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Complexity change in cardiovascular disease

Research output: Contribution to journal › Review article › peer-review

63 Scopus citations

Abstract

With the fast development of wearable medical device in recent years, it becomes critical to conduct research on continuously measured physiological signals. Entropy is a key metric for quantifying the irregularity and/or complexity contained in human physiological signals. In this review, we focus on exploring how entropy changes in various physiological signals in cardiovascular diseases. Our review concludes that the direction of entropy change relies on the physiological signals under investigation. For heart rate variability and pulse index, the entropy of a healthy person is higher than that of a patient with cardiovascular diseases. For diastolic period variability and diastolic heart sound, the direction of entropy change is reversed. Our conclusion should not only give valuable guidance for further research on the application of entropy in cardiovascular diseases but also provide a foundation for using entropy to analyze the irregularity and/or complexity of physiological signals measured by wearable medical device.

Original languageEnglish
Pages (from-to)1320-1328
Number of pages9
JournalInternational Journal of Biological Sciences
Volume13
Issue number10
DOIs
StatePublished - 2017

Bibliographical note

Publisher Copyright:
© Ivyspring International Publisher.

Funding

This work was supported by the Start-up Research Grant (SRG2016-00083-FHS) at University of Macau.

FundersFunder number
Universidade de MacauSRG2016-00083-FHS

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • Cardiovascular disease
    • Complexity
    • Entropy
    • Irregularity
    • Physiological signal

    ASJC Scopus subject areas

    • Ecology, Evolution, Behavior and Systematics
    • Applied Microbiology and Biotechnology
    • Molecular Biology
    • Developmental Biology
    • Cell Biology

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