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Multifractal Complexity Analysis of Electroencephalography (EEG) Signals and Kinematic Dynamics During Walking | ||
| Journal of Advanced Sport Technology | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 03 آذر 1404 | ||
| نوع مقاله: Original research papers | ||
| شناسه دیجیتال (DOI): 10.22098/jast.2025.18618.1444 | ||
| نویسندگان | ||
| Mehrdad Anbarian* ؛ Ruhollah Basatnia | ||
| Department of Sports Biomechanics, Faculty of Sports Sciences, Bu-Ali Sina University, Hamedan, Iran. | ||
| چکیده | ||
| Walking, as a complex motor activity, requires precise coordination within the neuromuscular system. This study aimed to analyze the multiscale complexity of electroencephalography (EEG) signals and kinematic data during walking to investigate brain-lower limb interactions. Thirteen male participants walked on a treadmill under controlled conditions, during which EEG signals and kinematic data were recorded. Multifractal complexity analysis using the multifractal detrended fluctuation analysis (MF-DFA) method was applied to the data to extract the Hurst exponent as a complexity index for dynamic features of movements in displacement dimensions along three axes (X, Y, Z) and cortical activity in motor brain regions (C3 and C4) during walking. Results indicated that the generalized Hurst exponent H(q) in the C3 and C4 regions was similar and exhibited a significant positive correlation with the same parameter in the dynamics of the contralateral limb, supporting the principle of interhemispheric control. Segmental analysis of the thigh, shank, and foot revealed substantial dynamic symmetry between the right and left sides. The multifractal patterns of the segments demonstrated significant differences, with the highest H(q) in the shank and the lowest in the thigh. Strong intra-system coordination among segments suggests an integrated organization in motor control. These findings confirm neuromuscular symmetry and coordination, provide utility for assessing motor disorders and designing rehabilitation protocols, and underscore the importance of multiscale analysis in elucidating complex brain-body interactions, with potential applications in neuroscience, biomechanics, and rehabilitation research. | ||
| کلیدواژهها | ||
| Walking؛ EEG signals؛ kinematic data؛ multifractal analysis؛ Hurst exponent | ||
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آمار تعداد مشاهده مقاله: 52 |
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