A brain-computer interface (BCI) is a type of system that can directly acquire signals from the human brain and translate them into digital commands that can be recognized and processed on a computer. A BCI provides a pathway for reestablishing communication and environmental control capability to severely disabled persons. While BCI spellers show great promise in BCI's research, they require improved information transfer rate (ITR) to be effective. To improve the ITR, we propose a double row/column (RC) paradigm based hybrid BCI spelling approach that employs P300 and SSVEP as the signals that are used simultaneously to spell characters. In this approach, the target character is identified by 4-dimensional coordinates that are realized by the two brain activity patterns. Each coordinate of the target is detected by the hybrid brain potential using fusion method.