Dynamic stability of human walking in visually and mechanically destabilizing environments☆
Introduction
Our ability to remain stable while walking is challenged during many daily activities like walking on an uneven sidewalk, or stepping off a curb or over an obstacle. Clinically, some have measured gait variability as a possible indicator of stability. However, there is as yet no universally accepted measure to directly quantify stability in terms of how people respond to (either small or large) perturbations. Techniques from nonlinear dynamics provide direct quantitative assessments of local dynamic stability and have demonstrated measurable differences between healthy young and elderly people (Granata and Lockhart, 2008, Kang and Dingwell, 2008) and between patient populations and healthy individuals (Dingwell and Cusumano, 2000, Dingwell et al., 2007, Yakhdani et al., 2010) during unperturbed walking. However, how these measures of stability change when people are subjected to external perturbations has not yet been determined.
Floquet multipliers (FM) and local divergence exponents (LDE) have been used to assess orbital and local dynamic stability in humans during unperturbed walking (Donelan et al., 2004, Kang and Dingwell, 2006, Dingwell et al., 2008, Kang and Dingwell, 2008). FM generally indicate that humans are orbitally stable (i.e., FM<1) whereas LDE indicate that humans are locally unstable (LDE>0) during unperturbed walking (Dingwell et al., 2007). However, it is not yet known to what extent either measure can be appropriately used to assess gait. First, human gait is neither strictly periodic (a requirement of FM calculations) nor strongly aperiodic (an assumption of LDE calculations). Second, FM and LDE are strictly defined only for deterministic systems and all biological systems are inherently stochastic. However, the finite-time modifications used to calculate FM and LDE do provide reasonable estimates of the stability of human walking even in the presence of these limitations. It is yet to be determined if these measures of stability can quantify changes in stability within a given individual, such as may be experienced with aging or when exposed to a challenging ambulatory environment.
Virtual reality (VR) systems provide a safe environment in which to apply perturbations during human gait, but still allow for a variety of types of perturbations to be applied (e.g., visual or somatosensory, in particular directions, etc). Changing aspects of the VR environment such as the angle of visual projection or optical flow speed can induce gait characteristics that are generally associated with more cautious walking, such as shorter and wider steps (Nyberg et al., 2006, Hollman et al., 2007, Lamontagne et al., 2007). These studies indicate the promise of using VR as a tool for studying changes in dynamic stability during perturbed gait. Recently, O'Connor and Kuo (2009) exposed subjects to sinusoidal oscillations of the visual scene and found that subjects were more sensitive in the ML than the AP direction during walking. Their study focused on changes in variability rather than direct measures of dynamic stability and left open the question of how stability measures change when humans are exposed to similar perturbations during walking.
We recently exposed individuals to continuous pseudo-random oscillations of either the visual scene or support surface in a virtual environment with speed appropriate optical flow. We knew these oscillations would make our subjects qualitatively more unstable. This was confirmed by the fact that when our subjects were exposed to these perturbing environments, they exhibited “cautious” gait characteristics, like taking shorter and wider steps. They also exhibited increased movement variability (McAndrew et al., 2010). Our purpose here was to determine if these same qualitatively destabilizing oscillations could also evoke measureable changes in dynamic stability, as quantified by Floquet multipliers and local divergence exponents, during walking. We hypothesized that participants would be: (1) more dynamically unstable when walking during continuous, pseudo-random perturbations than without and (2) more dynamically unstable during mediolateral (ML) than during anterior–posterior (AP) perturbations.
Section snippets
Methods
A complete description of our experiment is given in McAndrew et al. (2010). In brief, we collected data on 12 healthy young adults walking in a Computer Assisted Rehabilitation ENvironment (CAREN) system (Motek, Amsterdam, Netherlands). While walking, participants were exposed to continuous, pseudo-random oscillations of the support surface or visual field. The 5 experimental conditions consisted of unperturbed walking (NOP), anterior–posterior platform (APP) or visual (APV) oscillations, and
Results
Subjects' C7 movements in the AP direction were orbitally more unstable during AP perturbations than during the NOP condition (p<0.001; Fig. 1 Left). There were no significant changes in orbital stability during the ML perturbations relative to NOP (p=0.963 for MLP; p=1.000 for MLV). APP perturbations caused the greatest increases in maxFM relative to all other conditions (p<0.001). Subjects' C7 movements in the ML direction were orbitally more unstable during the ML perturbations than during
Discussion
Understanding how humans remain stable during challenging locomotor activities is critical to developing effective tests to diagnose patients with increased fall risk. Imposing carefully structured locomotor challenges in contexts like virtual environments may also provide effective training interventions to reduce fall risk in these patients. The purpose of this study was to determine if exposing subjects to different types of continuous pseudo-random perturbations which destabilized their
Conflict of interest statement
The authors declare that there is no conflict of interest associated with this work.
Acknowledgements
Support provided by the Military Amputee Research Program (to JMW) and by National Institutes of Health Grants 1-R21-EB007638 and 1-R01-HD059844 (to JBD).
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