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Complexity-Based Analysis of the Variations of Brain and Muscle Reactions in Walking and Standing Balance While Receiving Different Perturbations

Najmeh Pakniyat, Hamidreza Namazi

2021Frontiers in Human Neuroscience18 citationsDOIOpen Access PDF

Abstract

In this article, we evaluated the variations of the brain and muscle activations while subjects are exposed to different perturbations to walking and standing balance. Since EEG and EMG signals have complex structures, we utilized the complexity-based analysis. Specifically, we analyzed the fractal dimension and sample entropy of Electroencephalogram (EEG) and Electromyogram (EMG) signals while subjects walked and stood, and received different perturbations in the form of pulling and rotation (via virtual reality). The results showed that the complexity of EEG signals was higher in walking than standing as the result of different perturbations. However, the complexity of EMG signals was higher in standing than walking as the result of different perturbations. Therefore, the alterations in the complexity of EEG and EMG signals are inversely correlated. This analysis could be extended to investigate simultaneous variations of rhythmic patterns of other physiological signals while subjects perform different activities.

Topics & Concepts

Sample entropyElectroencephalographyRecurrence quantification analysisBalance (ability)Approximate entropyRhythmLeg musclePhysical medicine and rehabilitationComputer scienceElectromyographyPattern recognition (psychology)NeurosciencePsychologyArtificial intelligenceSpeech recognitionMedicinePhysicsAcousticsNonlinear systemQuantum mechanicsEEG and Brain-Computer InterfacesFractal and DNA sequence analysisNeural dynamics and brain function