CAJ | 학술논문

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,三种箅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.
미약적뇌전신호중상혼유공빈간우,엄중영향도유용적뇌전신호제취화분석.침대전통함파기회삭약유용적뇌전신호적결함,문중연구료삼충은건산법:기우령겁점분포원리적함파기、자괄응려파기이급독립성분분석산법,래억제뇌전신호중적공빈간우.방진실험결과표명,삼충폐법도가이성공거제뇌전신호중적공빈간우성분,병차교전통함파기대공빈부근빈보영향경소,종이유효지극복료전통함파기적결함;차외,독립성분분석산법능경호지보류유용적뇌전신식,구유경대적우월성.령외,삼충산법도가이응용우기타수요함파적장합,구유흔호적확전성.
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.