Electroencephalograph (EEG) recordings during right and left motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain computer interface (BCI) can provide a new communication channel to replace an impaired motor function. It can be used by e.g., handicap users with amyotrophic lateral sclerosis (ALS). In BCI system, the miss-recognition of subject's will causes the dangerous accident. Therefore, Error detection is necessary in order to avoid miss-operation of the machine. In this study, statistical pattern recognition method based on AR model was introduced to discriminate the EEG signals recorded during right and left motor imagery. Next, pattern recognition and spectrum analysis of EEG signals in the correct-recognition and miss-recognition were investigated in order to construct a detection system of miss-recognition. Finally, the possibility of Error detection was confirmed.