A model of task-level human stepping regulation yields semistable walking.

A simple lateral dynamic walker, with swing leg dynamics and three adjustable input parameters, is used to study how motor regulation affects frontal plane stepping. Motivated by experimental observations and phenomenological models, we imposed task-level multiobjective regulation targeting the walker's optimal lateral foot placement at each step. The regulator prioritizes achieving step width and lateral body position goals to varying degrees by choosing a mixture parameter. Our model thus integrates a lateral mechanical template, which captures fundamental mechanics of frontal-plane walking, with a lateral motor regulation template, an empirically verified model of how humans manipulate lateral foot placements in a goal-directed manner. The model captures experimentally observed stepping fluctuation statistics and demonstrates how linear empirical models of stepping dynamics can emerge from first-principles nonlinear mechanics. We find that task-level regulation gives rise to a goal equivalent manifold in the system's extended state space of mechanical states and inputs, a subset of which contains a continuum of period-1 gaits forming a semistable set: perturbations off of any of its gaits result in transients that return to the set, though typically to different gaits.

How older adults maintain lateral balance while walking on narrowing paths.

BACKGROUND: Older adults have difficulty maintaining side-to-side balance while navigating daily environments. Losing balance in such circumstances can lead to falls. We need to better understand how older adults adapt lateral balance to navigate environment-imposed task constraints. RESEARCH QUESTION: How do older adults adjust mediolateral balance while walking along continually-narrowing paths, and what are the stability implications of these adjustments? METHODS: Eighteen older (71.6±6.0 years) and twenty younger (21.7±2.6 years) healthy adults traversed 25 m-long paths that gradually narrowed from 45 cm to 5 cm. Participants switched onto an adjacent path when they chose. We quantified participants' lateral center-of-mass dynamics and lateral Margins of Stability (MoSL) as paths narrowed. We quantified lateral Probability of Instability (PoIL) as the probability that participants would take a laterally unstable (MoSL<0) step as they walked. We also extracted these outcomes where participants switched paths. RESULTS: As paths narrowed, all participants exhibited progressively smaller average MoSL and increasingly larger PoIL. However, their MoSL variability was largest at both the narrowest and widest path sections. Older adults exhibited consistently both larger average and more variable MoSL across path widths. Taken into account together, these resulted in either comparable or somewhat larger PoIL as paths narrowed. Older adults left the narrowing paths sooner, on average, than younger. As they did so, older adults exhibited significantly larger average and more variable MoSL, but somewhat smaller PoIL than younger. SIGNIFICANCE: Our results directly challenge the predominant interpretation that larger average MoSL indicate "greater stability", which we argue is inconsistent with the principles underlying its derivation. In contrast, analyzing step-to-step gait dynamics, together with estimating PoIL allows one to properly quantify instability risk. Furthermore, the adaptive strategies uncovered using these methods suggest potential targets for future interventions to reduce falls in older adults.

How Healthy Older Adults Enact Lateral Maneuvers While Walking.

BACKGROUND: Walking requires frequent maneuvers to navigate changing environments with shifting goals. Humans accomplish maneuvers and simultaneously maintain balance primarily by modulating their foot placement, but a direct trade-off between these two objectives has been proposed. As older adults may rely more on foot placement to maintain lateral balance, they may be less able to adequately adapt stepping to perform lateral maneuvers. RESEARCH QUESTION: How do older adults adapt stepping to enact lateral lane-change maneuvers, and how do physical and perceived ability influence their task performance? METHODS: Twenty young (21.7 ± 2.6 yrs) and 18 older (71.6 ± 6.0 yrs) adults walked on a motorized treadmill in a virtual environment. Following an audible and visual cue, participants switched between two parallel paths, centered 0.6 m apart, to continue walking on their new path. We quantified when participants initiated the maneuver following the cue, as well as their step width, lateral position, and stepping variability ellipses at each maneuver step. RESULTS: Young and older adults did not differ in when they initiated the maneuver, but participants with lower perceived ability took longer to do so. Young and older adults also did not exhibit differences in step width or lateral positions at any maneuver step, but participants with greater physical ability reached their new path faster. While only older adults exhibited stepping adaptations prior to initiating the maneuver, both groups traded off stability for maneuverability to enact the lateral maneuver. SIGNIFICANCE: Physical and perceived balance ability, rather than age per se, differentially influenced maneuver task performance. Humans must make decisions related to the task of walking itself and do so based on both physical and perceived factors. Understanding and targeting these interactions may help improve walking performance among older adults.

How older adults regulate lateral stepping on narrowing walking paths.

Walking humans often navigate complex, varying walking paths. To reduce falls, we must first determine how older adults purposefully vary their steps in contexts that challenge balance. Here, 20 young (21.7±2.6 yrs) and 18 older (71.6±6.0 yrs) healthy adults walked on virtual paths that slowly narrowed (from 45 cm to as narrow as 5 cm). Participants could switch onto an "easier" path whenever they chose. We applied our Goal Equivalent Manifold framework to quantify how participants adjusted their lateral stepping variability and step-to-step corrections of step width and lateral position as these paths narrowed. We also extracted these characteristics at the locations where participants switched paths. As paths narrowed, all participants reduced their lateral stepping variability, but older adults less so. To stay on the narrowing paths, young adults increasingly corrected step-to-step deviations in lateral position more, by correcting step-to-step deviations in step width less. Conversely, as older adults also increasingly corrected lateral position deviations, they did so without sacrificing correcting step-to-step deviations in step width, presumably to preserve balance. While older adults left the narrowing paths sooner, several of their lateral stepping characteristics remained similar to those of younger adults. Older adults largely maintained overall walking performance per se, but they did so by changing how they balanced the competing stepping regulation requirements intrinsic to the task: maintaining position vs. step width. Thus, balancing how to achieve multiple concurrent stepping goals while walking provides older adults the flexibility they need to appropriately adapt their stepping on continuously narrowing walking paths.

Generalizing stepping concepts to non-straight walking.

People rarely walk in straight lines. Instead, we make frequent turns or other maneuvers. Spatiotemporal parameters fundamentally characterize gait. For straight walking, these parameters are well-defined for the task of walking on a straight path. Generalizing these concepts to non-straight walking, however, is not straightforward. People follow non-straight paths imposed by their environment (sidewalk, windy hiking trail, etc.) or choose readily-predictable, stereotypical paths of their own. People actively maintain lateral position to stay on their path and readily adapt their stepping when their path changes. We therefore propose a conceptually coherent convention that defines step lengths and widths relative to predefined walking paths. Our convention simply re-aligns lab-based coordinates to be tangent to a walker's path at the mid-point between the two footsteps that define each step. We hypothesized this would yield results both more correct and more consistent with notions from straight walking. We defined several common non-straight walking tasks: single turns, lateral lane changes, walking on circular paths, and walking on arbitrary curvilinear paths. For each, we simulated idealized step sequences denoting "perfect" performance with known constant step lengths and widths. We compared results to path-independent alternatives. For each, we directly quantified accuracy relative to known true values. Results strongly confirmed our hypothesis. Our convention returned vastly smaller errors and introduced no artificial stepping asymmetries across all tasks. All results for our convention rationally generalized concepts from straight walking. Taking walking paths explicitly into account as important task goals themselves thus resolves conceptual ambiguities of prior approaches.

Generalizing Stepping Concepts To Non-Straight Walking.

People rarely walk in straight lines. Instead, we make frequent turns or other maneuvers. Spatiotemporal parameters fundamentally characterize gait. For straight walking, these parameters are well-defined for that task of walking on a straight path. Generalizing these concepts to non-straight walking, however, is not straightforward. People also follow non-straight paths imposed by their environment (store aisle, sidewalk, etc.) or choose readily-predictable, stereotypical paths of their own. People actively maintain lateral position to stay on their path and readily adapt their stepping when their path changes. We therefore propose a conceptually coherent convention that defines step lengths and widths relative to known walking paths. Our convention simply re-aligns lab-based coordinates to be tangent to a walker's path at the mid-point between the two footsteps that define each step. We hypothesized this would yield results both more correct and more consistent with notions from straight walking. We defined several common non-straight walking tasks: single turns, lateral lane changes, walking on circular paths, and walking on arbitrary curvilinear paths. For each, we simulated idealized step sequences denoting "perfect" performance with known constant step lengths and widths. We compared results to path- independent alternatives. For each, we directly quantified accuracy relative to known true values. Results strongly confirmed our hypothesis. Our convention returned vastly smaller errors and introduced no artificial stepping asymmetries across all tasks. All results for our convention rationally generalized concepts from straight walking. Taking walking paths explicitly into account as important task goals themselves thus resolves conceptual ambiguities of prior approaches.

How Healthy Older Adults Enact Lateral Maneuvers While Walking.

Background: Walking requires frequent maneuvers to navigate changing environments with shifting goals. Humans accomplish maneuvers and simultaneously maintain balance primarily by modulating their foot placement, but a direct trade-off between these two objectives has been proposed. As older adults rely more on foot placement to maintain lateral balance, they may be less able to adequately adapt stepping to perform lateral maneuvers. Research Question: How do older adults adapt stepping to enact lateral lane-change maneuvers, and how do physical and perceived ability influence their task performance? Methods: Twenty young (21.7 ± 2.6 yrs) and 18 older (71.6 ± 6.0 yrs) adults walked on a motorized treadmill in a virtual environment. Following an audible and visual cue, participants switched between two parallel paths, centered 0.6m apart, to continue walking on their new path. We quantified when participants initiated the maneuver following the cue, as well as their step width, lateral position, and stepping variability ellipses at each maneuver step. Results: Young and older adults did not differ in when they initiated the maneuver, but participants with lower perceived ability took longer to do so. Young and older adults also did not exhibit differences in step width or lateral positions at any maneuver step, but participants with greater physical ability reached their new path faster. While only older adults exhibited stepping adaptations prior to initiating the maneuver, both groups traded-off stability for maneuverability to enact the lateral maneuver. Significance: Physical and perceived balance ability, rather than age per se, differentially influenced maneuver task performance. Humans must make decisions related to the task of walking itself and do so based on both physical and perceived factors. Understanding and targeting these interactions may help improve walking performance among older adults.

Adaptive multi-objective control explains how humans make lateral maneuvers while walking.

To successfully traverse their environment, humans often perform maneuvers to achieve desired task goals while simultaneously maintaining balance. Humans accomplish these tasks primarily by modulating their foot placements. As humans are more unstable laterally, we must better understand how humans modulate lateral foot placement. We previously developed a theoretical framework and corresponding computational models to describe how humans regulate lateral stepping during straight-ahead continuous walking. We identified goal functions for step width and lateral body position that define the walking task and determine the set of all possible task solutions as Goal Equivalent Manifolds (GEMs). Here, we used this framework to determine if humans can regulate lateral stepping during non-steady-state lateral maneuvers by minimizing errors consistent with these goal functions. Twenty young healthy adults each performed four lateral lane-change maneuvers in a virtual reality environment. Extending our general lateral stepping regulation framework, we first re-examined the requirements of such transient walking tasks. Doing so yielded new theoretical predictions regarding how steps during any such maneuver should be regulated to minimize error costs, consistent with the goals required at each step and with how these costs are adapted at each step during the maneuver. Humans performed the experimental lateral maneuvers in a manner consistent with our theoretical predictions. Furthermore, their stepping behavior was well modeled by allowing the parameters of our previous lateral stepping models to adapt from step to step. To our knowledge, our results are the first to demonstrate humans might use evolving cost landscapes in real time to perform such an adaptive motor task and, furthermore, that such adaptation can occur quickly-over only one step. Thus, the predictive capabilities of our general stepping regulation framework extend to a much greater range of walking tasks beyond just normal, straight-ahead walking.

Rethinking margin of stability: Incorporating step-to-step regulation to resolve the paradox.

Derived from inverted pendulum dynamics, mediolateral Margin of Stability (MoSML) is a mechanically-grounded measure of instantaneous frontal-plane stability. However, average MoSML measures yield paradoxical results. Gait pathologies or perturbations often induce larger (supposedly "more stable") average MoSML, despite clearly destabilizing factors. However, people do not walk "on average" - they walk (and sometimes lose balance) one step at a time. We assert the paradox arises because averaging MoSML discards crucial step-to-step dynamics. We present a framework unifying the inverted pendulum with Goal-Equivalent Manifold (GEM) analyses. We identify in the pendulum's center-of-mass dynamics constant-MoSML manifolds, including one candidate "stability GEM" signifying the goal to maintain some constant MoSML∗. We used this framework to assess step-to-step MoSML dynamics of humans walking in destabilizing environments. While goal-relevant deviations were readily corrected, people did not exploit equifinality by allowing deviations to persist along this GEM. Thus, maintaining a constant MoSML∗ is inconsistent with observed step-to-step fluctuations in center-of-mass states. Conversely, the extent to which participants regulated fluctuations in mediolateral foot placements strongly predicted their regulation of center-of-mass fluctuations. Thus, center-of-mass dynamics may arise indirectly as a consequence of regulating mediolateral foot placements. To help resolve the paradox caused by averaging MoSML, we present a new statistic, Probability of Instability (PoIL), used here to predict lateral instability likelihood. Participants exhibited increased PoIL when destabilized (p = 9.45 × 10-34), despite exhibiting larger ("more stable") average MoSML (p = 1.70 × 10-15). Thus, PoIL correctly captured people's increased risk of losing lateral balance, whereas average MoSML did not. PoIL also helps explain why people's average MoSML increased in destabilizing contexts.

Humans trade off whole-body energy cost to avoid overburdening muscles while walking.

Metabolic cost minimization is thought to underscore the neural control of locomotion. Yet, avoiding high muscle activation, a cause of fatigue, often outperforms energy minimization in computational predictions of human gait. Discerning the relative importance of these criteria in human walking has proved elusive, in part, because they have not been empirically decoupled. Here, we explicitly decouple whole-body metabolic cost and 'fatigue-like' muscle activation costs (estimated from electromyography) by pitting them against one another using two distinct gait tasks. When experiencing these competing costs, participants (n = 10) chose the task that avoided overburdening muscles (fatigue avoidance) at the expense of higher metabolic power (p < 0.05). Muscle volume-normalized activation more closely models energy use and was also minimized by the participants' decision (p < 0.05), demonstrating that muscle activation was, at best, an inaccurate signal for metabolic energy. Energy minimization was only observed when there was no adverse effect on muscle activation costs. By decoupling whole-body metabolic and muscle activation costs, we provide among the first empirical evidence of humans embracing non-energetic optimality in favour of a clearly defined neuromuscular objective. This finding indicates that local muscle fatigue and effort may well be key factors dictating human walking behaviour and its evolution.

Viability, task switching, and fall avoidance of the simplest dynamic walker.

Walking humans display great versatility when achieving task goals, like avoiding obstacles or walking alongside others, but the relevance of this to fall avoidance remains unknown. We recently demonstrated a functional connection between the motor regulation needed to achieve task goals (e.g., maintaining walking speed) and a simple walker's ability to reject large disturbances. Here, for the same model, we identify the viability kernel-the largest state-space region where the walker can step forever via at least one sequence of push-off inputs per state. We further find that only a few basins of attraction of the speed-regulated walker's steady-state gaits can fully cover the viability kernel. This highlights a potentially important role of task-level motor regulation in fall avoidance. Therefore, we posit an adaptive hierarchical control/regulation strategy that switches between different task-level regulators to avoid falls. Our task switching controller only requires a target value of the regulated observable-a "task switch"-at every walking step, each chosen from a small, predetermined collection. Because humans have typically already learned to perform such goal-directed tasks during nominal walking conditions, this suggests that the "information cost" of biologically implementing such controllers for the nervous system, including cognitive demands in humans, could be quite low.

Walking humans trade off different task goals to regulate lateral stepping.

People walk in complex environments where they must adapt their steps to maintain balance and satisfy changing task goals. How people do this is not well understood. We recently developed computational models of lateral stepping, based on Goal Equivalent Manifolds that serve as motor regulation templates, to identify how people regulate walking movements from step-to-step. In normal walking, healthy adults strongly maintain step width, but also lateral position on their path. Here, we used this framework to pose empirically-testable hypotheses about how humans might adapt their lateral stepping dynamics when asked to prioritize different stepping goals. Participants walked on a treadmill in a virtual-reality environment under 4 conditions: normal walking and, while given direct feedback at each step, walking while trying to maintain constant step width, constant absolute lateral position, or constant heading (direction). Time series of lateral stepping variables were extracted, and variability and statistical persistence (reflecting step-to-step regulation) quantified. Participants exhibited less variability of the prescribed stepping variable compared to normal walking during each feedback condition. Stepping regulation results supported our models' predictions: to maintain constant step width or position, people either maintained or increased regulation of the prescribed variable, but also decreased regulation of its complement. Thus, people regulated lateral foot placements in predictable and systematic ways determined by specific task goals. Humans regulate stepping movements to not only "just walk" (step without falling), but also to achieve specific goal-directed tasks within a specific environment. The framework and motor regulation templates presented here capture these important interactions.

How persons with transtibial amputation regulate lateral stepping while walking in laterally destabilizing environments.

BACKGROUND: Persons with lower limb amputation often experience decreased physical capacity, difficulty walking, and increased fall risk. To either prevent or recover from a loss of balance, one must effectively regulate their stepping movements. It is therefore critical to identify how well persons with amputation regulate stepping. Here, we used a multi-objective control framework based on Goal Equivalent Manifolds to identify how persons with transtibial amputation (TTA) regulate lateral stepping while walking without and with lateral perturbations. RESEARCH QUESTION: When walking in destabilizing environments, do otherwise healthy persons with TTA exhibit greater difficulty regulating lateral stepping due to impaired control? Or do they instead continue to use similar strategies to regulate lateral stepping despite their amputation? METHODS: Eight persons with unilateral TTA and thirteen able-bodied (AB) controls walked in a virtual environment under three conditions: no perturbations, laterally oscillating visual field, and laterally oscillating treadmill platform. We analyzed step-to-step time series of step widths and absolute lateral body positions. We computed means, standard deviations and Detrended Fluctuation Analysis scaling exponents for each time series and computed how much participants directly corrected step width and position deviations at each step. We compared our results to computational predictions to identify the underlying causes of our experimental findings. RESULTS: All participants exhibited significantly increased variability, decreased scaling exponents, and tighter direct control when perturbed. Simulations from our stepping regulation models revealed that people responded to the increased variability produced by the imposed perturbations by tightening their control of both step width and lateral position. Participants with TTA exhibited only a few minor differences from AB in lateral stepping regulation, even when subjected to substantially destabilizing lateral perturbations. SIGNIFICANCE: Since control of stepping is intrinsically multi-objective, developing effective interventions to reduce fall risk in persons with amputation will likely require strategies that adopt multi-objective approaches.

Task-level regulation enhances global stability of the simplest dynamic walker.

Much remains unknown about how considerations such as stability and energy minimization shape the way humans walk. While active neuromotor control keeps humans upright, they also need to choose from multiple stepping regulation strategies to achieve one or more task goals, such as maintaining a desired speed or direction. Experiments on human treadmill walking motivate an important question: why do humans prefer one task-level regulation strategy over another-perhaps to enhance their ability to reject large disturbances? Here, we study the relationship between task-level regulation and global stability in a powered compass walker on a treadmill, with added step-to-step speed and position regulators. For treadmill walking, we find that speed regulation greatly enlarges and regularizes the unregulated walker's stability region, i.e. its basin of attraction, much more than position regulation. Thus, our results suggest a possible explanation for the experimental finding that humans strongly prioritize regulating speed from one stride to the next, even as they walk economically on average. Furthermore, our work suggests a functional connection between task-level motor regulation and global stability-and, thus, perhaps even fall risk.

How healthy older adults regulate lateral foot placement while walking in laterally destabilizing environments.

Gait variability is generally associated with falls, but specific connections remain disputed. To reduce falls, we must first understand how older adults maintain lateral balance while walking, particularly when their stability is challenged. We recently developed computational models of lateral stepping, based on Goal Equivalent Manifolds, that separate effects of step-to-step regulation from variability. These show walking humans seek to strongly maintain step width, but also lateral position on their path. Here, 17 healthy older (ages 60+) and 17 healthy young (ages 18-31) adults walked in a virtual environment with no perturbations and with laterally destabilizing perturbations of either the visual field or treadmill platform. For step-to-step time series of step widths and lateral positions, we computed variability, statistical persistence and how much participants directly corrected deviations at each step. All participants exhibited significantly increased variability, decreased persistence and tighter direct control when perturbed. Simulations from our stepping regulation models indicate people responded to the increased variability imposed by these perturbations by either maintaining or tightening control of both step width and lateral position. Thus, while people strive to maintain lateral balance, they also actively strive to stay on their path. Healthy older participants exhibited slightly increased variability, but no differences from young in stepping regulation and no evidence of greater reliance on visual feedback, even when subjected to substantially destabilizing perturbations. Thus, age alone need not degrade lateral stepping control. This may help explain why directly connecting gait variability to fall risk has proven difficult.

Correlations of pelvis state to foot placement do not imply within-step active control.

Experimental studies of human walking have shown that within an individual step, variations in the center of mass (CoM) state can predict corresponding variations in the next foot placement. This has been interpreted by some to indicate the existence of active control in which the nervous system uses the CoM state at or near mid-stance to regulate subsequent foot placement. However, the passive dynamics of the moving body and/or moving limbs also contribute (perhaps strongly) to foot placement, and thus to its variation. The extent to which correlations of CoM state to foot placement reflect the effects of within-step active control, those of passive dynamics, or some combination of both, remains an important and still open question. Here, we used an open-loop-stable 2D walking model to show that this predictive ability cannot by itself be taken as evidence of within-step active control. In our simulations, we too find high correlations between the CoM state and subsequent foot placement, but these correlations are entirely due to passive dynamics as our system has no active control, either within a step or between steps. This demonstrates that any inferences made from such correlations about within-step active control require additional supporting evidence beyond the correlations themselves. Thus, these within-step predictive correlations leave unresolved the relative importance of within-step active control as compared to passive dynamics, meaning that such methods should be used to characterize control in human walking only with caution.

Multi-objective control in human walking: insight gained through simultaneous degradation of energetic and motor regulation systems.

Minimization of metabolic energy is considered a fundamental principle of human locomotion, as demonstrated by an alignment between the preferred walking speed (PWS) and the speed incurring the lowest metabolic cost of transport. We aimed to (i) simultaneously disrupt metabolic cost and an alternate acute task requirement, namely speed error regulation, and (ii) assess whether the PWS could be explained on the basis of either optimality criterion in this new performance and energetic landscape. Healthy adults (N = 21) walked on an instrumented treadmill under normal conditions and, while negotiating a continuous gait perturbation, imposed leg-length asymmetry. Oxygen consumption, motion capture data and ground reaction forces were continuously recorded for each condition at speeds ranging from 0.6 to 1.8 m s-1, including the PWS. Both metabolic and speed regulation measures were disrupted by the perturbation (p < 0.05). Perturbed PWS selection did not exhibit energetic prioritization (although we find some indication of energy minimization after motor adaptation). Similarly, PWS selection did not support prioritization of speed error regulation, which was found to be independent of speed in both conditions. It appears that, during acute exposure to a mechanical gait perturbation of imposed leg-length asymmetry, humans minimize neither energetic cost nor speed regulation errors. Despite the abundance of evidence pointing to energy minimization during normal, steady-state gait, this may not extend acutely to perturbed gait. Understanding how the nervous system acutely controls gait perturbations requires further research that embraces multi-objective control paradigms.

Humans use multi-objective control to regulate lateral foot placement when walking.

A fundamental question in human motor neuroscience is to determine how the nervous system generates goal-directed movements despite inherent physiological noise and redundancy. Walking exhibits considerable variability and equifinality of task solutions. Existing models of bipedal walking do not yet achieve both continuous dynamic balance control and the equifinality of foot placement humans exhibit. Appropriate computational models are critical to disambiguate the numerous possibilities of how to regulate stepping movements to achieve different walking goals. Here, we extend a theoretical and computational Goal Equivalent Manifold (GEM) framework to generate predictive models, each posing a different experimentally testable hypothesis. These models regulate stepping movements to achieve any of three hypothesized goals, either alone or in combination: maintain lateral position, maintain lateral speed or "heading", and/or maintain step width. We compared model predictions against human experimental data. Uni-objective control models demonstrated clear redundancy between stepping variables, but could not replicate human stepping dynamics. Most multi-objective control models that balanced maintaining two of the three hypothesized goals also failed to replicate human stepping dynamics. However, multi-objective models that strongly prioritized regulating step width over lateral position did successfully replicate all of the relevant step-to-step dynamics observed in humans. Independent analyses confirmed this control was consistent with linear error correction and replicated step-to-step dynamics of individual foot placements. Thus, the regulation of lateral stepping movements is inherently multi-objective and balances task-specific trade-offs between competing task goals. To determine how people walk in their environment requires understanding both walking biomechanics and how the nervous system regulates movements from step-to-step. Analogous to mechanical "templates" of locomotor biomechanics, our models serve as "control templates" for how humans regulate stepping movements from each step to the next. These control templates are symbiotic with well-established mechanical templates, providing complimentary insights into walking regulation.

Humans control stride-to-stride stepping movements differently for walking and running, independent of speed.

As humans walk or run, external (environmental) and internal (physiological) disturbances induce variability. How humans regulate this variability from stride-to-stride can be critical to maintaining balance. One cannot infer what is "controlled" based on analyses of variability alone. Assessing control requires quantifying how deviations are corrected across consecutive movements. Here, we assessed walking and running, each at two speeds. We hypothesized differences in speed would drive changes in variability, while adopting different gaits would drive changes in how people regulated stepping. Ten healthy adults walked/ran on a treadmill under four conditions: walk or run at comfortable speed, and walk or run at their predicted walk-to-run transition speed. Time series of relevant stride parameters were analyzed to quantify variability and stride-to-stride error-correction dynamics within a Goal-Equivalent Manifold (GEM) framework. In all conditions, participants' stride-to-stride control respected a constant-speed GEM strategy. At each consecutively faster speed, variability tangent to the GEM increased (p ≤ 0.031), while variability perpendicular to the GEM decreased (p ≤ 0.044). There were no differences (p ≥ 0.999) between gaits at the transition speed. Differences in speed determined how stepping variability was structured, independent of gait, confirming our first hypothesis. For running versus walking, measures of GEM-relevant statistical persistence were significantly less (p ≤ 0.004), but showed minimal-to-no speed differences (0.069 ≤ p ≤ 0.718). When running, people corrected deviations both more quickly and more directly, each indicating tighter control. Thus, differences in gait determined how stride-to-stride fluctuations were regulated, independent of speed, confirming our second hypothesis.

Increased gait variability may not imply impaired stride-to-stride control of walking in healthy older adults: Winner: 2013 Gait and Clinical Movement Analysis Society Best Paper Award.

Older adults exhibit increased gait variability that is associated with fall history and predicts future falls. It is not known to what extent this increased variability results from increased physiological noise versus a decreased ability to regulate walking movements. To "walk", a person must move a finite distance in finite time, making stride length (Ln) and time (Tn) the fundamental stride variables to define forward walking. Multiple age-related physiological changes increase neuromotor noise, increasing gait variability. If older adults also alter how they regulate their stride variables, this could further exacerbate that variability. We previously developed a Goal Equivalent Manifold (GEM) computational framework specifically to separate these causes of variability. Here, we apply this framework to identify how both young and high-functioning healthy older adults regulate stepping from each stride to the next. Healthy older adults exhibited increased gait variability, independent of walking speed. However, despite this, these healthy older adults also concurrently exhibited no differences (all p>0.50) from young adults either in how their stride variability was distributed relative to the GEM or in how they regulated, from stride to stride, either their basic stepping variables or deviations relative to the GEM. Using a validated computational model, we found these experimental findings were consistent with increased gait variability arising solely from increased neuromotor noise, and not from changes in stride-to-stride control. Thus, age-related increased gait variability likely precedes impaired stepping control. This suggests these changes may in turn precede increased fall risk.