In this study, we developed a practical EEG-based BCI paradigm for online binary communication of patients in completely locked-in state (CLIS). The performance of our BCI paradigm was evaluated with a female patient in CLIS, who had never communicated even with her family for more than a year. An average online classification accuracy of 87.5 % was achieved using EEG data recorded just for 5 seconds. This is the first report of successful application of EEG-based BCI to the online yes/no communication of patients in CLIS.