Multimodal Neuro-Biomechanical Signatures of Walking Speed in Healthy Adults

Walking speed alters both neural control and mechanical demands, yet these responses are often investigated independently, limiting understanding of their coordinated role in human locomotion. This study presents a multimodal neuro-biomechanical framework to characterize speed-dependent adaptations in healthy young adults by integrating electroencephalographic activity, muscle activation, lower-limb kinematics, and force-plate measurements. Data from ۵۹ participants walking on a treadmill at ۰.۵۰, ۰.۷۵, and ۱.۰۰ meters per second were analyzed using a within-subject repeated-measures design. Electroencephalographic signals were subjected to artifact-aware quality control and spectral analysis using absolute and relative power in the delta, theta, alpha, and beta bands. Muscle activity was quantified from mean absolute value electromyographic signals, while gait events, ground-reaction-force parameters, center-of-pressure measures, and joint-motion features were extracted from force-plate and inertial data. Increasing walking speed produced marked biomechanical adaptations, including an approximately ۹۱ percent increase in loading rate, a ۲۶ percent reduction in vertical impulse, and a ۲۴ percent increase in center-of-pressure path length. Tibialis anterior activation increased by approximately ۳۸ percent. Although absolute electroencephalographic power increased across all frequency bands, relative beta power decreased by approximately ۱۳ percent, indicating that broadband power elevation and frequency-specific redistribution should be interpreted separately. Phase-resolved analysis further suggested stronger beta modulation during early stance and push-off at higher speeds. Cross-domain associations between neural, muscular, and mechanical changes did not remain significant after correction for multiple comparisons. Overall, the findings demonstrate that walking speed induces concurrent but partially independent adaptations across neural, muscular, and biomechanical systems, supporting the value of multimodal assessment for a more comprehensive interpretation of human gait control.

کلیدواژه ها:

EEG ، EMG ، Gait Biomechanics ، Walking Speed ، Multimodal Sensing