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
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;
Conference_Titel :
General Assembly and Scientific Symposium (URSI GASS), 2014 XXXIth URSI
Conference_Location :
Beijing
DOI :
10.1109/URSIGASS.2014.6930085