• DocumentCode
    126726
  • Title

    Brain networks based on EEG between high and low-proficiency operators by controlling of mineral grinding process

  • Author

    Chengcheng Hua ; Hong Wang ; Shaowen Lu

  • Author_Institution
    State Key Lab. of Synthetical Autom. for Process Ind., Shenyang, China
  • fYear
    2014
  • fDate
    16-23 Aug. 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper presents the difference in brain networks between the high-proficiency operators and low-proficiency operators while they did the controlling of mineral grinding process. The brain functional connectivity during the controlling task was investigated by means of Granger causality, like partial direct coherence (PDC) based on EEG. In the experiment, the ocular artifacts were removed using Independent Component Analysis (ICA) and sample entropy. The results show that the brain networks of high-proficiency operators (Hps) are more complex and complete than low-proficiency operators´ (Lps) (p<;0.05). The brain networks could be a useful method to describe the operators´ proficiency.
  • Keywords
    causality; electroencephalography; grinding; independent component analysis; mineral processing; process control; EEG signal; Granger causality; ICA; brain functional connectivity; brain networks; high-proficiency operators; independent component analysis; low-proficiency operators; mineral grinding process control; partial direct coherence; sample entropy; Brain models; Computational modeling; Electrodes; Electroencephalography; Mathematical model; Process control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    General Assembly and Scientific Symposium (URSI GASS), 2014 XXXIth URSI
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/URSIGASS.2014.6930085
  • Filename
    6930085