Energy Distribution Evaluation Using Renyi Entropy Measures With Application in EEG Data Analysis

T. Popescu
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Abstract

The ”corrected” EEG recordings, after artifact removing, may be the subject of further investigations, for example segmentation and energy distribution, resulting new informa- tion to be used for feature extraction, of great help for medical diagnosis. The paper presents a generally method for energy distribution evalua- tion using measures of R´enyi entropy. The pre- sented approach ensures the possibility of quan- titative analysis of the information contained in time-frequency distribution of EEG signals. The proposed procedure is applied with good results in the analysis of a sample lowpass event-related potentials (ERP) data, collected from 13 scalp and 1 EOG electrodes.
基于人益熵的能量分布评价及其在脑电数据分析中的应用
“校正”后的脑电图记录,在去除伪影后,可能成为进一步研究的主题,例如分割和能量分布,从而产生新的信息用于特征提取,对医学诊断有很大帮助。本文提出了一种利用R´enyi熵测度评价能量分布的一般方法。该方法保证了对脑电信号时频分布所含信息进行定量分析的可能性。该方法在分析13个头皮电极和1个EOG电极的低通事件相关电位(ERP)数据中取得了良好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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