Channel selection in single-trial evoked potentials estimation
通道选择对诱发脑电单次提取精度影响的研究

Adopting the "Imitating-natural-reading" elicited potentials as carriers between brain and computer,the evoked potentials were extracted by support vector machines.Taking the signals from the four EEG recordings as features and setting the time length of signal in a trial as 300ms,the classification rates were tested on average with three time intervals,namely,100ms~400ms,200ms~500ms,and 300ms~600ms,for every subject respectively,and got the best classification accuracy of 95.9%(subject M),94.3%(subject H),and 93.8%(subject T) in three subjects respectively.The results are good to simplifying the design of our BCI.