摘要
针对脑机接口中存在的信号容易受到干扰、操作复杂的问题,利用经济便携式脑电采集设备Emotiv EPOC+搭载了一套基于稳态视觉刺激的脑机交互系统。该脑机接口系统首次将功率谱密度分析、典型相关性分析等方法按照不同权重相结合,使得目标识别的准确率高达98.6%,且该系统具有很高的抗噪能力和可拓展性。
The common brain-computer interface systems perform badly in resisting the noise and seem complicated for operation. In this paper, we designed a brain-computer interaction system that equipped with Emotiv EPOC ＋ to overcome such problems. In particular, by combineing power spectral density analysis and canonical correlation analysis with different weights, we proposed a novel algorithm to improve the recognition rate as high as 98.6% , and it has high anti-noise ability and extensibility.
出处
《信息技术与网络安全》
2018年第2期116-118,139,共4页
Information Technology and Network Security
