Research Institute for Cognition and Robotics - CoR-Lab, Bielefeld University, Germany.
Neural Netw. 2009 Nov;22(9):1329-33. doi: 10.1016/j.neunet.2009.07.003. Epub 2009 Jul 16.
We present a Brain-Computer Interface (BCI) game, the MindGame, based on the P300 event-related potential. In the MindGame interface P300 events are translated into movements of a character on a three-dimensional game board. A linear feature selection and classification scheme is applied to identify P300 events and calculate gradual feedback features from a scalp electrode array. The classification during the online run of the game is computed on a single-trial basis without averaging over subtrials. We achieve classification rates of 0.65 on single-trials during the online operation of the system while providing gradual feedback to the player.
我们提出了一种基于 P300 事件相关电位的脑-机接口（BCI）游戏，称为“MindGame”。在 MindGame 界面中，P300 事件被转换为三维游戏板上的一个字符的运动。我们应用了线性特征选择和分类方案来识别 P300 事件，并从头皮电极阵列计算出逐渐的反馈特征。在游戏的在线运行期间，分类是基于单个试次进行计算的，而不是在子试次上进行平均。在系统的在线运行期间，我们在单个试次上实现了 0.65 的分类率，同时向玩家提供逐渐的反馈。
