Ordinal pattern based complexity analysis for EEG activity evoked by manual acupuncture in healthy subjects

Guosheng Yi, Jiang Wang, Kai Ming Tsang, Wai Lok Chan, Xile Wei, Bin Deng, Chunxiao Han

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)


Manual acupuncture (MA) is widely used in Traditional Chinese Medicine clinic for pain treatment and controlling stress. To investigate how MA modulates brain activities, electroencephalograph (EEG) signals are recorded with 20 channels by MA at ST36 of right leg in 11 healthy subjects during rest. Two novel nonlinear measures based on ordinal patterns of EEG series, i.e. permutation entropy (PE) and order index (OI), are adopted to investigate the nonlinear complexity characteristic in EEG data at different acupuncture states. It is observed that the recorded EEG series during and after MA have higher PE values and lower OI values compared to before MA. The results show that MA at ST36 can increase EEG complexity, which is especially obvious during MA. Our findings suggest that the PE and OI measures are promising methods to reveal EEG dynamical changes associated with MA stimulus, which could provide a potential for further exploring the interactions between acupuncture and brain activity. Moreover, these preliminary conclusions highlight the beneficial modulations of brain activity by MA, which could contribute to understanding the acupuncture effects on brain, as well as the neurophysiological mechanisms underlying MA.
Original languageEnglish
Article number1450018
JournalInternational Journal of Bifurcation and Chaos
Issue number2
Publication statusPublished - 1 Jan 2014


  • complexity
  • EEG
  • Manual acupuncture
  • order index
  • permutation entropy

ASJC Scopus subject areas

  • Modelling and Simulation
  • Applied Mathematics


Dive into the research topics of 'Ordinal pattern based complexity analysis for EEG activity evoked by manual acupuncture in healthy subjects'. Together they form a unique fingerprint.

Cite this