Examination of time-varying kinematic responses to support surface disturbances

Abstract

Abstract:To examine the evolution of inter-segmental coordination over time, a previously developed multi-variate model of postural coordination during quiet stance (Kuo et al. 1998) has been extended. In the original model, postural coordination was treated as an eigenvalue-eigenvector problem between two segmental degrees of freedom represented by angular displacements of the trunk and lower limb. Strategies of postural coordination were then identified using the sign of the covariance between the two segments' angular displacements. In contrast to the original model, the current model first subdivided the entire trial into smaller time segments, comprising four cycles of perturbation, i.e., a 16 sec window. This window marched along the data advancing in 8.3 ms steps, each time performing the computation from the original model on the terms of the covariance matrix. The resulting time-segment-dependent postural strategies estimated the changes in posture control that took place over the course of the experiment. In addition to the statistical modeling, the auto-power spectrums and cross-spectral density function estimates for the entire trial, as well as for the individual time-segments, were analyzed. In these experiments subjects experienced a 0.25 Hz sinusoidal perturbation of a platform while exposed to a virtual reality environment. The data we collected showed that the statistical and spectral characteristics across the entire trial may differ from individual time segments of the same trial indicating time varying postural behavior. Comparison of these results from young and elderly subjects revealed that the time dependency observed in postural behavior was sensitive to aging. The young population managed to be consistent in their postural behavior throughout the entire trial and responded to the perturbation frequency with an out-of-phase response between the postural segments. Elderly subjects, however, demonstrated inconsistent postural behaviors as they switched back and forth between different postural coordination patterns within a trial.

Balance control strategies during perturbed and unperturbed balance in standing and handstand

“…Time-frequency analysis of centre of pressure motion during unperturbed stance has revealed that human balance is non-stationary with time-varying properties [ 15 , 16 ]. Gurses et al [ 17 ] examined the evolution of intersegmental coordination over time, adapting the model of Kuo et al [ 18 ] by dividing trials into overlapping time segments of 16 s duration. Results indicated statistical and spectral characteristics across the entire trial can differ from individual time segments of the same trial displaying time-varying intersegmental coordination behaviours [ 17 ].…”

“…Gurses et al [ 17 ] examined the evolution of intersegmental coordination over time, adapting the model of Kuo et al [ 18 ] by dividing trials into overlapping time segments of 16 s duration. Results indicated statistical and spectral characteristics across the entire trial can differ from individual time segments of the same trial displaying time-varying intersegmental coordination behaviours [ 17 ]. Employing stationary-based data analysis techniques to non-stationary balance or coordination data will result in misrepresentations of the full temporal characteristics of postural control.…”

Delayed Center of Mass Feedback in Elderly Humans Leads to Greater Muscle Co-Contraction and Altered Balance Strategy under Perturbed Balance: a Predictive Musculoskeletal Simulation Study

“…This might explain the heightened ankle strategy use in longer delays, reflecting Versteeg et al's findings. In a 2011 study by Gurses et al [63], the authors compared balance strategies of young adults vs elderly for different frequencies of perturbation and found that young adults predominantly used hip strategy, whereas elderly individuals employed a mix of hip and ankle strategies used by elderly. This implies an age-related shift towards ankle strategy in response to perturbations.…”

“…This might explain the heightened ankle strategy use in longer delays, reflecting Versteeg et al's findings. In a 2011 study by Gurses et al[63], that ankle strategy dominated when perturbance frequency was below 2.11 Hz.…”

Developing a Human Balance Test System (DETES) in Order to Investigate Control Mechanisms of Human Erect Posture

“…Data analyses from CoP signal (basic measurement for estimating human balance in quasi static and dynamic conditions, which is derived from kinetic outputs) is performed at time and frequency domains [17]. Figures 4a and b show exemplar CoP x and CoP y time signals of an healthy subject collected at quiet stance and their related Fast Fouriér Transformations (FFT, see below paragraph for an explanation/ implication of FFT, Figures 4c and d).…”