Original investigation correlated joint fluctuations can influence the selection of steady state gait patterns in the elderly

Benefits of nonlinear analysis indices of walking stride interval in the evaluation of neurodegenerative diseases

Indices characterising the long-range temporal structure of walking stride interval (SI) variability such as Hurst exponent (H) and fractal dimension (D) may be used in addition to indices measuring the amount of variability like the coefficient of variation (CV). We assess the added value of the former indices in a clinical neurological context. Our aim is to demonstrate that they provide a clinical significance in aging and in frequent neurodegenerative diseases such as Parkinson's disease, Huntington, and amyotrophic lateral sclerosis. Indices assessing the temporal structure of variability are mainly dependent on SI time series length and algorithms used, making quantitative comparisons between different studies difficult or even impossible. Here, we recompute these indices from available SI time series, either from our lab or from online databases. More precisely, we recompute CV, H, and D in a unified way. The average SI is also added to the measured parameters. We confirm that variability indices are relevant indicators of aging process and neurodegenerative diseases. While CV is sensitive to aging process and pathology, it does not discriminate between specific neurodegenerative diseases. H, which measures predictability of SI, significantly decreases with age but increases in patients suffering from amyotrophic lateral sclerosis. D, catching complexity of SI, is correlated with total functional capacity in patients with Huntington's disease. We conclude that the computation of H complements the clinical diagnosis of walking in patients with neurodegenerative diseases and we recommend it as a relevant supplement to classical CV or averaged SI. Since H and D indices did not lead to the same observations, suggesting the multi-fractal nature of SI dynamics, we recommend to open clinical gait analysis to the evaluation of more parameters.

Human movement variability, nonlinear dynamics, and pathology: is there a connection?

Fields studying movement generation, including robotics, psychology, cognitive science, and neuroscience utilize concepts and tools related to the pervasiveness of variability in biological systems. The concept of variability and the measures for nonlinear dynamics used to evaluate this concept open new vistas for research in movement dysfunction of many types. This review describes innovations in the exploration of variability and their potential importance in understanding human movement. Far from being a source of error, evidence supports the presence of an optimal state of variability for healthy and functional movement. This variability has a particular organization and is characterized by a chaotic structure. Deviations from this state can lead to biological systems that are either overly rigid and robotic or noisy and unstable. Both situations result in systems that are less adaptable to perturbations, such as those associated with unhealthy pathological states or absence of skillfulness.

A new approach for quantitative analysis of inter-joint coordination during gait

A new method for quantitative analysis of interjoint coordination at various walking speeds is presented. The model imposed a parametric relationship among lower limb joint motions (hips and knees) using the least number of parameters. An integration of different analysis tools such as harmonic analysis, principal component analysis, and artificial neural networks helped overcome high-dimensionality, temporal dependence, and nonlinear relationships of the gait patterns. The trained model was fed only two control parameters (cadence and stride length) for each gait cycle and predicted the corresponding gait waveforms. Based on the differences between predicted and actual gait waveforms, a coordination score, which ranged from 0 to 10, was defined at various walking speeds. The model was applied to eight patients with knee arthroplasty at different follow-ups as well as to eight healthy subjects, walking at three different speeds. The results showed that knee replacement and rehabilitation programs improved the coordination score. The technique provides an analytical tool that can be used as a routine test in the clinical evaluation of human gait abnormalities.