Brain Function Networks Reveal Movement-related EEG Potentials Associated with Exercise-induced Fatigue

The present research was aimed to find out EEG potentials related to movement in exercise-induced fatigue task using brain function network analysis, so that future researchers can find more accurate mutual informations between these potentials to detect fatigue to make healthy people exercise better and especially improve the effectiveness of rehabilitation in patients with motor dysfunction. EEG signals from 32 electrode sites of 20 subjects(10 adults (5 females and 5 males) and 10 children (6 females and 4 males) were recorded. We applied network topologies extracted from brain function networks constructed by phase synchronization to identify movement-related electrode sites. We first found that there were significant differences on the global network topologies of subjects of different ages and genders, and the difference between subjects of different ages was greater, so adults and children in the subjects were separated to discuss potential selection related to movement. The following finding illustrated that local network topologies of some electrode sites correlated significantly with the degree of fatigue, we thought and selected such electrode sites to be movement-related. Results showed that 17 potentials in adults, 6 most relevant potentials as important potentials(CP5,C3,AF4,CZ,PZ,C4), and 4 potentials (F4,F8,F3,FC5) in children were selected as movement-related EEG potentials associated with exercise-induced fatigue in rotating the forearm repetitively task. We demonstrated that the credibility of our selections by observing the classification accuracy of local network topologies of non-fatigue state and fatigue state in our selected electrode sites was higher than that of local network topologies of non-fatigue state and fatigue state in our unselected electrode sites, which suggested that our selected movement-related electrode sites were more able to detect non-fatigue state and fatigue state.