The P300-based spelling system is one of the most popular brain–computer interface applications. Its success largely depends on performance, including information transmission rate (ITR) and detection (i.e., accuracy). To achieve good we proposed a multiscale convolutional neural network (MS-CNN) model that consists seven layers. First, an upfront data set was used to train MS-CNN, aiming obtai...