Application of Kalman Filter to Remove TMS-Induced Artifacts from EEG Recordings
Application of Kalman Filter to Remove TMS-Induced Artifacts from EEG Recordings
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DOI：
10.1109/tcst.2008.921814
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发表时间：
2008-11-01
影响因子：
4.8
通讯作者：
Rossi, Simone
中科院分区：
文献类型：
--
作者：
Morbidi, Fabio;Garulli, Andrea;Rossi, Simone
经颅磁刺激（TMS）是一种技术，其中由位于头皮旁边的线圈产生的脉冲磁场用于对大脑皮质中的神经元进行局部去极化。经颅磁刺激可以与脑电图（EEG）相结合，以可视化响应直接皮层刺激的区域大脑活动，使其成为研究大脑功能的有前途的工具。EEG/TMS共配准的技术缺点是TMS脉冲产生破坏EEG迹线的高振幅和持久伪影。在这个简短的，离线卡尔曼滤波器的方法，以消除TMS引起的伪影EEG记录。卡尔曼滤波器被施加到描述EEG和TMS信号生成的动态模型的组合所产生的线性系统。时变协方差矩阵上的问题的物理参数适当调整，使我们能够建模的EEG/TMS信号的非平稳分量，（忽略了传统的固定滤波器）。实验结果表明，该方法保证了有效的删除TMS引起的伪影，同时保持TMS脉冲周围的EEG信号的完整性。
Transcranial magnetic stimulation (TMS) is a technique in which a pulsed magnetic field created by a coil positioned next to the scalp is used to locally depolarize neurons in brain cortex. TMS can be combined with electroencephalography (EEG) to visualize regional brain activity in response to direct cortical stimulation, making it a promising tool for studying brain function. A technical drawback of EEG/TMS coregistrations is that the TMS impulse generates high amplitude and long-lasting artifacts that corrupt the EEG trace. In this brief, an offline Kalman filter approach to remove TMS-induced artifacts from EEG recordings is proposed. The Kalman filter is applied to the linear system arising from the combination of the dynamic models describing EEG and TMS signals generation. Time-varying covariance matrices suitably tuned on the physical parameters of the problem allow us to model the non-stationary components of the EEG/TMS signal, (neglected by conventional stationary filters). Experimental results show that the proposed approach guarantees an efficient deletion of TMS-induced artifacts while preserving the integrity of EEG signals around TMS impulses.