消除脑电图伪差的数据处理方法

Data Processing Method for Eliminating EEG Artifacts

本文提出了一种消除电脑电图主要伪差（肌电伪差、眼动伪差和基线漂移）的实用有效方法．即用线性Ｋａｌｍａｎ滤波未消除脑电图的肌电伪差，用ＦＩＲ数字高通滤波器抑制眼动伪差及基线漂移，取得了良好的效果，为进一步设计脑电图的计算机自动化分析和诊断系统，解决了关键性的问题．在数据处理的同时还对线性Ｋａｌｍａｎ滤波经行了改进，即去除了肌电伪差模型，使系统更为简洁，滤波效果更好．

This paper describs an efffective method for removing main artifacts (the muscle artifacts, the ocular movement artifacts and the DC drift) from the EEG signal. In procedure, the muscle artiffacts is reduced by the linear Kalman filter, the ocular movement artifacts and the DC drift are reducted by the high-pass FIR digital filter. The key to designing the automatic analysis and diagnosing system for EEG is solved. Meanwhile, the authors improve the methed for removing the muscle artifacts-Kalman filter, it is that the EMG artifacts model is eliminated. Thus, the system is simple and useful and may find a general application in the field of noise reduction contatined in the wide set of biological signals