Complex brain activity analysis and recognition based on multiagent methods

Hao Lan Zhang, Jiming Liu, Margaret G. Dowens

Research output: Journal PublicationArticlepeer-review

2 Citations (Scopus)


Brain activity recognition research has been a challenging area for many decades since Hans Berger described electroencephalogram (EEG) in 1929. Many previous researches cannot successfully identify EEG status due to dynamic brain activities and complicated brain correlation. This article adopts multiagent-based methods to analyze EEG datasets, which can enhance the analytical efficiency through incorporating autonomous, self-coordination characteristics of agents. Intelligent agents are autonomous applications that can improve system compatibility. The preliminary results indicate that the combination of time-dependency correlation method with multiagent method is an efficient solution for brain activity recognition.

Original languageEnglish
Article numbere5855
JournalConcurrency Computation Practice and Experience
Issue number8
Publication statusPublished - 13 Jun 2020


  • AOCs
  • EEG pattern recognition
  • brain informatics
  • multiagents

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Computational Theory and Mathematics


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