000180083 001__ 180083
000180083 005__ 20190812205633.0
000180083 037__ $$aCONF
000180083 245__ $$aReal-time Prediction of Fast and Slow Delivery of Mental Commands in a Motor Imagery BCI: An Entropy-based Approach
000180083 269__ $$a2012
000180083 260__ $$c2012
000180083 336__ $$aConference Papers
000180083 520__ $$aProviding adaptive shared control for Brain- Computer Interfaces (BCIs) can result in better performance while reducing the user’s mental workload. In this respect, online estimation of accuracy and speed of command delivery are important factors. This study aims at real-time differentiation between fast and slow trials in a motor imagery BCI. In our experiments, we refer to trials shorter than the median of trial lengths as “fast” trials and to those longer than the median as “slow” trials. We propose a classifier for real-time distinction between fast and slow trials based on estimates of the entropy rates for the first 2-3 s of the electroencephalogram (EEG). Results suggest that it can be predicted whether a trial is slow or fast well before a cutoff time. This is important for adaptive shared control especially because 55% to 75% of trials (for the five subjects in this study) are longer than that cutoff time
000180083 6531_ $$aBrain-Computer Interface (BCI)
000180083 6531_ $$aShared Control
000180083 6531_ $$aEEG
000180083 6531_ $$aEntropy
000180083 700__ $$0245183$$g204823$$aSaeedi, Sareh
000180083 700__ $$0241256$$g137762$$aChavarriaga, Ricardo
000180083 700__ $$g122796$$aGastpar, Michael C.$$0241387
000180083 700__ $$aMillán, José del R.$$g149175$$0240030
000180083 7112_ $$dOctober 14-17, 2012$$cSeoul, S. Korea$$aThe 2012 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2012)
000180083 773__ $$j42$$tIEEE Transactions on Systems, Man, and Cybernetics$$k3$$q3327-3331
000180083 8564_ $$zn/a$$yn/a$$uhttps://infoscience.epfl.ch/record/180083/files/SMC2012F_Saeedi_1.pdf$$s206326
000180083 909C0 $$xU12367$$pNCCR-ROBOTICS$$0252409
000180083 909C0 $$0252018$$xU12103$$pCNBI
000180083 909C0 $$xU12599$$pCNP$$0252517
000180083 909CO $$qGLOBAL_SET$$pconf$$pSTI$$ooai:infoscience.tind.io:180083
000180083 917Z8 $$x204823
000180083 917Z8 $$x204823
000180083 917Z8 $$x204823
000180083 917Z8 $$x137762
000180083 917Z8 $$x137762
000180083 917Z8 $$x204823
000180083 937__ $$aEPFL-CONF-180083
000180083 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000180083 980__ $$aCONF