基于复杂性度量的大脑警觉度分析

Brain Vigilance Analysis Based on the Measure of Complexity

警觉度是人在一段时间里保持持续注意力的能力。为了探求在工作过程中警觉度随时间的变化规律,本文设计了以三位数加减法来诱导警觉度发生变化的实验,并通过警觉度任务(PVT)实验结合脑电测量该变化过程,提取并分析了11例受试者脑电信号排列熵(PE)这一复杂性度量,并与非线性参数样本熵(SE)做了简要比较。实验结果表明:该算法可以很好地反映警觉度下降时脑电信号的动态变化过程,且运算速度快,抗噪能力强,对脑电信号长度要求低,可以作为衡量大脑警觉度的指标。

Vigilance is defined as the ability to maintain attention for prolonged periods of time. In order to explore the variation of brain vigilance in work process, we designed addition and subtraction experiment with numbers of three digits to induce the vigilance to change, combined it with psychomotor vigilance task （PVT） to measure this process of electroencephalogram （EEG）, extracted and analyzed permutation entropy （PE） of 11 cases of subjects＇ EEG and made a brief comparison with nonlinear parameter sample entropy （SE）. The experimental results showed that： PE could well reflect the dynamic changes of EEG when vigilance decreases, and has advantages of fast arithmetic speed, high noise immunity, and low requirements for EEG length. This can be used as a measure of the brain vigilance indicators.