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Processing task-relevant visual information is important for the successful completion of many everyday tasks. Prior work demonstrated that aging is associated with increased susceptibility to distraction by salient stimuli. However, these studies often use simple stimuli and little is known about how aging influences visual attention in 3D environments that are more representative of real-world visual complexity. We asked young and older adults to complete a virtual reality-based visual search task with three levels of increasing visual complexity. As the visual complexity of the environment increased, all participants took longer to complete the task, in part because they increased the time spent re-fixating task-relevant objects and the time spent fixating task-irrelevant objects. We also found that older adults took longer to complete the task and spent more time re-fixating task-relevant objects and fixating task-irrelevant objects. In addition, we found that short-term and working memory capacities were related to multiple measures of performance in the visual search task. These results demonstrate the importance of assessing the effects of aging on the control of visual attention using tasks and environments that better capture features of the real world.

BackgroundWalking patterns in stroke survivors are highly heterogeneous, which poses a challenge in systematizing treatment prescriptions for walking rehabilitation interventions.ObjectiveWe used bilateral spatiotemporal and force data during walking to create a multi-site research sample to: 1) identify clusters of walking behaviors in people post-stroke and neurotypical controls, and 2) determine the generalizability of these walking clusters across different research sites. We hypothesized that participants post-stroke will have different walking impairments resulting in different clusters of walking behaviors, which are also different from control participants.MethodsWe collected data from 81 post-stroke participants across four research sites and included data from 31 control participants. Using sparse K-means clustering, we identified walking clusters based on 17 spatiotemporal and force variables. We analyzed the biomechanical features within each cluster to characterize cluster-specific walking behaviors. We also assessed the generalizability of the clusters using a leave-one-out approach.ResultsWe identified five clusters: a fast and asymmetric cluster, a moderate speed and symmetric cluster with short stance times, a moderate speed and asymmetric cluster, a slow cluster with frontal plane force asymmetries, and a slow and symmetric cluster. The moderate speed and asymmetric cluster did not generalize across sites.ConclusionsAlthough post-stroke walking patterns are heterogenous, these patterns can be systematically classified into distinct clusters based on spatiotemporal and force data. Future interventions could target the key features that characterize each cluster to increase the efficacy of interventions to improve mobility in people post-stroke.

BackgroundGait biofeedback is commonly used to reduce gait dysfunction in a variety of clinical conditions. In these studies, participants alter their walking to reach the desired magnitude of a specific gait parameter (the biofeedback target) with each step. Biofeedback of parameters such as anterior ground reaction force and step length have been well-studied. Yet, there is no standardized methodology to set the target magnitude of these parameters. Here we present an approach to predict the anterior ground reaction force and step length of neurotypical adults walking at different speeds as a potential method for personalized gait biofeedback.Research questionTo determine if anterior ground reaction force and step lengths achieved during neurotypical walking could be predicted using gait speed and participants’ demographic and anthropomorphic characteristics.MethodsWe analyzed kinetic and kinematic data from 51 neurotypical adults who walked on a treadmill at up to eight speeds. We calculated the average peak anterior ground reaction force and step length of the right lower extremity at each speed. We used linear mixed-effects models to evaluate the effect of speed, leg length, mass, and age on anterior ground reaction force and step length. We fit the model to data from 37 participants and validated predictions from the final models on an independent dataset from 23 participants.ResultsFinal prediction models for anterior ground reaction force and step length both included speed, speed squared, age, mass, and leg length. The models both showed strong agreement between predicted and actual values on an independent dataset.SignificanceAnterior ground reaction force and step length for neurotypical adults can be predicted given an individual’s gait speed, age, leg length, and mass. This may provide a standardized method to personalize targets for individuals with gait dysfunction in future studies of gait biofeedback.

Impaired motor learning in individuals with Parkinson's disease is often attributed to deficits in executive function, which serves as an important cognitive process supporting motor learning. However, less is known about the role of other cognitive domains and its association with motor learning in Parkinson's disease. The objective of this study was to investigate the associations between motor learning and multiple domains of cognitive performance in individuals with Parkinson's disease. Twenty-nine participants with Parkinson's disease received comprehensive neuropsychological testing, followed by practice of a bimanual finger sequence task. A retention test of the finger sequence task was completed 24 h later. Hierarchical linear regressions were used to examine the associations between motor learning (acquisition rate and retention) and cognitive performance in five specific cognitive domains, while controlling for age, sex, and years of Parkinson's disease diagnosis. We found that a higher acquisition rate was associated with better episodic memory, specifically better recall in visual episodic memory, in individuals with Parkinson's disease. No significant associations were observed between retention and cognitive performance in any domains. The association between motor acquisition and episodic memory indicates an increased dependency on episodic memory as a potential compensatory cognitive strategy used by individuals with Parkinson's disease during motor learning.

Next-generation Advanced Modular Reactors are expected to aid in the worldwide transition to net-zero emissions. However, these reactors are designed to operate at very high temperatures, which makes the structural integrity of the reactor critical to its design. The structural integrity of previous nuclear reactor designs has been calculated using deterministic methods, but this approach can lead to overly-conservative (or in some cases, optimistic) assessments. Probabilistic structural integrity analysis methods offer the potential to increase understanding of uncertainty and variability in the reactor design, which can reduce design conservatism or increase robustness. Classical Monte-Carlo analysis has been widely used for probabilistic structural integrity analysis, but this approach can be computationally expensive, making it unsuitable for use when iterating and refining reactor designs. This paper assesses alternative probabilistic structural integrity analysis methods, from simple, pseudo-stochastic look-up curve methods to a more complex surrogate Monte-Carlo analysis method using Gaussian process regression. Of the pseudo-stochastic methods, the log-normalized damage margin (LNDM) method is recommended, as it is the most robust, even when used with complex creep laws. The surrogate Monte-Carlo analysis (using a Gaussian process regressor as a surrogate) was found to generate results that were just as accurate and precise as classical Monte-Carlo analysis, but with several orders of magnitude lower computational cost.

Step length asymmetry (SLA) is common in most stroke survivors. Several studies have shown that factors such as paretic propulsion can explain between-subjects differences in SLA. However, whether the factors that account for between-subjects variance in SLA are consistent with those that account for within-subjects, stride-by-stride variance in SLA has not been determined. SLA direction is heterogeneous, and different impairments likely contribute to differences in SLA direction. Here, we identified common predictors between-subjects that explain within-subjects variance in SLA using sparse partial least squares regression (sPLSR). We determined whether the SLA predictors differ based on SLA direction and whether predictors obtained from within-subjects analyses were the same as those obtained from between-subjects analyses. We found that for parti-cipants who walked with longer paretic steps paretic double support time, braking impulse, peak vertical ground reaction force, and peak plantarflexion moment explained 59% of the within-subjects variance in SLA. However the within-subjects variance accounted for by each individual predictor was less than 10%. Peak paretic plantarflexion moment accounted for 4% of the within-subjects variance and 42% of the between-subjects variance in SLA. In participants who walked with shorter paretic steps, paretic and non-paretic braking impulse explained 18% of the within-subjects variance in SLA. Conversely, paretic braking impulse explained 68% of the between-subjects variance in SLA, but the association between SLA and paretic braking impulse was in the opposite direction for within-subjects vs. between-subjects analyses. Thus, the relationships that explain between-subjects variance might not account for within-subjects stride-by-stride variance in SLA.

Our nervous systems can learn optimal control policies in response to changes to our bodies, tasks, and movement contexts. For example, humans can learn to adapt their control policy in walking contexts where the energy-optimal policy is shifted along variables such as step frequency or step width. However, it is unclear how the nervous system determines which ways to adapt its control policy. Here, we asked how human participants explore through variations in their control policy to identify more optimal policies in new contexts. We created new contexts using exoskeletons that apply assistive torques to each ankle at each walking step. We analyzed four variables that spanned the levels of the whole movement, the joint, and the muscle: step frequency, ankle angle range, total soleus activity, and total medial gastrocnemius activity. We found that, across all of these analyzed variables, variability increased upon initial exposure to new contexts and then decreased with experience. This led to adaptive changes in the magnitude of specific variables, and these changes were correlated with reduced energetic cost. The timescales by which adaptive changes progressed and variability decreased were faster for some variables than others, suggesting a reduced search space within which the nervous system continues to optimize its policy. These collective findings support the principle that exploration through general variability leads to specific adaptation toward optimal movement policies.

Background Gait training at fast speeds is recommended to reduce walking activity limitations post-stroke. Fast walking may also reduce gait kinematic impairments post-stroke. However, it is unknown if differences in gait kinematics between people post-stroke and neurotypical adults decrease when walking at faster speeds. Objective To determine the effect of faster walking speeds on gait kinematics post-stroke relative to neurotypical adults walking at similar speeds. Methods We performed a secondary analysis with data from 28 people post-stroke and 50 neurotypical adults treadmill walking at multiple speeds. We evaluated the effects of speed and group on individual spatiotemporal and kinematic metrics and performed k-means clustering with all metrics at self-selected and fast speeds. Results People post-stroke decreased step length asymmetry and trailing limb angle impairment, reducing between-group differences at fast speeds. Speed-dependent changes in peak swing knee flexion, hip hiking, and temporal asymmetries exaggerated between-group differences. Our clustering analyses revealed two clusters. One represented neurotypical gait behavior, composed of neurotypical and post-stroke participants. The other characterized stroke gait behavior—comprised entirely of participants post-stroke with smaller lower extremity Fugl-Meyer scores than the post-stroke participants in the neurotypical gait behavior cluster. Cluster composition was largely consistent at both speeds, and the distance between clusters increased at fast speeds. Conclusions The biomechanical effect of fast walking post-stroke varied across individual gait metrics. For participants within the stroke gait behavior cluster, walking faster led to an overall gait pattern more different than neurotypical adults compared to the self-selected speed. This suggests that to potentiate the biomechanical benefits of walking at faster speeds and improve the overall gait pattern post-stroke, gait metrics with smaller speed-dependent changes may need to be specifically targeted within the context of fast walking.

Background Musculoskeletal modeling is currently a preferred method for estimating the muscle forces that underlie observed movements. However, these estimates are sensitive to a variety of assumptions and uncertainties, which creates difficulty when trying to interpret the muscle forces from musculoskeletal simulations. Here, we describe an approach that uses Bayesian inference to identify plausible ranges of muscle forces for a simple motion while representing uncertainty in the measurement of the motion and the objective function used to solve the muscle redundancy problem. Methods We generated a reference elbow flexion–extension motion and computed a set of reference forces that would produce the motion while minimizing muscle excitations cubed via OpenSim Moco. We then used a Markov Chain Monte Carlo (MCMC) algorithm to sample from a posterior probability distribution of muscle excitations that would result in the reference elbow motion. We constructed a prior over the excitation parameters which down-weighted regions of the parameter space with greater muscle excitations. We used muscle excitations to find the corresponding kinematics using OpenSim, where the error in position and velocity trajectories (likelihood function) was combined with the sum of the cubed muscle excitations integrated over time (prior function) to compute the posterior probability density. Results We evaluated the muscle forces that resulted from the set of excitations that were visited in the MCMC chain (seven parallel chains, 500,000 iterations per chain). The estimated muscle forces compared favorably with the reference forces generated with OpenSim Moco, while the elbow angle and velocity from MCMC matched closely with the reference (average RMSE for elbow angle = 2°; and angular velocity = 32°/s). However, our rank plot analyses and potential scale reduction statistics, which we used to evaluate convergence of the algorithm, indicated that the chains did not fully mix. Conclusions While the results from this process are a promising step towards characterizing uncertainty in muscle force estimation, the computational time required to search the solution space with, and the lack of MCMC convergence indicates that further developments in MCMC algorithms are necessary for this process to become feasible for larger-scale models.

Virtual reality (VR) interfaces provide immersive and engaging rehabilitation for populations such as people with Parkinson’s disease (PD). However, VR experiences for walking often lack haptic feedback about the user’s interaction with the environment. In this paper, we design a haptic interface that provides feedback in a therapeutic game to increase player’s engagement and immersion, with the goal of improving multitasking, obstacle avoidance, and mobility.

Background People poststroke often walk with a spatiotemporally asymmetric gait, due in part to sensorimotor impairments in the paretic lower extremity. Although reducing asymmetry is a common objective of rehabilitation, the effects of improving symmetry on balance are yet to be determined. Objective We established the concurrent validity of whole-body angular momentum as a measure of balance, and we determined if reducing step length asymmetry would improve balance by decreasing whole-body angular momentum. Methods We performed clinical balance assessments and measured whole-body angular momentum during walking using a full-body marker set in a sample of 36 people with chronic stroke. We then used a biofeedback-based approach to modify step length asymmetry in a subset of 15 of these individuals who had marked asymmetry and we measured the resulting changes in whole-body angular momentum. Results When participants walked without biofeedback, whole-body angular momentum in the sagittal and frontal plane was negatively correlated with scores on the Berg Balance Scale and Functional Gait Assessment supporting the validity of whole-body angular momentum as an objective measure of dynamic balance. We also observed that when participants walked more symmetrically, their whole-body angular momentum in the sagittal plane increased rather than decreased. Conclusions Voluntary reductions of step length asymmetry in people poststroke resulted in reduced measures of dynamic balance. This is consistent with the idea that after stroke, individuals might have an implicit preference not to deviate from their natural asymmetry while walking because it could compromise their balance. Clinical Trials Number: NCT03916562.

BACKGROUND Participant recruitment remains a barrier to conducting clinical research. The disabling nature of a stroke, which often includes functional and cognitive impairments, and the acute stage of illness at which patients are appropriate for many trials make recruiting patients particularly complex and challenging. In addition, people aged 65 years and older, which includes most stroke survivors, have been identified as a group that is difficult to reach and is commonly underrepresented in health research, particularly clinical trials. Digital media may provide effective tools to support enrollment efforts of stroke survivors in clinical trials. OBJECTIVE The objective of this study was to compare the effectiveness of general practice (traditional) and digital (online) methods of recruiting stroke survivors to a clinical mobility study. METHODS Recruitment for a clinical mobility study began in July 2018. Eligible study participants included individuals 18 years and older who had a single stroke and were currently ambulatory in the community. General recruiting practice included calling individuals listed in a stroke registry, contacting local physical therapists, and placing study flyers throughout a university campus. Between May 21, 2019, and June 26, 2019, the study was also promoted digitally using the social network Facebook and the search engine marketing tool Google AdWords. The recruitment advertisements (ads) included a link to the study page to which users who clicked were referred. Primary outcomes of interest for both general practice and digital methods included recruitment speed (enrollment rate) and sample characteristics. The data were analyzed using the Lilliefors test, the Welch two-sample t test, and the Mann-Whitney test. Significance was set at P=.05. All statistical analyses were performed in MATLAB 2019b. RESULTS Our results indicate that digital recruitment methods can address recruitment challenges regarding stroke survivors. Digital recruitment methods allowed us to enroll study participants at a faster rate (1.8 participants/week) compared to using general practice methods (0.57 participants/week). Our findings also demonstrate that digital and general recruitment practices can achieve an equivalent level of sample representativeness. The characteristics of the enrolled stroke survivors did not differ significantly by age (P=.95) or clinical scores (P=.22; P=.82). Comparing the cost-effectiveness of Facebook and Google, we found that the use of Facebook resulted in a lower cost per click and cost per enrollee per ad. CONCLUSIONS Digital recruitment can be used to expedite participant recruitment of stroke survivors compared to more traditional recruitment practices, while also achieving equivalent sample representativeness. Both general practice and digital recruitment methods will be important to the successful recruitment of stroke survivors. Future studies could focus on testing the effectiveness of additional general practice and digital media approaches and include robust cost-effectiveness analyses. Examining the effectiveness of different messaging and visual approaches tailored to culturally diverse and underrepresented target subgroups could provide further data to move toward evidence-based recruitment strategies.

Background Participant recruitment remains a barrier to conducting clinical research. The disabling nature of a stroke, which often includes functional and cognitive impairments, and the acute stage of illness at which patients are appropriate for many trials make recruiting patients particularly complex and challenging. In addition, people aged 65 years and older, which includes most stroke survivors, have been identified as a group that is difficult to reach and is commonly underrepresented in health research, particularly clinical trials. Digital media may provide effective tools to support enrollment efforts of stroke survivors in clinical trials. Objective The objective of this study was to compare the effectiveness of general practice (traditional) and digital (online) methods of recruiting stroke survivors to a clinical mobility study. Methods Recruitment for a clinical mobility study began in July 2018. Eligible study participants included individuals 18 years and older who had a single stroke and were currently ambulatory in the community. General recruiting practice included calling individuals listed in a stroke registry, contacting local physical therapists, and placing study flyers throughout a university campus. Between May 21, 2019, and June 26, 2019, the study was also promoted digitally using the social network Facebook and the search engine marketing tool Google AdWords. The recruitment advertisements (ads) included a link to the study page to which users who clicked were referred. Primary outcomes of interest for both general practice and digital methods included recruitment speed (enrollment rate) and sample characteristics. The data were analyzed using the Lilliefors test, the Welch two-sample t test, and the Mann-Whitney test. Significance was set at P=.05. All statistical analyses were performed in MATLAB 2019b. Results Our results indicate that digital recruitment methods can address recruitment challenges regarding stroke survivors. Digital recruitment methods allowed us to enroll study participants at a faster rate (1.8 participants/week) compared to using general practice methods (0.57 participants/week). Our findings also demonstrate that digital and general recruitment practices can achieve an equivalent level of sample representativeness. The characteristics of the enrolled stroke survivors did not differ significantly by age (P=.95) or clinical scores (P=.22; P=.82). Comparing the cost-effectiveness of Facebook and Google, we found that the use of Facebook resulted in a lower cost per click and cost per enrollee per ad. Conclusions Digital recruitment can be used to expedite participant recruitment of stroke survivors compared to more traditional recruitment practices, while also achieving equivalent sample representativeness. Both general practice and digital recruitment methods will be important to the successful recruitment of stroke survivors. Future studies could focus on testing the effectiveness of additional general practice and digital media approaches and include robust cost-effectiveness analyses. Examining the effectiveness of different messaging and visual approaches tailored to culturally diverse and underrepresented target subgroups could provide further data to move toward evidence-based recruitment strategies.

This demo uses Virtual Reality (VR) to assess cognitive function in people with Parkinson’s disease. We developed a VR-based assessment that combines simple game mechanics with components of the Trail Making Test. We collect performance metrics and gaze analytics during gameplay using the HTC Vive Pro Eye system. Ultimately, this data will allow clinicians and researchers to characterize cognitive and visuomotor deficits in people with neurological impairments such as Parkinson’s disease.

Cost functions have the potential to provide compact and understandable generalizations of motion. The goal of Inverse Optimal Control (IOC) is to analyze an observed behavior which is assumed to be optimal with respect to an unknown cost function, and infer this cost function. Here we develop a method for characterizing cost functions of legged locomotion, with the goal of representing complex humanoid behavior with simple models. To test this methodology we simulate walking gaits of a simple 5 link planar walking model which optimize known cost functions, and assess the ability of our IOC method to recover them. In particular, the IOC method uses an iterative trajectory optimization process to infer cost function weightings consistent with those used to generate a single demonstrated optimal trial. We also explore sensitivity of the IOC to sensor noise in the observed trajectory, imperfect knowledge of the model or task, as well as uncertainty in the components of the cost function used. With appropriate modeling, these methods may help infer cost functions from human data, yielding a compact and generalizable representation of human-like motion for use in humanoid robot controllers, as well as providing a new tool for experimentally exploring human preferences., Comment: 9 pages, 5 figures

Background. Maintaining balance in response to perturbations during walking often requires the use of corrective responses to keep the center of mass within the base of support. The relationship between the center of mass and base of support is often quantified using the margin of stability. Although people post-stroke increase the margin of stability following perturbations, control deficits may lead to asymmetries in regulation of margins of stability, which may also cause maladaptive coupling between the sagittal and frontal planes during balance-correcting responses.Methods. We assessed how paretic and non-paretic margins of stability are controlled during recovery from forward perturbations and determined how stroke-related impairments influence the coupling between the anteroposterior and mediolateral margins of stability. Twenty-one participants with post-stroke hemiparesis walked on a treadmill while receiving slip-like perturbations on both limbs at foot-strike. We assessed anteroposterior and mediolateral margins of stability before perturbations and during perturbation recovery.Findings. Participants walked with smaller anteroposterior and larger mediolateral margins of stability on the paretic versus non-paretic sides. When responding to perturbations, participants increased the anteroposterior margin of stability bilaterally by extending the base of support and reducing the excursion of the extrapolated center of mass. The anteroposterior and mediolateral margins of stability in the paretic limb negatively covaried during reactive steps such that increases in anteroposterior were associated with reductions in mediolateral margins of stability.Interpretation. Balance training interventions to reduce fall risk post-stroke may benefit from incorporating strategies to reduce maladaptive coupling of frontal and sagittal plane stability.

Severe impairment of limb movement after stroke can be challenging to address in the chronic stage of stroke (e.g., greater than 6 months post stroke). Recent evidence suggests that physical therapy can still promote meaningful recovery after this stage, but the required high amount of therapy is difficult to deliver within the scope of standard clinical practice. Digital gaming technologies are now being combined with brain&ndash, computer interfaces to motivate engaging and frequent exercise and promote neural recovery. However, the complexity and expense of acquiring brain signals has held back widespread utilization of these rehabilitation systems. Furthermore, for people that have residual muscle activity, electromyography (EMG) might be a simpler and equally effective alternative. In this pilot study, we evaluate the feasibility and efficacy of an EMG-based variant of our REINVENT virtual reality (VR) neurofeedback rehabilitation system to increase volitional muscle activity while reducing unintended co-contractions. We recruited four participants in the chronic stage of stroke recovery, all with severely restricted active wrist movement. They completed seven 1-hour training sessions during which our head-mounted VR system reinforced activation of the wrist extensor muscles without flexor activation. Before and after training, participants underwent a battery of clinical and neuromuscular assessments. We found that training improved scores on standardized clinical assessments, equivalent to those previously reported for brain&ndash, computer interfaces. Additionally, training may have induced changes in corticospinal communication, as indexed by an increase in 12&ndash, 30 Hz corticomuscular coherence and by an improved ability to maintain a constant level of wrist muscle activity. Our data support the feasibility of using muscle&ndash, computer interfaces in severe chronic stroke, as well as their potential to promote functional recovery and trigger neural plasticity.

People can learn to exploit external assistance during walking to reduce energetic cost. For example, walking on a split-belt treadmill affords the opportunity for people to redistribute the mechanical work performed by the legs to gain assistance from the difference in belts’ speed and reduce energetic cost. Though we know what people should do to acquire this assistance, this strategy is not observed during typical adaptation studies. We hypothesized that extending the time allotted for adaptation would result in participants adopting asymmetric step lengths to increase the assistance they can acquire from the treadmill. Here, participants walked on a split-belt treadmill for 45 min while we measured spatiotemporal gait variables, metabolic cost, and mechanical work. We show that when people are given sufficient time to adapt, they naturally learn to step further forward on the fast belt, acquire positive mechanical work from the treadmill, and reduce the positive work performed by the legs. We also show that spatiotemporal adaptation and energy optimization operate over different timescales: people continue to reduce energetic cost even after spatiotemporal changes have plateaued. Our findings support the idea that walking with symmetric step lengths, which is traditionally thought of as the endpoint of adaptation, is only a point in the process by which people learn to take advantage of the assistance provided by the treadmill. These results provide further evidence that reducing energetic cost is central in shaping adaptive locomotion, but this process occurs over more extended timescales than those used in typical studies. NEW & NOTEWORTHY Split-belt treadmill adaptation can be seen as a process where people learn to acquire positive work from the treadmill to reduce energetic cost. Though we know what people should do to reduce energetic cost, this strategy is not observed during adaptation studies. We extended the duration of adaptation and show that people continuously adapt their gait to acquire positive work from the treadmill to reduce energetic cost. This process requires longer exposure than traditionally allotted.

Fibre composites, and especially aligned discontinuous composites (ADCs), offer enormous versatility in composition, microstructure, and performance, but are difficult to optimise, due to their inherent variability and myriad permutations of microstructural design variables. This work combines an accurate yet efficient virtual testing framework (VTF) with a data-driven intelligent Bayesian optimisation routine, to maximise the mechanical performance of ADCs for a number of single- and multi-objective design cases. The use of a surrogate model helps to minimise the number of optimisation iterations, and provides a more accurate insight into the expected performance of materials which feature significant variability. Results from the single-objective optimisation study show that a wide range of structural properties can be achieved using ADCs, with a maximum stiffness of 505 GPa, maximum ultimate strain of 3.94%, or a maximum ultimate strength of 1.92 GPa all possible. A moderate trade-off in performance can be achieved when considering multi-objective optimisation design cases, such as an optimal ultimate strength & ultimate strain combination of 982 MPa and 3.27%, or an optimal combination of 720 MPa yield strength & 1.91% pseudo-ductile strain.

Recovery from perturbations during walking is primarily mediated by reactive control strategies that coordinate multiple body segments to maintain balance. Balance control is often impaired in clinical populations who walk with spatiotemporally asymmetric gait, and, as a result, rehabilitation efforts often seek to reduce asymmetries in these populations. Previous work has demonstrated that the presence of spatiotemporal asymmetries during walking does not impair the control of whole-body dynamics during perturbation recovery. However, it remains to be seen how the neuromotor system adjusts intersegmental coordination patterns to maintain invariant whole-body dynamics. Here, we determined if the neuromotor system generates stereotypical coordination patterns irrespective of the level of asymmetry or if the neuromotor system allows for variance in intersegmental coordination patterns to stabilize whole-body dynamics in the sagittal plane. Nineteen healthy participants walked on a dual-belt treadmill at a range of step length asymmetries, and they responded to unpredictable, slip-like perturbations. We used principal component analysis of segmental angular momenta to characterize intersegmental coordination patterns before, during, and after imposed perturbations. We found that two principal components were sufficient to explain ~ 95% of the variance in segmental angular momentum during both steady-state walking and responses to perturbations. Our results also revealed that walking with asymmetric step lengths led to changes in intersegmental coordination patterns during the perturbation and during subsequent recovery steps without affecting whole-body angular momentum. These results suggest that the nervous system allows for variance in segment-level coordination patterns to maintain invariant control of whole-body angular momentum during walking. Future studies exploring how these segmental coordination patterns change in individuals with asymmetries that result from neuromotor impairments can provide further insight into how the healthy and impaired nervous system regulates dynamic balance during walking.

Pseudo-ductility presents a potential means for preventing catastrophic failure in composite materials; large deformations will prevent brittle fracture and provide warning before final failure. This work explores how the pseudo-ductility and strength of aligned hybrid discontinuous composites can be controlled by manipulating the arrangement of different fibre types. Aligned carbon/glass hybrid specimens with different fibre arrangements are manufactured and tested using a modification to the High Performance Discontinuous Fibre (HiPerDiF) method. Experimental results are complemented by an improved virtual testing framework, which accurately captures the fracture behaviour of a range of hybrid discontinuous composite microstructures. With a randomly intermingled fibre arrangement as a baseline, a 27 % increase in strength and a 44 % increase in pseudo-ductility can be achieved when low elongation fibres are completely isolated from one-another. Results demonstrate that the HiPerDiF method is the current state-of-the-art for maximising the degree of intermingling and hence the pseudo-ductility of hybrid composites.

The ability to control the body's center of mass (CoM) is critical for preventing falls, which are a major health concern in aging populations. Control of the CoM has been assessed by characterizing dynamic margins of stability (MoS) which capture the dynamic relationship between the CoM and the base of support. Accurate estimation of CoM dynamics is best accomplished using a full-body marker set. However, a number of simplified estimates have been used throughout literature. Here, we determined the biases and sources of bias when computing MoS using four simplified CoM models, and we characterized how these biases varied in straight walking versus turning. CoM kinematics were characterized using a full-body marker set, the lower extremities and trunk, lower extremities only, an average of four pelvic markers, and one pelvic marker alone. Significant bias was demonstrated for most methods and was larger during turning tasks compared to straight walking. In the fore-aft direction, only overestimates in the MoS were observed, and these ranged from 15 to 110% larger than the true MoS value. In the mediolateral direction, both under- and over-estimates were observed and ranged from -175 to 225%. Across tasks, bias was smallest when using the lower extremity plus trunk (-23 to 62%) and pelvis average methods (-71 to 43%). Sources of bias were attributed to misestimates of CoM height, velocity, and position. Together, our findings suggest that the 1) lower extremity and trunk model and 2) pelvis average model should be considered in future studies to minimize bias when simplified models of CoM dynamics are desired.

Aligned discontinuous composites offer a tailorable structural response, as their mechanical behaviour can be tailored by adjusting their microstructure. However, the stochastic nature of their microstructure, and the myriad permutations of different constituent properties makes optimisation of these materials difficult. In this work, an accurate yet efficient virtual testing framework is combined with an intelligent Bayesian optimisation routine to maximise the initial stiffness, ultimate strain, and ultimate strength of aligned discontinuous composites.

Recovery from perturbations during walking is primarily mediated by reactive control strategies that coordinate multiple body segments to maintain balance. Balance control is often impaired in clinical populations who walk with spatiotemporally asymmetric gait, and, as a result, rehabilitation efforts often seek to reduce asymmetries in these populations. Previous work has demonstrated that the presence of spatiotemporal asymmetries during walking does not impair the control of whole-body dynamics during perturbation recovery. However, it remains to be seen how the neuromotor system adjusts intersegmental coordination patterns to maintain invariant whole-body dynamics. Here, we determined if the neuromotor system generates stereotypical coordination patterns irrespective of the level of asymmetry or if the neuromotor system allows for variance in intersegmental coordination patterns to stabilize whole-body dynamics. Nineteen healthy participants walked on a dual-belt treadmill at a range of step length asymmetries, and they responded to unpredictable, slip-like perturbations. We used principal component analysis of segmental angular momenta to characterize intersegmental coordination patterns before, during, and after imposed perturbations. We found that two principal components were sufficient to explain ~ 95% of the variance in segmental angular momentum during both steading walking and responses to perturbations. Our results also revealed that walking with asymmetric step lengths led to changes in intersegmental coordination patterns during the perturbation and during subsequent recovery steps without affecting whole-body angular momentum. These results suggest that the nervous system allows for variance in segment-level coordination patterns to maintain invariant control of whole-body angular momentum during walking. Future studies exploring how these segmental coordination patterns change in individuals with asymmetries that result from neuromotor impairments can provide further insight into how the healthy and impaired nervous system regulates dynamic balance during walking.

Aligned hybrid-fibre discontinuous composites offer the ability to tailor their mechanical response through careful microstructural design. However, with tailorability comes microstructural complexity, which in turn leads to many sources of variability and defects. A virtual testing framework was further extended to investigate the influence of variability and defects on the mechanical performance of various aligned discontinuous composite material systems. This approach identified the most critical sources of variability as (i) fibre strength, (ii) the distance between fibre ends, or (iii) the level of fibre-type intermingling, depending on the material system. Fibre vacancy defects were shown to have the most significant influence on the strength and ductility of aligned discontinuous composites, although this sensitivity can be reduced through hybridisation of the fibre types.

A fundamental feature of human locomotor control is the need to adapt our walking pattern in response to changes in the environment. For example, when people walk on a split-belt treadmill which has belts that move at different speeds, they adapt to the asymmetric speed constraints by reducing their spatiotemporal asymmetry. Here, we aim to understand the role of stability as a potential factor driving this adaptation process. We recruited 24 healthy, young adults to adapt to walking on a split-belt treadmill while either holding on to a handrail or walking with free arm swing. We measured whole-body angular momentum and step length asymmetry as measures of dynamic balance and spatiotemporal asymmetry, respectively. To understand how changes in intersegmental coordination influenced measures of dynamic balance, we also measured segmental angular momenta and the coefficient of limb cancellation. When participants were initially exposed to the asymmetry in belt speeds, we observed an increase in whole-body angular momentum that was due to both an increase in the momentum of individual limb segments and a reduction in limb cancellation. Holding on to a handrail reduced the perturbation to asymmetry during the early phase of adaptation and resulted in a smaller after-effect during post-adaptation. In addition, the stabilization provided by holding on to a handrail led to reductions in the coupling between angular momentum and asymmetry. These results suggest that regulation of dynamic balance is most important during the initial, transient phase of adaptation to walking on a split-belt treadmill.Summary StatementRegulation of balance exhibits a transient effect on adaptation to imposed asymmetries during bipedal walking. External stabilization attenuates initial deviations in spatiotemporal asymmetry but has no effect on subsequent adaptation.

Key points The neuromotor system generates flexible motor patterns that can adapt to changes in our bodies or environment and also take advantage of assistance provided by the environment. We ask how energy minimization influences adaptive learning during human locomotion to improve economy when walking on a split-belt treadmill. We use a model-based approach to predict how people should adjust their walking pattern to take advantage of the assistance provided by the treadmill, and we validate these predictions empirically. We show that adaptation to a split-belt treadmill can be explained as a process by which people reduce step length asymmetry to take advantage of the work performed by the treadmill to reduce metabolic cost. Our results also have implications for the evaluation of devices designed to reduce effort during walking, as locomotor adaptation may serve as a model approach to understand how people learn to take advantage of external assistance. Abstract In everyday tasks such as walking and running, we often exploit the work performed by external sources to reduce effort. Recent research has focused on designing assistive devices capable of performing mechanical work to reduce the work performed by muscles and improve walking function. The success of these devices relies on the user learning to take advantage of this external assistance. Although adaptation is central to this process, the study of adaptation is often done using approaches that seem to have little in common with the use of external assistance. We show in 16 young, healthy participants that a common approach for studying adaptation, split-belt treadmill walking, can be understood from a perspective in which people learn to take advantage of mechanical work performed by the treadmill. Initially, during split-belt walking, people step further forward on the slow belt than the fast belt which we measure as a negative step length asymmetry, but this asymmetry is reduced with practice. We demonstrate that reductions in asymmetry allow people to extract positive work from the treadmill, reduce the positive work performed by the legs, and reduce metabolic cost. We also show that walking with positive step length asymmetries, defined by longer steps on the fast belt, minimizes metabolic cost, and people choose this pattern after guided experience of a wide range of asymmetries. Our results suggest that split-belt adaptation can be interpreted as a process by which people learn to take advantage of mechanical work performed by an external device to improve economy.

Stroke survivors often have a slow, asymmetric walking pattern. They also walk with a higher metabolic cost than healthy, age-matched controls. It is often assumed that spatial-temporal asymmetries contribute to the increased metabolic cost of walking poststroke. However, elucidating this relationship is made challenging because of the interdependence between spatial-temporal asymmetries, walking speed, and metabolic cost. Here, we address these potential confounds by measuring speed-dependent changes in metabolic cost and implementing a recently developed approach to dissociate spatial versus temporal contributions to asymmetry in a sample of stroke survivors. We used expired gas analysis to compute the metabolic cost of transport (CoT) for each participant at 4 different walking speeds: self-selected speed, 80% and 120% of their self-selected speed, and their fastest comfortable speed. We also computed CoT for a sample of age- and gender-matched control participants who walked at the same speeds as their matched stroke survivor. Kinematic data were used to compute the magnitude of a number of variables characterizing spatial-temporal asymmetries. Across all speeds, stroke survivors had a higher CoT than controls. We also found that our sample of stroke survivors did not choose a self-selected speed that minimized CoT, contrary to typical observations in healthy controls. Multiple regression analyses revealed negative associations between speed and CoT and a positive association between asymmetries in foot placement relative to the trunk and CoT. These findings suggest that interventions designed to increase self-selected walking speed and reduce foot-placement asymmetries may be ideal for improving walking economy poststroke.

Composite materials often feature defects, particularly for composites which feature a complex microstructure, such as aligned discontinuous composites. This study uses an accurate but efficient virtual testing framework, which was used to predict the influence of defects on the structural performance of both hybrid and nonhybrid aligned discontinuous composites. Fibre vacancy defects were found to cause the strongest reduction in material properties, while hybridisation was found to be an effective means to reduce the influence of defects on the structural response.

Successful negotiation of obstacles during walking relies on the integration of visual information about the environment with ongoing locomotor commands. When information about the body and the environment is removed through occlusion of the lower visual field, individuals increase downward head pitch angle, reduce foot placement precision, and increase safety margins during crossing. However, whether these effects are mediated by loss of visual information about the lower extremities, the obstacle, or both remains to be seen. Here we used a fully immersive, virtual obstacle negotiation task to investigate how visual information about the lower extremities is integrated with information about the environment to facilitate skillful obstacle negotiation. Participants stepped over virtual obstacles while walking on a treadmill with one of three types of visual feedback about the lower extremities: no feedback, end-point feedback, and a link-segment model. We found that absence of visual information about the lower extremities led to an increase in the variability of leading foot placement after crossing. The presence of a visual representation of the lower extremities promoted greater downward head pitch angle during the approach to and subsequent crossing of an obstacle. In addition, having greater downward head pitch was associated with closer placement of the trailing foot to the obstacle, further placement of the leading foot after the obstacle, and higher trailing foot clearance. These results demonstrate that the fidelity of visual information about the lower extremities influences both feedforward and feedback aspects of visuomotor coordination during obstacle negotiation. NEW & NOTEWORTHY Here we demonstrate that visual information about the lower extremities is utilized for precise foot placement and control of safety margins during obstacle negotiation. We also found that when a visual representation of the lower extremities is present, this information is used in the online control of foot trajectory. Together, our results highlight how visual information about the body and the environment is integrated with motor commands for planning and online control of obstacle negotiation.

The ability to maintain dynamic balance in response to unexpected perturbations during walking is largely mediated by reactive control strategies. Reactive control during perturbed walking can be characterized by multiple metrics such as measures of whole-body angular momentum (WBAM), which capture the rotational dynamics of the body, and through Floquet analysis which captures the orbital stability of a limit cycle attractor. Recent studies have demonstrated that people with spatiotemporal asymmetries during gait have impaired control of whole-body dynamics as evidenced by higher peak-to-peak ranges of WBAM over the gait cycle. While this may suggest that spatiotemporal asymmetries could impair stability, no studies have quantified how direct modification of asymmetry influences reactive balance control. Here, we used a biofeedback paradigm that allows participants to systematically adopt different levels of step length asymmetry to test the hypothesis that walking asymmetrically impairs the reactive control of balance. In addition, we tested the hypothesis that perturbations to the non-dominant leg would cause less whole-body rotation due to its hypothesized role in weight support during walking. We characterized reactive control strategies in two ways. We first computed integrated angular momentum to characterize changes in whole-body configuration during multi-step responses to perturbations. We also computed the maximum Floquet multipliers (FMs) across the gait cycle, which represent the rate of convergence back to limit cycle behavior. Our results show that integrated angular momentum during the perturbation step and subsequent recovery steps, as well as the magnitude of maximum FMs over the gait cycle, do not change across levels of asymmetry. However, our results showed both limb-dependent and limb-independent responses to unexpected perturbations. Overall, our findings suggest that there is no causal relationship between step length asymmetry and impaired reactive control of balance in the absence of neuromotor impairments. Our approach could be used in future studies to determine if reducing asymmetries in populations with neuromotor impairments, such people post-stroke or amputees improves dynamic stability.

Walking is highly adaptable to new demands and environments. We have previously studied adaptation of locomotor patterns via a split-belt treadmill, where subjects learn to walk with one foot moving faster than the other. Subjects learn to adapt their walking pattern by changing the location (spatial) and time (temporal) of foot placement. Here we asked whether we can induce adaptation of a specific walking pattern when one limb does not “walk” but instead marches in place (i.e., marching-walking hybrid). The marching leg's movement is limited during the stance phase, and thus certain sensory signals important for walking may be reduced. We hypothesized that this would produce a spatial-temporal strategy different from that of normal split-belt adaptation. Healthy subjects performed two experiments to determine whether they could adapt their spatial-temporal pattern of step lengths during the marching-walking hybrid and whether the learning transfers to over ground walking. Results showed that the hybrid group did adapt their step lengths, but the time course of adaptation and deadaption was slower than that for the split-belt group. We also observed that the hybrid group utilized a mostly spatial strategy whereas the split-belt group utilized both spatial and temporal strategies. Surprisingly, we found no significant difference between the hybrid and split-belt groups in over ground transfer. Moreover, the hybrid group retained more of the learned pattern when they returned to the treadmill. These findings suggest that physical rehabilitation with this marching-walking paradigm on conventional treadmills may produce changes in symmetry comparable to what is observed during split-belt training.

In an earlier study of newly hatched chicks we reported that continuous bright light exposure throughout incubation accelerated locomotor development and continuous dark exposure delayed it, compared to less intense, intermittent light exposure. Commonly studied gait parameters indicated locomotor skill was similar across groups. However, dark incubated chicks walked with a greater step width, raising the possibility of differences in dynamic balance and control of forward progression. In this study, we established methods to retrospectively examine the previously published locomotor data for differences in lateral drift. We hypothesized that chicks incubated in darkness would exhibit more drift than chicks incubated in light. Analyses identified differences in forward progression between chicks incubated in the two extreme light conditions, supporting the study's hypothesis. We discuss the significance of our findings and potential design considerations for future studies of light-accelerated motor development in precocial and nonprecocial animals. © 2015 Wiley Periodicals, Inc. Dev Psychobiol 57: 459–469, 2015.

Background. Step length asymmetry (SLA) is a common hallmark of gait poststroke. Though conventionally viewed as a spatial deficit, SLA can result from differences in where the feet are placed relative to the body (step position strategy), the timing between foot strikes (step time strategy), or the velocity of the body relative to the feet (step velocity strategy). Objective. The goal of this study was to characterize the relative contributions of each of these strategies to SLA. Methods. We developed an analytical model that parses SLA into independent step position, step time, and step velocity contributions. This model was validated by reproducing SLA values for 25 healthy participants when their natural symmetric gait was perturbed on a split-belt treadmill moving at either a 2:1 or 3:1 belt-speed ratio. We then applied the validated model to quantify step position, step time, and step velocity contributions to SLA in 15 stroke survivors while walking at their self-selected speed. Results. SLA was predicted precisely by summing the derived contributions, regardless of the belt-speed ratio. Although the contributions to SLA varied considerably across our sample of stroke survivors, the step position contribution tended to oppose the other 2—possibly as an attempt to minimize overall SLA. Conclusions. Our results suggest that changes in where the feet are placed or changes in interlimb timing could be used as compensatory strategies to reduce overall SLA in stroke survivors. These results may allow clinicians and researchers to identify patient-specific gait abnormalities and personalize their therapeutic approaches accordingly.