Multi-way space-time-wave-vector analysis for EEG source separation
Multi-way space-time-wave-vector analysis for EEG source separation
复制标题
脑电信号源分离的多路时空波矢量分析
DOI：
10.1016/j.sigpro.2011.10.014
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
I. Merlet
中科院分区：
文献类型：
--
作者：
H. Becker;P. Comon;L. Albera;M. Haardt;I. Merlet
对于脑电图数据的源分析，采用等效偶极子模型和更现实的分布式源模型。一些作者已经证明，空时频（STF）数据的正则多进分解（也称为ParaFac）可以用来拟合等效偶极子与电势数据。本文提出了一种新的基于空时波矢量（STWV）数据的多路方法，该方法是通过对测量数据进行三维局部傅里叶变换得到的。这种方法可以看作是分离信号源，降低噪声和干扰，提取信号源时间信号的预处理步骤。结果可以进一步用于定位等效偶极子或分布源，从而提高传统源定位技术（例如LORETA）的性能。此外，我们提出了一种新的迭代源定位算法，称为二元系数匹配追踪（BCMP），该算法基于现实的分布式源模型。计算机模拟用于比较STWV分析与等效偶极子拟合STF技术的性能，并评估STWV方法与LORETA和BCMP相结合的效率，在考虑分布式源场景的情况下，STWV方法会产生更好的结果。
For the source analysis of electroencephalographic (EEG) data, both equivalent dipole models and more realistic distributed source models are employed. Several authors have shown that the canonical polyadic decomposition (also called ParaFac) of space–time–frequency (STF) data can be used to fit equivalent dipoles to the electric potential data. In this paper we propose a new multi-way approach based on space–time–wave-vector (STWV) data obtained by a 3D local Fourier transform over space accomplished on the measured data. This method can be seen as a preprocessing step that separates the sources, reduces noise as well as interference and extracts the source time signals. The results can further be used to localize either equivalent dipoles or distributed sources increasing the performance of conventional source localization techniques like, for example, LORETA. Moreover, we propose a new, iterative source localization algorithm, called Binary Coefficient Matching Pursuit (BCMP), which is based on a realistic distributed source model. Computer simulations are used to examine the performance of the STWV analysis in comparison to the STF technique for equivalent dipole fitting and to evaluate the efficiency of the STWV approach in combination with LORETA and BCMP, which leads to better results in case of the considered distributed source scenarios.
影响因子：
2.7
作者：
Lantz, G;Menendez, RGD;Michel, CM
通讯作者：
Michel, CM
研究文章发作期头皮脑电图的规范分解和准确的源定位：原理和模拟研究
DOI：
--
发表时间：
2007
期刊：
影响因子：
--
作者：
M. Vos;L. D. Lathauwer;B. Vanrumste;S. Huffel;W. Paesschen
通讯作者：
W. Paesschen
影响因子：
2.7
作者：
Menendez, RGD;Andino, SG;Landis, T
通讯作者：
Landis, T