The performance of the spatiotemporal Kalman filter and LORETA in seizure onset localization
The performance of the spatiotemporal Kalman filter and LORETA in seizure onset localization
复制标题
时空卡尔曼滤波器和 LORETA 在癫痫发作定位中的性能
DOI：
10.1109/embc.2015.7318959
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
M. Siniatchkin
中科院分区：
文献类型：
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作者：
L. Hamid;M. Sarabi;N. Japaridze;G. Wiegand;U. Heute;U. Stephani;A. Galka;M. Siniatchkin
在脑电图（EEG）源成像过程中，例如在低分辨率电磁断层扫描（LORETA）中，经常使用空间平滑假设来解决生物电逆问题。由于脑电数据具有时间结构，将时间平滑约束和空间平滑约束相结合可以改善脑电反演问题的求解。本文研究了基于空间和时间平滑的时空卡尔曼滤波（STKF）方法在局灶性癫痫发作定位中的性能，并将其结果与LORETA进行了比较。本研究的主要发现是，当源空间由全脑体积网格组成时，具有二阶自回归模型的STKF在定位的准确性和一致性方面明显优于LORETA。在未来，这些有希望的结果将通过更多患者的数据得到证实，并对结果进行统计分析。此外，将使用不同类型的局灶性癫痫来研究时间平滑约束的影响。
The assumption of spatial-smoothness is often used to solve the bioelectric inverse problem during electroencephalographic (EEG) source imaging, e.g., in low resolution electromagnetic tomography (LORETA). Since the EEG data show a temporal structure, the combination of the temporal-smoothness and the spatial-smoothness constraints may improve the solution of the EEG inverse problem. This study investigates the performance of the spatiotemporal Kalman filter (STKF) method, which is based on spatial and temporal smoothness, in the localization of a focal seizure's onset and compares its results to those of LORETA. The main finding of the study was that the STKF with an autoregressive model of order two significantly outperformed LORETA in the accuracy and consistency of the localization, provided that the source space consists of a whole-brain volumetric grid. In the future, these promising results will be confirmed using data from more patients and performing statistical analyses on the results. Furthermore, the effects of the temporal smoothness constraint will be studied using different types of focal seizures.
DOI：
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发表时间：
2005
期刊：
影响因子：
--
作者：
R. Pascual
通讯作者：
R. Pascual