【摘要】 在用非线性动力学方法分析EEG信号(睡眠脑电)的过程中,由于近似熵的优点而得到了广泛的应用,但也存在着自身有偏估计、数值和信号长度有关等缺点;在此基础上提出了样品熵的概念,并尝试将样品熵用于睡眠脑电分析,结果表明,它对区分不同的睡眠阶段取得了理想的效果.更多还原

【Abstract】 it’s proved that the EEG is nonlinear. So the nonlinear dynamics was widely used in the processing of EEG signals.Espe-cial the Approximate entropy (ApEn) for its advantage compared with other method.But the Approximate entropy also has the shortcut: this method may be heavily dependent on the data length and that it lacks relative consistency and it’s inherently biased.So,sample entropy (SampEn),was introduced by Richman and Moorman. And here we use the SampEn to analysis the sleep EEG.更多还原