北京生物医学工程

少年与中年脑电信号的多尺度符号序列熵分析

Multiscale sign series entropy analysis based on the young and middle-aged electroencephalogram

作者：杜飞王世通戴加飞侯凤贞李锦王俊

单位：<p style="white-space: normal;">南京邮电大学图像处理与图像通信江苏省实验室<p style="white-space: normal;">(南京210003)</p></p>

分类号：R318.04

出版年·卷·期（页码）：2016·35·6（599-603）

摘要：

目的脑电信号的生理分析对于评估大脑功能的活跃程度、生理状态具有重要意义，脑电图(electroencephalography, EEG)是临床检查脑部疾病的一种手段，而影响脑电图结果的因素很多，其中年龄是不容忽视的因素之一。本论文提出多尺度符号序列熵(multiscale sign series entropy, MSSE)用于分析不同年龄阶段的β波脑电信号，采用符号化的方法来处理时间序列可以去除一些细节的信息而保留感兴趣的部分。方法首先依次对4组中年和少年的β波脑电数据从数据长度N、字长m和噪声等多个角度对其符号序列熵(sign series entropy, SSE)进行分析，验证了SSE能够正确区分中年和少年的β波脑电信号。接着基于SSE算法在多个尺度下对含噪声和去噪声的中年和少年的β波脑电信号进行分析。结果随着尺度的增加，含噪声与去噪声β波脑电信号SSE的值也同步升高，并且少年的SSE均高于中年的SSE。结论脑电信号的多尺度符号熵分析方法可以有效区分少年和中年β波脑电信号，并且在信号噪声的影响下也可对不同年龄段的β波脑电信号进行检测。

Objective Electroencephalogram (EEG) is a kind of method for clinical examination of brain diseases. A lot of factors affect the EEG results and the age is one of the factors cannot be ignored. This paper presents multiscale sign series entropy (MSSE) analysis method for beta wave of EEG signal analysis of different age stages. Sign way to handling time sequence may remove certain details of the information and reserve the interested parts. Methods We first analyze the sign series entropy (SSE) from four groups of the young and middle-aged beta wave of EEG data, including multiple angles data length, word length m and noise, and verify that the SSE can correctly distinguish the young and middle-aged beta wave of EEG. Then at multiple scales, we analyze noisy EEG and denoising EEG based on SSE. Results With the increase of the scale, the values of the SSE also increase, and the SSE of the youth are higher than that of middle-aged. Conclusions namely under the MSSE can effectively distinguish young and middle-aged beta wave of EEG, and in the influence of signal noise can also be detected in different ages beta wave of EEG.

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