Wavelet analysis of epileptic spikes
Wavelet analysis of epileptic spikes
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DOI：
10.1103/physreve.67.052902
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发表时间：
2003-05-01
影响因子：
2.4
通讯作者：
West, BJ
中科院分区：
文献类型：
--
作者：
Latka, M;Was, Z;West, BJ
人类脑电图的发作间期尖峰和尖波是癫痫的特征特征。这些电位源于许多神经元同步病理放电的结果。可靠地检测这种电位一直是脑电图分析中长期存在的问题，特别是在长期监测在癫痫患者的研究中变得普遍之后。尖峰的传统定义是基于其幅度、持续时间、锐度以及从背景中的出现。然而，由于存在大量瞬变和伪影，仅围绕此定义构建的尖峰检测系统并不可靠。我们使用小波变换来分析癫痫的脑电图表现特征。我们证明，癫痫尖峰跨尺度的小波变换行为可以构成相对简单但有效的检测算法的基础。
Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.