Fractal-Based EEG Data Analysis of Body Parts Movement Imagery Tasks

The Journal of Physiological Sciences

Montri Phothisonothai¹  Masahiro Nakagawa¹ 

[1] Chaos and Fractals Informatics Laboratory, Nagaoka University of Technology

关键词: fractal dimension;    electroencephalogram (EEG);    brain wave;    mental tasks;    motor imagery task;    EEG data analysis;   

DOI  :  10.2170/physiolsci.RP006307

学科分类：生理学

来源: Springer

【 摘 要 】

References(37)Cited-By(7)The objective of this study is to analyze the spontaneous electroencephalographic (EEG) data corresponding to body parts movement imagery tasks in terms of fractal properties. We proposed the six algorithms of fractal dimension (FD) estimators; box-counting algorithm, Higuchi algorithm, variance fractal algorithm, detrended fluctuation analysis, power spectral density analysis, and critical exponent analysis. The different parts of human body movement imagination such as feet, tongue, and index finger are proposed for use as the tasks in this experiment. The EEG data were recorded from three healthy subjects (2 males and 1 female). The experimental results are useful in the measurement of FD changes in EEG data and present different characteristics in terms of variability. The probability density function (PDF) is also applied to show that the FD distribution is along each electrode. This study proposes that the performances of each method can extract information from the EEG data of imagined movement.

【 授权许可】

Unknown