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Multifractal analysis of electronic cardiogram taken from healthy and unhealthy adult subjects

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  • Wang, Jun
  • Ning, Xinbao
  • Chen, Ying

Abstract

Electronic Cardiogram (ECG) data taken from healthy adult subjects are found to characterize multifractality. In order to quantitatively analyze multifractal spectrum, the area of the spectrum is computed. We have a comparison between the spectrum of the young subjects and that of the old ones. We find that the area of young adult subject's multifractal spectrum is far larger than the older one's and the logarithm of the area of the spectrum is inversely proportion to age. It shows that when time is running on human heartbeat energy is exponentially decreasing until heart failure. And distinct difference between the area of the multifractal spectrum of healthy subjects and that of having coronary disease is not found. We analyze the ECG data taken from patients with brain injury. The area of their ECG multifractal spectrum is distinctly descending. It shows that a person's multifractal spectrum is controlled mainly by his neurosystem. With advancing age, the neuroautonomic control of people's body on the ECG decreases and tends from multifractality to monofractality.

Suggested Citation

  • Wang, Jun & Ning, Xinbao & Chen, Ying, 2003. "Multifractal analysis of electronic cardiogram taken from healthy and unhealthy adult subjects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 561-568.
    • Handle: RePEc:eee:phsmap:v:323:y:2003:i:c:p:561-568
    DOI: 10.1016/S0378-4371(03)00045-1
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    Citations

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    Cited by:

    1. Yang, Xiaodong & Ning, Xinbao & Wang, Jun, 2007. "Multifractal analysis of human synchronous 12-lead ECG signals using multiple scale factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 413-422.
    2. Yuxin Zhao & Shuai Chang & Chang Liu, 2015. "Multifractal theory with its applications in data management," Annals of Operations Research, Springer, vol. 234(1), pages 133-150, November.
    3. 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).
    4. Dailyudenko, Victor F., 2008. "Topological considerations of an attractor based on temporal locality along its phase trajectories," Chaos, Solitons & Fractals, Elsevier, vol. 37(3), pages 876-893.
    5. Yang, Xiaodong & Du, Sidan & Ning, Xinbao & Bian, Chunhua, 2008. "Mass exponent spectrum analysis of human ECG signals and its application to complexity detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3546-3554.

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