Background: For an individual to walk, they must maintain control of their dynamic balance. However, situations that present an increased cognitive load may impair an individual's ability to control their balance. While dual-task studies have analyzed walking-while-talking conditions, few studies have focused specifically on the influence of cognitive load on balance control. The purpose of this study was to assess how individuals prioritize their cognitive resources and control dynamic balance during dual-task conditions of varying difficulty.Methods: Young healthy adults (n = 15) performed two single-task conditions (spelling while standing and walking with no cognitive load) and three dual-task conditions (walking with increasing cognitive load: attentive listening, spelling short words backwards and spelling long words backwards). Repeated measures analysis of variances were used to assess differences in balance outcome measures and cognitive performance.Results: Cognitive performance did not change between the single-and dual-task conditions as measured by percent error and response rate (p = 0.3). Balance control, assessed as the range of whole-body angular momentum, did not change between the no load and listening conditions, but decreased during the short and long spelling conditions (p < 0.001).Conclusions: These results showed that balance control decreases during dual-task treadmill walking with increased cognitive loads, but that cognitive performance does not change. The decrease in balance control suggests that participants prioritized cognitive performance over balance control during these dual-task walking conditions. This work offers additional insight into the automaticity of walking and task-prioritization in healthy individuals and provides the basis for future studies to determine differences in neurologically impaired populations.

No abstract

No abstract

Studies of active matter—systems consisting of individuals or ensembles of internally driven and damped locomotors—are of interest to physicists studying nonequilibrium dynamics, biologists interested in individuals and swarm locomotion, and engineers designing robot controllers. While principles governing active systems on hard ground or within fluids are well studied, another class of systems exists at deformable interfaces. Such environments can display mixes of fluid-like and elastic features, leading to locomotor dynamics that are strongly influenced by the geometry of the surface, which, in itself, can be a dynamical entity. To gain insight into principles by which locomotors are influenced via a deformation field alone (and can influence other locomotors), we study robot locomotion on an elastic membrane, which we propose as a model of active systems on highly deformable interfaces. As our active agent, we use a differential driven wheeled robotic vehicle which drives straight on flat homogeneous surfaces, but reorients in response to environmental curvature. We monitor the curvature field–mediated dynamics of a single vehicle interacting with a fixed deformation as well as multiple vehicles interacting with each other via local deformations. Single vehicles display precessing orbits in centrally deformed environments, while multiple vehicles influence each other by local deformation fields. The active nature of the system facilitates a differential geometry–inspired mathematical mapping from the vehicle dynamics to those of test particles in a fictitious “spacetime,” allowing further understanding of the dynamics and how to control agent interactions to facilitate or avoid multivehicle membrane-induced cohesion.