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Application of Matched-Filtering to Extract EEG Features and Decouple Signal Contributions from Multiple Seizure Foci in Brain Malformations

机译:匹配过滤在大脑畸形中从多次癫痫发作灶下提取EEG特征和解耦信号贡献

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Developmental brain malformations often cause intractable and in many cases generalized and/or multifocal seizures. Surgical intervention is not possible in these cases as it is difficult to isolate the epileptogenic foci. Scalp EEG signals recorded during such seizures include coupled contributions from different sources. If it was possible to decouple these contributions based on differences in both their signatures and inter-arrival times at different electrodes, it would subsequently be possible to estimate the locations of the seizure foci. For this purpose, we applied matched filtering to scalp EEG data from 3 patients with multifocal seizures, using patient-specific source-related short EEG segments as the template waveforms. These segments were assumed to be seizure-related based on distinct sets of inter-arrival times at different channels and alternating signal polarities. We present preliminary results and demonstrate that matched filtering can be successfully applied to extract decoupled signal components from the EEG, generated by potentially distinct sources, and thus with distinct inter-arrival times but partially overlapping spectra.
机译:发育脑畸形往往会引起棘手,并且在许多情况下是普遍的和/或多焦点癫痫发作。在这些情况下,手术干预是不可能的,因为难以分离癫痫症焦点。在此类癫痫发作期间记录的头皮EEG信号包括来自不同来源的耦合贡献。如果可以基于其签名和到达不同电极的到达时间的差异来解耦这些贡献,随后可以估计癫痫发作焦点的位置。为此目的,我们将匹配的过滤从3名多焦点癫痫发作的3例患者应用匹配的过滤,使用患者特定的源相关的短EEG段作为模板波形。假设这些段基于不同通道和交替信号极性的不同组间隔时间进行癫痫发作相关。我们提出初步结果,并证明可以成功应用匹配的滤波以从脑电图中提取来自EEG的分离信号分量,从而具有不同的到达间隔时间,而是部分重叠的光谱。

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