In order to more effectively apply an artifact removal melhod in an online brain-computer interface （BCI） system, a new method based on canonical correlation analysis （CCA） and two-channel eleetroeneephalography ...In order to more effectively apply an artifact removal melhod in an online brain-computer interface （BCI） system, a new method based on canonical correlation analysis （CCA） and two-channel eleetroeneephalography （EEG） recordings to quickly remove ocular artifacts （OA） is proposed in this paper. Considering both the formation of EEG signals contaminated by OA and the spread of OA, vertical electrooculo~＇aphy （VEOG） was appropriately introduced in CCA, and the blind source separation （BSS~ method based on CCA was used in a new way during the OA removal process. Both experimental and comparison with ICA and SOBI results show that the new method with simple calculation and fast processing speed can effectively separate and remove OA using only two-channel EEG recordings, with retaining useful EEG signals. Hence, this method used in an online BCI system will be more effective.展开更多
基金National Science Foundation of China grant number: 61172108,61139001 and 60872122+1 种基金Shanghai Dianji University Leading Academic Discipine Project grant number: 10xkf01
文摘In order to more effectively apply an artifact removal melhod in an online brain-computer interface （BCI） system, a new method based on canonical correlation analysis （CCA） and two-channel eleetroeneephalography （EEG） recordings to quickly remove ocular artifacts （OA） is proposed in this paper. Considering both the formation of EEG signals contaminated by OA and the spread of OA, vertical electrooculo~＇aphy （VEOG） was appropriately introduced in CCA, and the blind source separation （BSS~ method based on CCA was used in a new way during the OA removal process. Both experimental and comparison with ICA and SOBI results show that the new method with simple calculation and fast processing speed can effectively separate and remove OA using only two-channel EEG recordings, with retaining useful EEG signals. Hence, this method used in an online BCI system will be more effective.
