Analyzing complexity and fractality of glucose dynamics in a pregnant woman with type 2 diabetes under treatment

Xiaoyan Chen, Dandan Wang, Jinxiang Lin, Teng Zhang, Shunyou Deng, Lianyi Huang, Yu Jin, Chang Chen, Zhaozhi Zhang, Jun Zheng, Baoqing Sun, Paul Bogdan, Xiaohua Douglas Zhang

Research output: Contribution to journalArticlepeer-review


Currently, the rapid development of continuous glucose monitoring (CGM) device brings new insights into the treatment of diabetic patients including those during pregnancy. Complexity and fractality have recently under fast development for extracting information embodied in glucose dynamics measured using CGM. Although scientists have investigated the difference of complexity in glucose dynamics between diabetes and non-diabetes in order to discover better approaches for diabetes care, no one has analyzed the complexity and fractality of glucose dynamics during the process of adopting CGM to successfully treat pregnant women with type 2 diabetes. Thus, we analyzed the complexity and fractality using power spectral density (PSD), multi-scale sample entropy (MSE) and multifractal detrended fluctuation analysis (MF-DFA) in a clinical case. Our results show that (i) there exists multifractal behavior in blood glucose dynamics; (ii) the alpha stable distribution fits to the glucose increment data better than the Gaussian distribution; and (iii) the “global” complexity indicated by multiscale entropy, spectrum exponent and Hurst exponent increase and the “local” complexity indicated by multifractal spectrum decrease after the successful therapy. Our results offer findings that may bring value to health care providers for managing glucose levels of pregnant women with type 2 diabetes as well as provide scientists a reference on applying complexity and fractality in the clinical practice of treating diabetes.

Original languageEnglish
Pages (from-to)2373-2380
Number of pages8
JournalInternational Journal of Biological Sciences
Issue number11
StatePublished - 2019

Bibliographical note

Funding Information:
This work was supported by University of Macau through Research Grants MYRG2018-00071-FHS and FHS-CRDA-029-002-2017. P.B. gratefully acknowledges the support by the National Science Foundation under CAREER Award CPS-1453860, the U.S. Army Defense Advanced Research Projects Agency (DARPA) under grant no. W911NF-17-1-0076, and DARPA Young Faculty Award under grant no. N66001-17-1-4044.

Publisher Copyright:
© The author(s).


  • Complexity analysis
  • Continuous glucose monitoring
  • Fractal analysis
  • Multiscale sample entropy
  • Type 2 diabetes with pregnancy

ASJC Scopus subject areas

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


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