摘要
微弱的脑电信号中常混有工频干扰,严重影响到有用的脑电信号提取和分析。针对传统陷波器会削弱有用的脑电信号的缺陷,文中研究了三种稳健算法:基于零极点分布原理的陷波器、自适应滤波器以及独立成分分析算法,来抑制脑电信号中的工频干扰。仿真实验结果表明,三种算法都可以成功去除脑电信号中的工频干扰成分,并且较传统陷波器对工频附近频谱影响更小,从而有效地克服了传统陷波器的缺陷;此外,独立成分分析算法能更好地保留有用的脑电信息,具有更大的优越性。另外,三种算法都可以应用于其他需要陷波的场合,具有很好的扩展性。
Electroencephalogram（EEG）is feeble and it is always contaminated by power line interference,which makes it difficult to extract and analyze EEG signals.Traditional notch filter weakens parts of EEG signals since its spectrum is close to power line interference.In this paper,three robust algorithms are investigated,which are notch filter based on pole-zero placement algorithm,adaptive notch filter and independent component analysis（ICA）.Comprehensive comparisons between these algorithms are made and the experimental results demonstrate that the proposed algorithms can eliminate 50 Hz power line interference successfully and do little harm to useful EEG signals.Remarkably,ICA algorithm is the best choice for extracting EEG signals and eliminating artifacts due to its perfect performance shown in our experiments.In addition,these algorithms can be applied to other scenarios where notch filter is needed.
出处
《传感技术学报》
CAS
CSCD
北大核心
2010年第1期87-92,共6页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金资助课题(60503027)
