Publication details

Complexity and information-based analysis of th electroencephalogram (EEG) signals in standing, walking, and walking with a brain-computer interface


RAMADOSS Janarthanan DAWI Norazryana Mat RAJAGOPAL Karthikeyan NAMAZI Hamidreza

Year of publication 2022
Type Article in Periodical
Magazine / Source Fractals
MU Faculty or unit

Faculty of Sports Studies

Keywords EEG Signals; Complexity; Information; Fractal Theory; Shannon Entropy
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Description In this paper, we analyzed the variations in brain activation between different activities. SinceElectroencephalogram (EEG) signals as an indicator of brain activation contain information andhave complex structures, we employed complexityand information-based analysis. Specifically,we used fractal theory and Shannon entropy for our analysis. Eight subjects performed threedifferent activities (standing, walking, and walking with a brain–computer interface) whiletheir EEG signals were recorded. Based on the results, the complexity and information contentof EEG signals have the greatest and smallest values in walking and standing, respectively.Complexity and information-based analysis can be applied to analyze the activations of otherorgans in different conditions.

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