Abstract
By restricting analysis to single averaged strides considered to be characteristic for the individual under investigation, current methods in gait analysis do not exploit the full dynamics of continuous locomotion. Therefore, a novel approach is presented that is based on long-term measurements of kinematic data during treadmill walking. The method consists of reconstructing the system attractor in the embedding space and then analyzing its geometric structure. Estimating the dimension of movement trajectories correlates well with the notion of controlling multiple degrees of freedom during performance of complex movement tasks such as walking. The influence of walking speed on the complexity of physiologic walking was investigated in 10 healthy subjects walking on a treadmill at seven fixed speeds. The results suggest that human walking becomes more complex at slower speeds. This may be associated with results from EMG studies demonstrating more irregular EMG patterns at very slow walking speeds. This study emphasizes that tools from non-linear dynamics are well suited for providing more insight into motor control in humans.
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