Analysis of epileptic EEG signals using higher order spectra
Analysis of epileptic EEG signals using higher order spectra
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DOI：
10.1080/03091900701559408
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发表时间：
2009-01-01
影响因子：
--
通讯作者：
Lim, C. M.
中科院分区：
文献类型：
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作者：
Chua, K. C.;Chandran, V.;Lim, C. M.
癫痫发作发生的不可预测性在很大程度上增加了疾病的负担。检测癫痫发作的自动系统将使患者或他们附近的人采取适当的预防措施，并可以提供更多的洞察这些现象，从而揭示重要的临床信息。因此，已经提出了基于EEG记录来预测癫痫发作的各种方法。一个看似有前途的方法涉及高阶光谱（HOS）激发的非线性特征。本文的目的是找到不同的HOS功能正常，发作前（背景）和癫痫脑电信号。这可能有助于以最大的准确性尽早检测癫痫发作。在这项工作中，300 EEG数据，每个属于三类，进行了研究。我们的研究结果表明，基于HOS的措施显示出独特的范围为不同的类与高置信水平（p=0.002）。
The unpredictability of the occurrence of epileptic seizures contributes to the burden of the disease to a major degree. An automatic system that detects seizure onsets would allow patients or the people near them to take appropriate precautions, and could provide more insight into these phenomena, thereby revealing important clinical information. Thus, various methods have been proposed to predict the onset of seizures based on EEG recordings. A seemingly promising approach involves nonlinear features motivated by the higher order spectra (HOS). The goal in this paper is to find the different HOS features for normal, pre-ictal (background) and epileptic EEG signals. This may help in the detection of seizure onset as early as possible with maximal accuracy. In this work, 300 EEG data, each belonging to the three classes, are studied. Our results show that the HOS based measures show unique ranges for the different classes with high confidence level (p=0.002).