| 谢松云,张振中,张伟平,赵海涛.基于ICA的脑电信号去噪方法研究与应用[J].中国医学影像技术,2007,23(10):1562~1565 |
| 基于ICA的脑电信号去噪方法研究与应用 |
| Method and application of removing noise from EEG signals based on ICA method |
| 投稿时间：2007-04-20 |
| DOI： |
| 中文关键词: 独立分量分析 脑电信号 信号分离 去噪 |
| 英文关键词:Independent component analysis EEG Signal separation Denoise |
| 基金项目:国家自然科学基金(30470459),西北工业大学科技创新基金(M450212)。 |
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| 中文摘要: |
| 目的 在脑电信号的采集和处理过程中,受到各种各样噪声的影响,为有效地提取和分析检测信号中的有用信息,提出采用独立分量分析(independent component analysis, ICA)的方法对脑电信号进行去噪处理。方法 工频噪声、心电伪迹以及脑电波源信号之间的关系是统计独立的,满足ICA方法的分离条件,可将脑电信号去噪问题转化为独立分量分离问题,通过构造与工频噪声频率相同的正交正弦和余弦信号作为对工频噪声的参考信号,将构造的两个参考信号和心电信号以及含噪脑电信号作为ICA中混合矩阵的输入信号,采用收敛速度快的FastICA算法把脑电信号中的工频噪声和心电伪迹作为独立信号分离出去,得到去噪后的脑电信号。结果 通过ICA方法对噪声进行分离后,脑电信号中的两种噪声基本被消除,并且可很好地保留脑电信号有用成分。结论 将ICA的方法用于去除脑电信号中的多种噪声成分是有效的、可行的。 独立分量分析; 脑电信号; 信号分离; 去噪 |
| 英文摘要: |
| Objective Many noises are interfused into EEG signals when they are measuring. In order to remove the noises effectively, a novel method, based on the ICA theory, is shown in the thesis. Methods Power noise, ECG and EEG source signal are statistically independent, this features meet the requirements of ICA method, so we can transform the problem of denoising to be a problem of signal separation, a sine and a cosine signal are constructed and both of their frequency are equal to the power noise as a reference of power noise, use these two reference signal, ECG signal and noising EEG signal to be the input of ICA mixing matrix, then use FastICA algorithm with a fast convergence to remove power noise and ECG artifact from EEG signal as an independent component. Results By the means of ICA method for noises separation, power noise and ECG artifact are basically been removed with no harm to the details of EEG signals. Conclusion Using ICA method for EEG signals denoising is effective and doable. |
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