Constructing weighted networks based on EEG data segmentation for brain wave pattern recognition

Hao Lan Zhang, Xingsen Li, Jiming LIU, Yiu Ming CHEUNG

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The human brain is an extremely complex study. In recent years, EEG (Electroencephalography) data sets have been studied extensively in the various fields, particularly in the area of brain study. Some psychological work has suggested that human brains can generate EEG signals that are based on individual entities. These EEG signals varies according to different identities. This paper suggests a weighted network method for brain pattern recognition. The data segmentation technique is deployed in the process of constructing weighted networks. The EEG data segmentation technique incorporates the normal distribution sampling method [1]. The EEG data sets are obtained from various experiments including shopping psychological EEG data sets, driving EEG data sets, etc. This research discovers the potential of generating an efficient network for brain wave pattern recognition. The future work will further extend the current work and applied the proposed method to the human-robotic control and security areas.

Original languageEnglish
Title of host publicationProceedings - 2018 10th International Conference on Advanced Computational Intelligence, ICACI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages852-855
Number of pages4
ISBN (Electronic)9781538643624
DOIs
Publication statusPublished - 8 Jun 2018
Event10th International Conference on Advanced Computational Intelligence, ICACI 2018 - Xiamen, Fujian, China
Duration: 29 Mar 201831 Mar 2018

Publication series

NameProceedings - 2018 10th International Conference on Advanced Computational Intelligence, ICACI 2018

Conference

Conference10th International Conference on Advanced Computational Intelligence, ICACI 2018
Country/TerritoryChina
CityXiamen, Fujian
Period29/03/1831/03/18

Scopus Subject Areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Modelling and Simulation
  • Control and Optimization

User-Defined Keywords

  • Data mining
  • EEG
  • Pattern recognition

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