摘要
事件相关电位特征提取分析在大脑认知的神经生理基础和临床应用研究中起着重要的作用。基于事件相关电位特征分布的先验知识,提出了一种结合小波多尺度分辨和径向基神经网络进行事件相关电位提取的方法。应用径向基神经网络从脑电信号的小波多尺度分解系数中提取与低频响应相关的成分,实施重构完成事件相关电位特征提取。结果表明该方法具有较强的稳健性。
Feature extraction of event related potential （ERP） plays an important part in both fundamental and clinical researches for cerebral neurophysiology. Based on the prior knowledge of feature distribution of ERP, this paper introduces an approach to feature extraction of ERP from composite EEG, which is combined with wavelet multiresolution analysis （MRA） and radial basis function neural network （RBFNN）. The components related to lowfrequency response can be extracted from the wavelet decomposition coefficients by RBFNN. Then signal reconstruction is implemented to obtain the feature of ERP. Experimental result demonstrates that the approach is reliable.
出处
《医疗卫生装备》
CAS
2005年第8期22-24,共3页
Chinese Medical Equipment Journal
