Environments," Complexity, Hindawi, vol. 2017, pages 1-15, September.
    2. Yang, Xiaodong & Wang, Zhixiao & He, Aijun & Wang, Jun, 2020. "Identification of healthy and pathological heartbeat dynamics based on ECG-waveform using multifractal spectrum," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).

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