000201757 001__ 201757
000201757 005__ 20180913062659.0
000201757 0247_ $$2doi$$a10.3217/978-3-85125-378-8-73
000201757 037__ $$aCONF
000201757 245__ $$aTowards Implementation of Motor Imagery using Brain Connectivity Features
000201757 269__ $$a2014
000201757 260__ $$c2014
000201757 336__ $$aConference Papers
000201757 520__ $$aThis study aims to explore modulation of the connectivity pattern when people perform left hand versus right hand motor imagery and probe the feasibility of adopting connectivity information to discriminate these tasks. Nine subjects were recorded with 16-channel EEG system, covering sensorimotor cortex. Non-normalized directed transfer function (DTF) is used to obtain the brain connectivity between EEG electrodes. The results demonstrate that the modulations of intrahemispheric and interhemispheric information flows are not identical during left and right hand motor imageries. Particularly, the mu rhythm is highly modulated in intrahemispheric brain interactions, whereas the high frequency bands are more related with distant interhemispheric brain interactions. Furthermore, classification results suggest that the DTF features bring additional informative features for the classification between two tasks.
000201757 700__ $$0245439$$aZhang, Huaijian$$g209107
000201757 700__ $$0241256$$aChavarriaga, Ricardo$$g137762
000201757 700__ $$0240030$$aMillán, José del R.$$g149175
000201757 7112_ $$a6th International Brain-Computer Interface Conference$$cGraz, Austria$$dSeptember 16-19, 2014
000201757 8564_ $$s179586$$uhttps://infoscience.epfl.ch/record/201757/files/hjzhang_Graz_2014.pdf$$yPreprint$$zPreprint
000201757 909C0 $$0252018$$pCNBI$$xU12103
000201757 909C0 $$0252517$$pCNP$$xU12599
000201757 909CO $$ooai:infoscience.tind.io:201757$$pconf$$pSTI
000201757 917Z8 $$x209107
000201757 917Z8 $$x209107
000201757 917Z8 $$x137762
000201757 917Z8 $$x149175
000201757 937__ $$aEPFL-CONF-201757
000201757 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000201757 980__ $$aCONF