Aberrant decision-making as a risk factor for falls in aging.

Neuromotor impairments resulting from natural aging and aging-related diseases are often accompanied by a heightened prevalence of falls and fall-related injuries. Conventionally, the study of factors contributing to falls focuses on intrinsic characteristics, such as sensorimotor processing delays and weakness, and extrinsic factors, such as environmental obstacles. However, the impact of these factors only becomes evident in response to people's decisions about how and where they will move in their environment. This decision-making process can be considered a behavioral risk factor, and it influences the extent to which a person engages in activities that place them near the limits of their capacity. While there are readily available tools for assessing intrinsic and extrinsic fall risk, our understanding of how to assess behavioral risk is limited. Measuring behavioral risk requires a systematic assessment of how people make decisions when walking in complex environments and how these decisions relate to their functional capacity. We propose that experimental methods and computational models derived from behavioral economics can stimulate the development of such assessments. Behavioral economics relies on theoretical models and empirical studies to characterize the factors that influence how people make decisions under risky conditions where a given decision can have variable outcomes. Applying a behavioral economic approach to walking can provide insight into how internal assessment of one's fall risk influences the tasks that one is willing to perform. Ultimately, these assessments will allow us to identify people who make choices that increase their likelihood of fall-related injuries.

Associations between asymmetry and reactive balance control during split-belt walking.

The adaptive control of walking is often studied on a split-belt treadmill, where people gradually reduce their step length asymmetries (SLAs) by modulating foot placement and timing. Although it is proposed that this adaptation may be driven in part by a desire to reduce instability, it is unknown if changes in asymmetry impact people's ability to maintain balance in response to destabilizing perturbations. Here, we used intermittent perturbations to determine if changes in SLA affect reactive balance control as measured by whole-body angular momentum (WBAM) in the sagittal and frontal planes. Sixteen neurotypical older adults (70.0 ± 5.3 years old; 6 males) walked on a treadmill at a 2:1 belt speed ratio with real-time visual feedback of their achieved and target step lengths. We used mixed-effects models to determine if there were associations between SLA or foot placement and WBAM during the applied perturbations. Walking with more positive SLAs was associated with small reductions in forward WBAM (p < 0.001 for fast and slow belts) but increased lateral WBAM (p = 0.045 for fast belt; p = 0.003 for slow belt) during perturbations. When participants walked with more positive SLAs, they shortened their foot placement on the slow belt, and this shortening was associated with moderate reductions in forward WBAM (p < 0.001) and small increases in lateral WBAM (p = 0.008) during slow-belt perturbations. Our findings suggest that spatiotemporal changes that occur during split-belt treadmill walking may improve sagittal-plane stability by reducing people's susceptibility to losses of balance, but this may come at the expense of frontal-plane stability.

Visuospatial Skills Explain Differences in the Ability to Use Propulsion Biofeedback Post-stroke.

BACKGROUND AND PURPOSE: Visual biofeedback can be used to help people post-stroke reduce biomechanical gait impairments. Using visual biofeedback engages an explicit, cognitively demanding motor learning process. Participants with better overall cognitive function are better able to use visual biofeedback to promote locomotor learning; however, which specific cognitive domains are responsible for this effect are unknown. We aimed to understand which cognitive domains were associated with performance during acquisition and immediate retention when using visual biofeedback to increase paretic propulsion in individuals post-stroke. METHODS: Participants post-stroke completed cognitive testing, which provided scores for different cognitive domains, including executive function, immediate memory, visuospatial/constructional skills, language, attention, and delayed memory. Next, participants completed a single session of paretic propulsion biofeedback training, where we collected treadmill-walking data for 20 min with biofeedback and 2 min without biofeedback. We fit separate regression models to determine if cognitive domain scores, motor impairment (measured with the lower-extremity Fugl-Meyer), and gait speed could explain propulsion error and variability during biofeedback use and recall error during immediate retention. RESULTS: Visuospatial/constructional skills and motor impairment best-explained propulsion error during biofeedback use (adjusted R 2  = 0.56, P = 0.0008), and attention best-explained performance variability (adjusted R 2  = 0.17, P = 0.048). Language skills best-explained recall error during immediate retention (adjusted R 2  = 0.37, P = 0.02). DISCUSSION AND CONCLUSIONS: These results demonstrate that specific cognitive domain impairments explain variability in locomotor learning outcomes in individuals with chronic stroke. This suggests that with further investigation, specific cognitive impairment information may be useful to predict responsiveness to interventions and personalize training parameters to facilitate locomotor learning.

Generalizability of foot placement control strategies during unperturbed and perturbed gait.

Control of foot placement is an essential strategy for maintaining balance during walking. During unperturbed, steady-state walking, foot placement can be accurately described as a linear function of the body's centre of mass (CoM) state at midstance. However, it is uncertain if this mapping from CoM state to foot placement generalizes to larger perturbations that could potentially cause falls. Recovery from these perturbations may require reactive control strategies not observed during unperturbed walking. Here, we used unpredictable changes in treadmill belt speed to assess the generalizability of foot placement mappings identified during unperturbed walking. We found that foot placement mappings generalized poorly from unperturbed to perturbed walking and differed for forward perturbation versus backward perturbation. We also used the singular value decomposition of the mapping matrix to reveal that people were more sensitive to backward versus forward perturbations. Together, these results indicate that a single linear mapping cannot describe the foot placement control during both forward and backward losses of balance induced by treadmill belt speed perturbations. Better characterization of human balance control strategies could improve our understanding of why different neuromotor disorders result in heightened fall risk and inform the design of controllers for balance-assisting devices.

NSF DARE-Transforming modeling in neurorehabilitation: Four threads for catalyzing progress.

We present an overview of the Conference on Transformative Opportunities for Modeling in Neurorehabilitation held in March 2023. It was supported by the Disability and Rehabilitation Engineering (DARE) program from the National Science Foundation's Engineering Biology and Health Cluster. The conference brought together experts and trainees from around the world to discuss critical questions, challenges, and opportunities at the intersection of computational modeling and neurorehabilitation to understand, optimize, and improve clinical translation of neurorehabilitation. We organized the conference around four key, relevant, and promising Focus Areas for modeling: Adaptation & Plasticity, Personalization, Human-Device Interactions, and Modeling 'In-the-Wild'. We identified four common threads across the Focus Areas that, if addressed, can catalyze progress in the short, medium, and long terms. These were: (i) the need to capture and curate appropriate and useful data necessary to develop, validate, and deploy useful computational models (ii) the need to create multi-scale models that span the personalization spectrum from individuals to populations, and from cellular to behavioral levels (iii) the need for algorithms that extract as much information from available data, while requiring as little data as possible from each client (iv) the insistence on leveraging readily available sensors and data systems to push model-driven treatments from the lab, and into the clinic, home, workplace, and community. The conference archive can be found at (dare2023.usc.edu). These topics are also extended by three perspective papers prepared by trainees and junior faculty, clinician researchers, and federal funding agency representatives who attended the conference.

Strategies to maximize lead tensile strength during extraction in three families of pacing leads.

BACKGROUND: Traction force that can be applied to an extraction rail is based on lead tensile strength, a product of its construction. A strong rail allows safe advancement of the extraction sheath. This study expands previous work providing strategies to optimize INGEVITY rail strength. OBJECTIVE: The purpose of this study was to measure forces that leads encounter in a simulated extraction procedure, determine lead response, and develop extraction recommendations for INGEVITY, INGEVITY+, and FINELINE II lead families. METHODS: Leads were positioned in a simulated right atrial appendage implant. Subsequent traction forces enabled evaluation of lead tensile strength and effectiveness of preparation/extraction techniques. RESULTS: Significant findings include (1) preserving the lead terminal pin did not decrease lead tensile strength and typically maximized it; (2) the weakest region is between the cathode and anode; (3) mid lead scar increases traction force tolerance until that scar is removed; and (4) optimal rail strength was observed using a multivenous approach with a femoral snare. Unique lead family findings include increased tensile strength of FINELINE II polyurethane vs silicone and INGEVITY active fixation vs passive fixation. CONCLUSION: This study teaches the implanting clinician there are specific extraction techniques available to improve the removal of leads that may be the best option for a patient's clinical needs. Bench testing demonstrates that lead construction drives lead behavior during an extraction. Preserving the lead terminal pin provides consistent and, in most cases, optimal rail strength. If clinically indicated, a multivenous approach using a femoral snare significantly increases rail strength and protects the vulnerable lead tip.

Multi-Site Identification and Generalization of Clusters of Walking Behaviors in Individuals With Chronic Stroke and Neurotypical Controls.

BACKGROUND: Walking patterns in stroke survivors are highly heterogeneous, which poses a challenge in systematizing treatment prescriptions for walking rehabilitation interventions. OBJECTIVES: We 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. METHODS: We gathered data from 81 post-stroke participants across 4 research sites and collected 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. RESULTS: We identified 4 stroke clusters: a fast and asymmetric cluster, a moderate speed and asymmetric cluster, a slow cluster with frontal plane force asymmetries, and a slow and symmetric cluster. We also identified a moderate speed and symmetric gait cluster composed of controls and participants post-stroke. The moderate speed and asymmetric stroke cluster did not generalize across sites. CONCLUSIONS: Although 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.

Generalizability of foot-placement control strategies during unperturbed and perturbed gait.

Control of foot placement is an essential strategy for maintaining balance during walking. During unperturbed, steady-state walking, foot placement can be accurately described as a linear function of the body's center of mass state at midstance. However, it is uncertain if this mapping from center of mass state to foot placement generalizes to larger perturbations that may be more likely to cause falls. These perturbations may cause balance disturbances and generate reactive control strategies not observed during unperturbed walking. Here, we used unpredictable changes in treadmill speed to assess the generalizability of foot placement mappings identified during unperturbed walking. We found that foot placement mappings generalized poorly from unperturbed to perturbed walking and differed for forward versus backward perturbations. We also used singular value decomposition of the mapping matrix to reveal that people were more sensitive to backward versus forward perturbations. Together, these results indicate that control of foot placement during losses of balance differs from the control strategies used during unperturbed walking. Better characterization of human balance control strategies could improve our understanding of why different neuromotor disorders result in heightened fall risk and inform the design of controllers for balance-assisting devices.

Reactive responses of the arms increase the Margins of Stability and decrease center of mass dynamics during a slip perturbation.

Although reactive arm motions are important in recovering from a slip event, the biomechanical influences of upper extremity motions during slipping are not clear. The purpose of the current study was to determine whether reactive arm motions during slip recovery leads to increased margins of stability (MoS), and decreased center of mass (CoM) velocity and excursion. Thirty-two participants were randomized into 2 conditions: arms free and arms constrained. Participants traversed a 10-meter walkway and were exposed to an unexpected slip while wearing a protective harness. Anterior-posterior and medial-lateral MoS, as well as the CoM excursion and velocity during the slip perturbation was quantified using a three-dimensional motion capture system. In the frontal plane, individuals with their arms unconstrained demonstrated greater MoS (0.06 ± 0.03 vs -0.01 ± 0.02 m, p < 0.01), decreased CoM excursion (0.05 ± 0.02 vs 0.08 ± 0.01 m, p = 0.015), and a reduced CoM velocity (0.07 ± 0.03 vs. 0.14 ± 0.02 m/s, p < 0.01) compared to individuals with their arms constrained. In the sagittal plane, individuals with their arms unconstrained demonstrated, decreased CoM excursion (0.83 ± 0.13 vs 1.14 ± 0.20 m, p < 0.01) reduced CoM velocity (1.71 ± 0.08 vs. 1.79 ± 0.07 m/s, p = 0.02), but no differences in margins of stability (0.89 ± 0.13 vs 0.94 ± 0.10 m, p = 0.32). Our findings demonstrate that arm motions during a slip perturbation act to restore balance by minimizing displacement and velocity of the body CoM during a slip event in the frontal plane.

Gait speed and individual characteristics are related to specific gait metrics in neurotypical adults.

Gait biofeedback is a well-studied strategy to reduce gait impairments such as propulsion deficits or asymmetric step lengths. With biofeedback, participants alter their walking to reach the desired magnitude of a specific parameter (the biofeedback target) with each step. Biofeedback of anterior ground reaction force and step length is commonly used in post-stroke gait training as these variables are associated with self-selected gait speed, fall risk, and the energy cost of walking. However, biofeedback targets are often set as a function of an individual's baseline walking pattern, which may not reflect the ideal magnitude of that gait parameter. Here we developed prediction models based on speed, leg length, mass, sex, and age to predict anterior ground reaction force and step length of neurotypical adults as a possible method for personalized biofeedback. Prediction of these values on an independent dataset demonstrated strong agreement with actual values, indicating that neurotypical anterior ground reaction forces can be estimated from an individual's leg length, mass, and gait speed, and step lengths can be estimated from individual's leg length, mass, age, sex, and gait speed. Unlike approaches that rely on an individual's baseline gait, this approach provides a standardized method to personalize gait biofeedback targets based on the walking patterns exhibited by neurotypical individuals with similar characteristics walking at similar speeds without the risk of over- or underestimating the ideal values that could limit feedback-mediated reductions in gait impairments.

Multi-site identification and generalization of clusters of walking behaviors in individuals with chronic stroke and neurotypical controls.

Background: Walking patterns in stroke survivors are highly heterogeneous, which poses a challenge in systematizing treatment prescriptions for walking rehabilitation interventions. Objective: We 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. Methods: We gathered data from 81 post-stroke participants across four research sites and collected 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. Results: We identified four stroke clusters: a fast and asymmetric cluster, a moderate speed and asymmetric cluster, a slow cluster with frontal plane force asymmetries, and a slow and symmetric cluster. We also identified a moderate speed and symmetric gait cluster composed of controls and participants post-stroke. The moderate speed and asymmetric stroke cluster did not generalize across sites. Conclusions: Although 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.

Reducing Racial Disparities in the Timeliness of Potential Lung Cancer Evaluation With a Novel Application-Supported Rapid Outpatient Diagnostic Program: An Interrupted Time Series Analysis.

INTRODUCTION: Rapid outpatient diagnostic programs (RODP) expedite lung cancer evaluation, but their impact on racial disparities in the timeliness of evaluation is less clear. MATERIALS AND METHODS: This was a retrospective analysis of the impact of an internally developed application-supported RODP on racial disparities in timely referral completion rates for patients with potential lung cancer at a safety-net healthcare system. An application screened referrals to pulmonology for indications of lung mass or nodule and presented relevant clinical information that enabled dedicated pulmonologists to efficiently review and triage cases according to urgency. Subsequent care coordination was overseen by a dedicated nurse coordinator. To determine the program's impact, we conducted an interrupted time series analysis of the monthly fraction of referrals completed within 30 days, stratified by those identified as White, non-Hispanic and those that were not (racial and ethnic minorities). RESULTS: There were 902 patients referred in the 2 years preintervention and 913 in the 2 years postintervention. Overall, the median age was 63 years, and 44.7% of referred patients were female. 44.2% were White, non-Hispanic while racial and ethnic minorities constituted 54.3%. After the intervention, there was a significant improvement in the proportion of referrals completed within 30 days (62.4% vs. 48.2%, P <.01). The interrupted time series revealed a significant immediate improvement in timely completion among racial and ethnic minorities (23%, P < .01) that was not reflected in the majority White, non-Hispanic subgroup (11%, not significant). CONCLUSION: A thoughtfully designed and implemented RODP reduced racial disparities in the timely evaluation of potential lung cancer.

Speed-dependent biomechanical changes vary across individual gait metrics post-stroke relative to neurotypical adults.

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.

Age-related changes in gait biomechanics and their impact on the metabolic cost of walking: Report from a National Institute on Aging workshop.

Changes in old age that contribute to the complex issue of an increased metabolic cost of walking (mass-specific energy cost per unit distance traveled) in older adults appear to center at least in part on changes in gait biomechanics. However, age-related changes in energy metabolism, neuromuscular function and connective tissue properties also likely contribute to this problem, of which the consequences are poor mobility and increased risk of inactivity-related disease and disability. The U.S. National Institute on Aging convened a workshop in September 2021 with an interdisciplinary group of scientists to address the gaps in research related to the mechanisms and consequences of changes in mobility in old age. The goal of the workshop was to identify promising ways to move the field forward toward improving gait performance, decreasing energy cost, and enhancing mobility for older adults. This report summarizes the workshop and brings multidisciplinary insight into the known and potential causes and consequences of age-related changes in gait biomechanics. We highlight how gait mechanics and energy cost change with aging, the potential neuromuscular mechanisms and role of connective tissue in these changes, and cutting-edge interventions and technologies that may be used to measure and improve gait and mobility in older adults. Key gaps in the literature that warrant targeted research in the future are identified and discussed.

Impairments in the mechanical effectiveness of reactive balance control strategies during walking in people post-stroke.

People post-stroke have an increased risk of falls compared to neurotypical individuals, partly resulting from an inability to generate appropriate reactions to restore balance. However, few studies investigated the effect of paretic deficits on the mechanics of reactive control strategies following forward losses of balance during walking. Here, we characterized the biomechanical consequences of reactive control strategies following perturbations induced by the treadmill belt accelerations. Thirty-eight post-stroke participants and thirteen age-matched and speed-matched neurotypical participants walked on a dual-belt treadmill while receiving perturbations that induced a forward loss of balance. We computed whole-body angular momentum and angular impulse using segment kinematics and reaction forces to quantify the effect of impulse generation by both the leading and trailing limbs in response to perturbations in the sagittal plane. We found that perturbations to the paretic limb led to larger increases in forward angular momentum during the perturbation step than perturbations to the non-paretic limb or to neurotypical individuals. To recover from the forward loss of balance, neurotypical individuals coordinated reaction forces generated by both legs to decrease the forward angular impulse relative to the pre-perturbation step. They first decreased the forward pitch angular impulse during the perturbation step. Then, during the first recovery step, they increased the backward angular impulse by the leading limb and decreased the forward angular impulse by the trailing limb. In contrast to neurotypical participants, people post-stroke did not reduce the forward angular impulse generated by the stance limb during the perturbed step. They also did not increase leading limb angular impulse or decrease the forward trailing limb angular impulse using their paretic limb during the first recovery step. Lastly, post-stroke individuals who scored poorer on clinical assessments of balance and had greater motor impairment made less use of the paretic limb to reduce forward momentum. Overall, these results suggest that paretic deficits limit the ability to recover from forward loss of balance. Future perturbation-based balance training targeting reactive stepping response in stroke populations may benefit from improving the ability to modulate paretic ground reaction forces to better control whole-body dynamics.

Patterns of asymmetry and energy cost generated from predictive simulations of hemiparetic gait.

Hemiparesis, defined as unilateral muscle weakness, often occurs in people post-stroke or people with cerebral palsy, however it is difficult to understand how this hemiparesis affects movement patterns as it often presents alongside a variety of other neuromuscular impairments. Predictive musculoskeletal modeling presents an opportunity to investigate how impairments affect gait performance assuming a particular cost function. Here, we use predictive simulation to quantify the spatiotemporal asymmetries and changes to metabolic cost that emerge when muscle strength is unilaterally reduced and how reducing spatiotemporal symmetry affects metabolic cost. We modified a 2-D musculoskeletal model by uniformly reducing the peak isometric muscle force unilaterally. We then solved optimal control simulations of walking across a range of speeds by minimizing the sum of the cubed muscle excitations. Lastly, we ran additional optimizations to test if reducing spatiotemporal asymmetry would result in an increase in metabolic cost. Our results showed that the magnitude and direction of effort-optimal spatiotemporal asymmetries depends on both the gait speed and level of weakness. Also, the optimal speed was 1.25 m/s for the symmetrical and 20% weakness models but slower (1.00 m/s) for the 40% and 60% weakness models, suggesting that hemiparesis can account for a portion of the slower gait speed seen in people with hemiparesis. Modifying the cost function to minimize spatiotemporal asymmetry resulted in small increases (~4%) in metabolic cost. Overall, our results indicate that spatiotemporal asymmetry may be optimal for people with hemiparesis. Additionally, the effect of speed and the level of weakness on spatiotemporal asymmetry may help explain the well-known heterogenous distribution of spatiotemporal asymmetries observed in the clinic. Future work could extend our results by testing the effects of other neuromuscular impairments on optimal gait strategies, and therefore build a more comprehensive understanding of the gait patterns observed in clinical populations.

Manual stabilization reveals a transient role for balance control during locomotor adaptation.

A fundamental feature of human locomotor control is the need to adapt walking patterns 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 spatiotemporal asymmetry. Here, we aim to understand the role of balance control 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 whole body angular momentum, we also measured segmental angular momenta and the coefficient of 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 segments and a reduction in the coefficient of cancellation. Holding on to a handrail reduced the perturbation to asymmetry during the early phase of adaptation and resulted in a smaller aftereffect during early postadaptation. 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.NEW & NOTEWORTHY We investigated the role of dynamic balance during adaptation to a split-belt treadmill by measuring whole body angular momentum with or without holding on to a handrail. The initial step length asymmetry and associations between balance and asymmetry reduced when holding on to a handrail during early adaptation. These findings indicate that dynamic balance mostly contributes to the initial phase of adaptation when people are exposed to an asymmetric walking constraint.

The choice of reference point for computing sagittal plane angular momentum affects inferences about dynamic balance.

Background: Measures of whole-body angular momentum in the sagittal plane are commonly used to characterize dynamic balance during human walking. To compute angular momentum, one must specify a reference point about which momentum is calculated. Although biomechanists primarily compute angular momentum about the center of mass (CoM), momentum-based controllers for humanoid robots often use the center of pressure. Here, we asked if the choice of the reference point influences interpretations of how dynamic balance is controlled in the sagittal plane during perturbed walking. Methods: Eleven healthy young individuals walked on a dual-belt treadmill at their self-selected speed. Balance disturbances were generated by treadmill accelerations of varying magnitudes and directions. We computed angular momentum about two reference points: (1) the CoM or (2) the leading edge of the base of support and then projected it along the mediolateral axes that pass through either of the reference points as the sagittal plane angular momentum. We also performed principal component analysis to determine if the choice of reference point influences our interpretations of how intersegmental coordination patterns contribute to perturbation recovery. Results: We found that the peak angular momentum was correlated with perturbation amplitude and the slope of this relationship did not differ between reference points. One advantage of using a reference point at the CoM is that one can easily determine how the momenta from contralateral limbs, such as the left and right legs, offset one another to regulate the whole-body angular momentum. Alternatively, analysis of coordination patterns referenced to the leading edge of the base of support may provide more insight into the inverted-pendulum dynamics of walking during responses to sudden losses of balance.

General variability leads to specific adaptation toward optimal movement policies.

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.

Using Bayesian inference to estimate plausible muscle forces in musculoskeletal models.

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.