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利用伽柏原子密度对癫痫发作动力学进行表征。

Characterization of epileptic seizure dynamics using Gabor atom density.

作者信息

Jouny Christophe C, Franaszczuk Piotr J, Bergey Gregory K

机构信息

Department of Neurology, Johns Hopkins Epilepsy Center, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Meyer 2-147, Baltimore, MD 21287, USA.

出版信息

Clin Neurophysiol. 2003 Mar;114(3):426-37. doi: 10.1016/s1388-2457(02)00344-9.

Abstract

OBJECTIVE

The study of epileptic electroencephalograph (EEG) dynamics can potentially provide insights into seizure onset, evolution and termination. We propose a new synthetic measure based on time-frequency decomposition to provide detailed characterization of these dynamic changes.

METHODS

The matching pursuit (MP) method allows for continuous time-frequency decomposition. We have developed a derivative of the MP method, the Gabor atom density method (GAD) that facilitates interpretation during the dynamic ictal period. The GAD analysis was applied to intracranial recordings of complex partial seizures (n = 43) of mesial temporal origin in 7 patients.

RESULTS

Complex partial seizure occurrence is systematically associated with a GAD increase of 400 +/- 150%. The GAD increase coincides with the electrographical evidence of seizure onset. The similarity between seizures in a given patient is very high with uniform onset slope, maximum level and termination pattern. Global GAD responses over all channels can reveal detailed seizure propagation patterns including secondary independent foci and secondary generalization.

CONCLUSIONS

The GAD measure based on the MP decomposition is a reliable tool to detect seizure occurrence in long-term recordings, to differentiate seizures from artifacts on a multi-channel basis and to examine patterns of seizure propagation. The reproducible GAD pattern suggests consistent changes in signal inner structure and may provide new clues about seizure dynamics and evolution.

SIGNIFICANCE

The GAD method can provide information about seizure dynamics that can contribute to methods of seizure detection. These analyses may lead to better understanding of seizure termination and help facilitate application of responsive seizure control devices in humans.

摘要

目的

对癫痫脑电图(EEG)动力学的研究可能为癫痫发作的起始、演变和终止提供见解。我们提出一种基于时频分解的新综合测量方法,以详细描述这些动态变化。

方法

匹配追踪(MP)方法可实现连续时频分解。我们开发了MP方法的一种衍生方法,即加博尔原子密度方法(GAD),它有助于在动态发作期进行解释。GAD分析应用于7例患者内侧颞叶起源的复杂部分性发作(n = 43)的颅内记录。

结果

复杂部分性发作的发生与GAD增加400±150%有系统性关联。GAD增加与癫痫发作起始的电描记证据相一致。给定患者癫痫发作之间的相似性非常高,具有一致的起始斜率、最大水平和终止模式。所有通道上的整体GAD反应可揭示详细的癫痫发作传播模式,包括继发性独立病灶和继发性泛化。

结论

基于MP分解的GAD测量是一种可靠的工具,可用于在长期记录中检测癫痫发作,在多通道基础上区分癫痫发作与伪迹,并检查癫痫发作传播模式。可重复的GAD模式表明信号内部结构存在一致变化,可能为癫痫发作动力学和演变提供新线索。

意义

GAD方法可提供有关癫痫发作动力学的信息,有助于癫痫发作检测方法。这些分析可能有助于更好地理解癫痫发作终止,并有助于促进响应性癫痫控制设备在人体中的应用。

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