McSharry Patrick E, Smith Leonard A, Tarassenko Lionel
Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, UK.
IEEE Trans Biomed Eng. 2003 May;50(5):628-33. doi: 10.1109/TBME.2003.810688.
The performance of traditional linear (variance based) methods for the identification and prediction of epileptic seizures are contrasted with "modern" methods from nonlinear time series analysis. We note several flaws of design in demonstrations claiming to establish the efficacy of nonlinear techniques; in particular, we examine published evidence for precursor identification. We perform null hypothesis tests using relevant surrogate data to demonstrate that decreases in the correlation density prior to and during seizure may simply reflect increases in the variance.
将传统线性（基于方差）方法在癫痫发作识别和预测方面的表现与非线性时间序列分析中的“现代”方法进行了对比。我们注意到在声称确立非线性技术有效性的论证中存在几个设计缺陷；特别是，我们审视了已发表的关于先兆识别的证据。我们使用相关替代数据进行零假设检验，以证明癫痫发作之前及发作期间相关密度的降低可能仅仅反映了方差的增加。
