title: Task-irrelevant alpha component analysis in motor imagery based brain computer interface.
abstract: In motor imagery based BCI, the alpha rhythm shares the same frequency band with sensorimotor rhythm (SMR), and does not correlate with mental task, which contaminates the SMR recording. Independent component analysis (ICA) was applied to decompose original EEG signal into source components, and a comprehensive method was proposed to discriminate those source components by combining temporal, frequency, spatial, and class label information. Task-irrelevant alpha components were sorted out and their projections were reduced by proper bipolar electrode placement for improving the BCI performance.
authors.affiliation: Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.
authors.forename: Bin
authors.initials: B
authors.lastname: Lou
authors.forename: Bo
authors.initials: B
authors.lastname: Hong
authors.forename: Shangkai
authors.initials: S
authors.lastname: Gao
mesh_terms: D000465:Algorithms; D000513:Alpha Rhythm / Q000379:methods; D001931:Brain Mapping / Q000379:methods; D004569:Electroencephalography / Q000379:methods*; D019054:Evoked Potentials, Motor / Q000502:physiology*; D006801:Humans; D007092:Imagination / Q000502:physiology*; D009044:Motor Cortex / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013647:Task Performance and Analysis; D014584:User-Computer Interface