Jin Jing, Allison Brendan Z, Brunner Clemens, Wang Bei, Wang Xingyu, Zhang Jianhua, Neuper Christa, Pfurtscheller Gert
School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China.
Biomed Tech (Berl). 2010 Feb;55(1):5-18. doi: 10.1515/BMT.2010.003.
A brain-computer interface (BCI) is a new communication channel between humans and computers that translates brain activity into recognizable command and control signals. Attended events can evoke P300 potentials in the electroencephalogram. Hence, the P300 has been used in BCI systems to spell, control cursors or robotic devices, and other tasks. This paper introduces a novel P300 BCI to communicate Chinese characters. To improve classification accuracy, an optimization algorithm (particle swarm optimization, PSO) is used for channel selection (i.e., identifying the best electrode configuration). The effects of different electrode configurations on classification accuracy were tested by Bayesian linear discriminant analysis offline. The offline results from 11 subjects show that this new P300 BCI can effectively communicate Chinese characters and that the features extracted from the electrodes obtained by PSO yield good performance.
脑机接口（BCI）是人与计算机之间一种新的通信通道，它将大脑活动转化为可识别的命令和控制信号。所关注的事件能够在脑电图中诱发P300电位。因此，P300已被用于脑机接口系统中进行拼写、控制光标或机器人设备以及其他任务。本文介绍了一种用于汉字通信的新型P300脑机接口。为提高分类准确率，采用一种优化算法（粒子群优化算法，PSO）进行通道选择（即确定最佳电极配置）。通过离线贝叶斯线性判别分析测试了不同电极配置对分类准确率的影响。来自11名受试者的离线结果表明，这种新型P300脑机接口能够有效地进行汉字通信，并且从通过粒子群优化算法获得的电极提取的特征具有良好的性能。
