思维状态的EEG信号分类方法研究

Classification for EEG signals of different mental tasks

脑电信号(EEG)是一种研究脑活动的重要信息来源,基于脑电信号的人与计算机的通信已成为一种新的人机接口方式。运用时域回归方法对2～5种不同思维脑电信号进行预处理,用AR模型提取信号分段前后特征,最后用BP算法进行分类。并对分段前后的分类结果进行比较,实验表明,该方法达到很好的分类效果。

Electroencephalogram （EEG） signal is an important information source of underlying brain processes. The communication based on EEG between human brain and computer is a new modality of human-computer interaction. Through time-domain regression method for 2-5 kinds of EEG Denoising pretreatment,AR model Coefficient is extracted as feature vector,classifies themental tasks based on BP network.Comparing the classification results experiments show that this method can achieve good classification results.