J 2021

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

PAKNIYAD, Najmeh and Hamidreza NAMAZI

Basic information

Original name

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

Authors

PAKNIYAD, Najmeh (364 Islamic Republic of Iran) and Hamidreza NAMAZI (364 Islamic Republic of Iran, guarantor, belonging to the institution)

Edition

Frontiers in Human Neuroscience, Lausanne (Schwitzerland), FRONTIERS MEDIA SA, 2021, 1662-5161

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

30306 Sport and fitness sciences

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 3.473

RIV identification code

RIV/00216224:14510/21:00122673

Organization unit

Faculty of Sports Studies

DOI

UT WoS

000710920900001

Keywords in English

muscle; brain; EEG signals; EMG signals; complexity; walking; standing; perturbations

Tags

Tags

International impact, Reviewed
Změněno: 21/4/2022 15:09, Mgr. Pavlína Roučová, DiS.

Abstract

V originále

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.