Multiple walking speed-frequency relations are predicted by constrained optimization

On the relation between gait speed and gait cycle duration for walking on even ground

Gait models and reference motions are essential for the objective assessment of walking patterns and therapy progress, as well as research in the field of wearable robotics and rehabilitation devices in general. A human can achieve a desired gait speed by adjusting stride length and/or stride frequency. It is hypothesized that sex, age, and physique of a person have a significant influence on the combination of these parameters. A mathematical description of the relation between gait speed and its determinants is presented in the form of a parameterized analytic function. Based on the statistical significance of the parameters, three models are derived. The first two models are valid for slow to fast walking, which is defined as the interval of approximately 0.6-2.0ms-1, assuming a linear relation of gait speed and stride length, and a non-linear relation of gait speed and stride duration, respectively. The third model is valid for a defined range of walking speed centered at a certain (preferred or spontaneous) gait speed. The latter assumes a constant walk ratio, i.e. the ratio between step or stride length and step or stride frequency, and is recommended for walking at a speed of 1.0-1.6ms-1. On the basis of a large pool of gait datasets, regression coefficients with significance for age and/or body mass index are identified. The presented models allow to estimate the gait cycle duration based on gait speed, sex, age and body mass index of healthy persons walking on even ground.

Holographic Hintways: A systems feasibility and usability study of augmented reality cueing for gait adaptation

BACKGROUND

Through providing on-demand visual and auditory cues while walking,augmented reality (AR) can theoretically cue spatiotemporal gait adaptations in, populations such as those with Parkinson's disease. However, given the novelty of the, technology, the type and extent of gait adaptations in response to such a cueing, system are unknown. Before such systems can be incorporated into rehabilitation, approaches, it is important to understand how people interact with the technology.

RESEARCH QUESTIONS

What are the effects of visual and auditory cues delivered, through AR on spatiotemporal walking patterns and variability in a healthy, young, population? Is there a relationship between system usability and gait variability?

, METHODS

Twenty healthy, young participants walked in four different cueing conditions using an AR headset: No Cues (NC) (i.e., natural gait), Auditory (A), Visual (V), and Auditory + Visual (AV). Inertial measurement units recorded spatiotemporal gait data at 200 Hz, a System Usability Survey was administered afterward, and linear regression models were developed to examine whether gait variability is predictive of system usability.

RESULTS

All cueing conditions exhibited a significantly slower cadence compared to, NC trials. Cadence variability was significantly higher for A trials compared to V and, NC. V trials exhibited significantly decreased stride lengths compared to NC. Increased, reported system usability was significantly correlated with decreased stance phase, time variability across A trials.

SIGNIFICANCE

Our findings support that holographic spatial-visual and auditory cues, are promising to evoke spatiotemporal gait adaptations. Results also support the, notion that the type of system and cue delivery design may impact gait outcomes.,Before an AR cueing system can be applied to a specific population in future, interventions, a more holistic approach towards finding the relationship between this, technology and its users is needed.

Physiological, perceptual, and biomechanical differences between treadmill and overground walking in healthy adults: A systematic review and meta-analysis

This systematic review and meta-analysis aims to compare physiological, perceptual and biomechanical outcomes between walking on a treadmill and overground surfaces. Five databases (CINAHL, EMBASE, MEDLINE, SPORTDiscus, Web of Science) were searched until September 2022. Included studies needed to be a crossover design comparing biomechanical, physiological, or perceptual measures between motorised-treadmill and overground walking in healthy adults (18-65 years) walking at the same speed (<5% difference). The quality of studies were assessed using a modified Downs and Black Quality Index. Meta-analyses were performed to determine standardised mean difference ± 95% confidence intervals for all main outcome measures. Fifty-five studies were included with 1,005 participants. Relative oxygen consumption (standardised mean difference [95% confidence interval] 0.38 [0.14,0.63]) and cadence (0.22 [0.06,0.38]) are higher during treadmill walking. Whereas stride length (-0.36 [-0.62,-0.11]) and step length (-0.52 [-0.98,-0.06]) are lower during treadmill walking. Most kinetic variables are different between surfaces. The oxygen consumption, spatiotemporal and kinetic differences on the treadmill may be an attempt to increase stability due to the lack of control, discomfort and familiarity on the treadmill. Treadmill construction including surface stiffness and motor power are likely additional constraints that need to be considered and require investigation. This research was supported by an Australian Government Research Training Program (RTP) scholarship. Protocol registration is CRD42020208002 (PROSPERO International Prospective Register of Systematic Reviews) in October 2020.

Australia and New Zealand Clinical Motion Analysis Group (ANZ-CMAG) clinical practice recommendations

Clinical motion analysis involves quantitative measurement of gait patterns to identify gait anomalies that currently or have the potential to impact function, activities of daily living and participation. Clinical motion analysis services are equipped with motion capture technology and comprise specialised staff who deliver 3-dimensional motion analysis services to children and adults who present with varying levels of gait impairment. Data is then used to inform intervention recommendations to clinicians with a view to maintaining independent, functional and pain free walking (or appropriate mobility). The ANZ-CMAG (established in 2013) identified a need to establish recommendations to assist in standardising practice guidelines for both current and new clinical motion analysis services within the region. The group serves to promote collaboration between services in quality assurance processes, clinical practices, data sets and research activities. The clinical practice recommendations described in this paper cover: i) requirements for a motion analysis service (including staffing, facilities and equipment), ii) patient assessments (requirements, clinical information and data gathered, reporting and interpretation of patient data), iii) quality assurance processes (including motion capture system / biomechanical models & limitations, marker placement, data storage / record keeping, creation of normative dataset); iv) helpful resources. Better outcomes for children and adults with gait deviations is dependent upon accurate measurement and evaluation of walking and requires input from multidisciplinary clinical teams with specialist knowledge and skills. The ANZ-CMAG hopes these clinical practice recommendations are beneficial to motion analysis services with an aim to improve clinical practices, patient outcomes, and support research collaboration.

Inertial-Sensor-Based Monitoring of Sample Entropy and Peak Frequency Changes in Treadmill Walking during Recovery after Total Knee Arthroplasty

This study aimed to investigate whether sample entropy (SEn) and peak frequency values observed in treadmill walking could provide physical therapists valuable insights into gait rehabilitation following total knee arthroplasty (TKA). It was recognized that identifying movement strategies that during rehabilitation are initially adaptive but later start to hamper full recovery is critical to meet the clinical goals and minimize the risk of contralateral TKA. Eleven TKA patients were asked to perform clinical walking tests and a treadmill walking task at four different points in time (pre-TKA, 3, 6, and 12 months post-TKA). Eleven healthy peers served as the reference group. The movements of the legs were digitized with inertial sensors and SEn and peak frequency of the recorded rotational velocity-time functions were analyzed in the sagittal plane. SEn displayed a systematic increase during recovery in TKA patients (p < 0.001). Furthermore, lower peak frequency (p = 0.01) and sample entropy (p = 0.028) were found during recovery for the TKA leg. Movement strategies that initially are adaptive, and later hamper recovery, tend to diminish after 12 months post-TKA. It is concluded that inertial-sensor-based SEn and peak frequency analyses of treadmill walking enrich the assessment of movement rehabilitation after TKA.

Selection of gait parameters during constrained walking

It is commonly thought that at prescribed speeds humans choose gait parameters that minimize the cost of transportation. However, it is unclear whether and how the relationship between step length and step frequency is affected by the additional physiological factors caused by constraints. We performed a series of experiments to understand the selection of gait parameters under different constraints from a probabilistic perspective. First, we show that the effect of constraining step length on step frequency (i.e., monotonically decrease, Experiment I) is different from the effect of constraining step frequency on step length (i.e., inverted-U, Experiment II). Using the results from Experiment I and II, we summarized the marginal distribution of step length and step frequency and built their joint distribution in a probabilistic model. The probabilistic model predicts the selection of gait parameters by achieving the maximum probability of joint distribution of step length and step frequency. In Experiment III, the probabilistic model could well predict gait parameters at prescribed speeds, and it is similar to minimizing the cost of transportation. Finally, we show that the distribution of step length and step frequency were completely different between constrained and non-constrained walking. We argue that constraints in walking are major factors determining how humans choose gait parameters due to their involvement of mediators, i.e., attention or active control. Using the probabilistic model to account for gait parameters has an advantage compared with fixed-parameter models in that it can still include the effect of hidden mechanical, neurophysiological, or psychological variables by grouping them into distribution curves.

Recruit-aged adults may preferentially weight task goals over deleterious cost functions during short duration loaded and imposed gait tasks

Optimal motor control that is stable and adaptable to perturbation is reflected in the temporal arrangement and regulation of gait variability. Load carriage and forced-marching are common military relevant perturbations to gait that have been implicated in the high incidence of musculoskeletal injuries in military populations. We investigated the interactive effects of load magnitude and locomotion pattern on motor variability, stride regulation and spatiotemporal complexity during gait in recruit-aged adults. We further investigated the influences of sex and task duration. Healthy adults executed trials of running and forced-marching with and without loads at 10% above their gait transition velocity. Spatiotemporal parameters were analyzed using a goal equivalent manifold approach. With load and forced-marching, individuals used a greater array of motor solutions to execute the task goal (maintain velocity). Stride-to-stride regulation became stricter as the task progressed. Participants exhibited optimal spatiotemporal complexity with significant but not meaningful differences between sexes. With the introduction of load carriage and forced-marching, individuals relied on a strategy that maximizes and regulates motor solutions that achieve the task goal of velocity specifically but compete with other task functions. The appended cost penalties may have deleterious effects during prolonged execution, potentially increasing the risk of musculoskeletal injuries.

The energetic effect of hip flexion and retraction in walking at different speeds: a modeling study

In human walking, power for propulsion is generated primarily via ankle and hip muscles. The addition of a 'passive' hip spring to simple bipedal models appears more efficient than using only push-off impulse, at least, when hip spring associated energetic costs are not considered. Hip flexion and retraction torques, however, are not 'free', as they are produced by muscles demanding metabolic energy. Studies evaluating the inclusion of hip actuation costs, especially during the swing phase, and the hip actuation's energetic benefits are few and far between. It is also unknown whether these possible benefits/effects may depend on speed. We simulated a planar flat-feet model walking stably over a range of speeds. We asked whether the addition of independent hip flexion and retraction remains energetically beneficial when considering work-based metabolic cost of transport (MCOT) with different efficiencies of doing positive and negative work. We found asymmetric hip actuation can reduce the estimated MCOT relative to ankle actuation by up to 6%, but only at medium speeds. The corresponding optimal strategy is zero hip flexion and some hip retraction actuation. The reason for this reduced MCOT is that the decrease in collision loss is larger than the associated increase in hip negative work. This leads to a reduction in total positive mechanical work, which results in an overall lower MCOT. Our study shows how ankle actuation, hip flexion, and retraction actuation can be coordinated to reduce MCOT.

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.

Running in the wild: Energetics explain ecological running speeds

Human runners have long been thought to have the ability to consume a near-constant amount of energy per distance traveled, regardless of speed, allowing speed to be adapted to particular task demands with minimal energetic consequence.^1-3 However, recent and more precise laboratory measures indicate that humans may in fact have an energy-optimal running speed.^4-6 Here, we characterize runners' speeds in a free-living environment and determine if preferred speed is consistent with task- or energy-dependent objectives. We analyzed a large-scale dataset of free-living runners, which was collected via a commercial fitness tracking device, and found that individual runners preferred a particular speed that did not change across commonly run distances. We compared the data from lab experiments that measured participants' energy-optimal running speeds with the free-living preferred speeds of age- and gender-matched runners in our dataset and found the speeds to be indistinguishable. Human runners prefer a particular running speed that is independent of task distance and is consistent with the objective of minimizing energy expenditure. Our findings offer an insight into the biological objectives that shape human running preferences in the real world-an important consideration when examining human ecology or creating training strategies to improve performance and prevent injury.

Cultural variation in running techniques among non-industrial societies

Research among non-industrial societies suggests that body kinematics adopted during running vary between groups according to the cultural importance of running. Among groups in which running is common and an important part of cultural identity, runners tend to adopt what exercise scientists and coaches consider to be good technique for avoiding injury and maximising performance. In contrast, among groups in which running is not particularly culturally important, people tend to adopt suboptimal technique. This paper begins by describing key elements of good running technique, including landing with a forefoot or midfoot strike pattern and leg oriented roughly vertically. Next, we review evidence from non-industrial societies that cultural attitudes about running associate with variation in running techniques. Then, we present new data from Tsimane forager–horticulturalists in Bolivia. Our findings suggest that running is neither a common activity among the Tsimane nor is it considered an important part of cultural identity. We also demonstrate that when Tsimane do run, they tend to use suboptimal technique, specifically landing with a rearfoot strike pattern and leg protracted ahead of the knee (called overstriding). Finally, we discuss processes by which culture might influence variation in running techniques among non-industrial societies, including self-optimisation and social learning.

New evidence from the Tsimane underscores that running techniques vary between societies according to the cultural importance of running

Analysing gait patterns in degenerative lumbar spine diseases: a literature review

OBJECTIVES

To collate the current state of knowledge and explore differences in the spatiotemporal gait patterns of degenerative lumbar spine diseases: lumbar spinal stenosis (LSS), lumbar disc herniation (LDH) and low back pain (LBP).

BACKGROUND

LBP is common presenting complaint with degenerative lumbar spine disease being a common cause. In particular, the gait patterns of LSS, LDH and mechanical-type (facetogenic and discogenic) LBP is not established.

METHODS

A search of the literature was conducted to determine the changes in spatial and temporal gait metrics involved with each type of degenerative lumbar spine disease. A search of databases including Medline, Embase and PubMed from their date of inception to April 18th, 2021 was performed to screen, review and identify relevant studies for qualitative synthesis. Seventeen relevant studies were identified for inclusion in the present review. Of these, 5 studies investigated gait patterns in LSS, 10 studies investigated LBP and 2 studies investigated LDH. Of these, 4 studies employed wearable accelerometry in LSS (2 studies) and LBP (2 studies).

CONCLUSIONS

Previous studies suggest degenerative diseases of the lumbar spine have unique patterns of gait deterioration. LSS is characterised by asymmetry and variability. Spatiotemporal gait deterioration in gait velocity, cadence with increased double-support duration and gait variability are distinguishing features in LDH. LBP involves marginal abnormalities in temporal and spatial gait metrics. Previous studies suggest degenerative diseases of the lumbar spine have unique patterns of gait deterioration. Gait asymmetry and variability, may be relevant metrics for distinguishing between the gait profiles of lumbar spine diseases.

Modeling toes contributes to realistic stance knee mechanics in three-dimensional predictive simulations of walking

Physics-based predictive simulations have been shown to capture many salient features of human walking. Yet they often fail to produce realistic stance knee and ankle mechanics. While the influence of the performance criterion on the predicted walking pattern has been previously studied, the influence of musculoskeletal mechanics has been less explored. Here, we investigated the influence of two mechanical assumptions on the predicted walking pattern: the complexity of the foot model and the stiffness of the Achilles tendon. We found, through three-dimensional muscle-driven predictive simulations of walking, that modeling the toes, and thus using two-segment instead of single-segment foot models, contributed to robustly eliciting physiological stance knee flexion angles, knee extension torques, and knee extensor activity. Modeling toes also slightly decreased the first vertical ground reaction force peak, increasing its agreement with experimental data, and improved stance ankle kinetics. It nevertheless slightly worsened predictions of ankle kinematics. Decreasing Achilles tendon stiffness improved the realism of ankle kinematics, but there remain large discrepancies with experimental data. Overall, this simulation study shows that not only the performance criterion but also mechanical assumptions affect predictive simulations of walking. Improving the realism of predictive simulations is required for their application in clinical contexts. Here, we suggest that using more complex foot models might contribute to such realism.

Comparing optimized exoskeleton assistance of the hip, knee, and ankle in single and multi-joint configurations

Exoskeletons that assist the hip, knee, and ankle joints have begun to improve human mobility, particularly by reducing the metabolic cost of walking. However, direct comparisons of optimal assistance of these joints, or their combinations, have not yet been possible. Assisting multiple joints may be more beneficial than the sum of individual effects, because muscles often span multiple joints, or less effective, because single-joint assistance can indirectly aid other joints. In this study, we used a hip-knee-ankle exoskeleton emulator paired with human-in-the-loop optimization to find single-joint, two-joint, and whole-leg assistance that maximally reduced the metabolic cost of walking. Hip-only and ankle-only assistance reduced the metabolic cost of walking by 26 and 30% relative to walking in the device unassisted, confirming that both joints are good targets for assistance (N = 3). Knee-only assistance reduced the metabolic cost of walking by 13%, demonstrating that effective knee assistance is possible (N = 3). Two-joint assistance reduced the metabolic cost of walking by between 33 and 42%, with the largest improvements coming from hip-ankle assistance (N = 3). Assisting all three joints reduced the metabolic cost of walking by 50%, showing that at least half of the metabolic energy expended during walking can be saved through exoskeleton assistance (N = 4). Changes in kinematics and muscle activity indicate that single-joint assistance indirectly assisted muscles at other joints, such that the improvement from whole-leg assistance was smaller than the sum of its single-joint parts. Exoskeletons can assist the entire limb for maximum effect, but a single well-chosen joint can be more efficient when considering additional factors such as weight and cost.

The Cost of Gait Slowness: Can Persons with Parkinson's Disease Save Energy by Walking Faster?

BACKGROUND

Gait slowing is a common feature of Parkinson's disease (PD). Many therapies aim to improve gait speed in persons with PD, but goals are often imprecise. How fast should each patient walk? And how do persons with PD benefit from walking faster? There is an important need to understand how walking speed affects fundamental aspects of gait-including energy cost and stability-that could guide individualized therapy decisions in persons with PD.

OBJECTIVE

We investigated how changes in walking speed affected energy cost and spatiotemporal gait parameters in persons with PD. We compared these effects between dopaminergic medication states and to those observed in age-matched control participants.

METHODS

Twelve persons with PD and twelve control participants performed treadmill walking trials spanning at least five different speeds (seven speeds were desired, but not all participants could walk at the fastest speeds). Persons with PD participated in two walking sessions on separate days (once while optimally medicated, once after 12-hour withdrawal from dopaminergic medication). We measured kinematic and metabolic data across all trials.

RESULTS

Persons with PD significantly reduced energy cost by walking faster than their preferred speeds. This held true across medication conditions and was not observed in control participants. The patient-specific walking speeds that reduced energy cost did not significantly affect gait variability metrics (used as proxies for gait stability).

CONCLUSION

The gait slowing that occurs with PD results in energetically suboptimal walking. Rehabilitation strategies that target patient-specific increases in walking speed could result in a less effortful gait.

Energy optimization during walking involves implicit processing

Gait adaptations, in response to novel environments, devices or changes to the body, can be driven by the continuous optimization of energy expenditure. However, whether energy optimization involves implicit processing (occurring automatically and with minimal cognitive attention), explicit processing (occurring consciously with an attention-demanding strategy) or both in combination remains unclear. Here, we used a dual-task paradigm to probe the contributions of implicit and explicit processes in energy optimization during walking. To create our primary energy optimization task, we used lower-limb exoskeletons to shift people's energetically optimal step frequency to frequencies lower than normally preferred. Our secondary task, designed to draw explicit attention from the optimization task, was an auditory tone discrimination task. We found that adding this secondary task did not prevent energy optimization during walking; participants in our dual-task experiment adapted their step frequency toward the optima by an amount and at a rate similar to participants in our previous single-task experiment. We also found that performance on the tone discrimination task did not worsen when participants were adapting toward energy optima; accuracy scores and reaction times remained unchanged when the exoskeleton altered the energy optimal gaits. Survey responses suggest that dual-task participants were largely unaware of the changes they made to their gait during adaptation, whereas single-task participants were more aware of their gait changes yet did not leverage this explicit awareness to improve gait adaptation. Collectively, our results suggest that energy optimization involves implicit processing, allowing attentional resources to be directed toward other cognitive and motor objectives during walking.

Deep reinforcement learning for modeling human locomotion control in neuromechanical simulation

Modeling human motor control and predicting how humans will move in novel environments is a grand scientific challenge. Researchers in the fields of biomechanics and motor control have proposed and evaluated motor control models via neuromechanical simulations, which produce physically correct motions of a musculoskeletal model. Typically, researchers have developed control models that encode physiologically plausible motor control hypotheses and compared the resulting simulation behaviors to measurable human motion data. While such plausible control models were able to simulate and explain many basic locomotion behaviors (e.g. walking, running, and climbing stairs), modeling higher layer controls (e.g. processing environment cues, planning long-term motion strategies, and coordinating basic motor skills to navigate in dynamic and complex environments) remains a challenge. Recent advances in deep reinforcement learning lay a foundation for modeling these complex control processes and controlling a diverse repertoire of human movement; however, reinforcement learning has been rarely applied in neuromechanical simulation to model human control. In this paper, we review the current state of neuromechanical simulations, along with the fundamentals of reinforcement learning, as it applies to human locomotion. We also present a scientific competition and accompanying software platform, which we have organized to accelerate the use of reinforcement learning in neuromechanical simulations. This “Learn to Move” competition was an official competition at the NeurIPS conference from 2017 to 2019 and attracted over 1300 teams from around the world. Top teams adapted state-of-the-art deep reinforcement learning techniques and produced motions, such as quick turning and walk-to-stand transitions, that have not been demonstrated before in neuromechanical simulations without utilizing reference motion data. We close with a discussion of future opportunities at the intersection of human movement simulation and reinforcement learning and our plans to extend the Learn to Move competition to further facilitate interdisciplinary collaboration in modeling human motor control for biomechanics and rehabilitation research

Cost of transport at preferred walking speeds are minimized while walking on moderately steep incline surfaces

Research has shown that preferred walking speed results in a minimization of the cost of transport on flat surfaces. However, it has also been shown that over non-smooth surfaces other variables, such as stability, are necessary for task completion increasing the cost of transport. The purpose of this research was to investigate the effect of incline walking on the cost of transport, assessing the effect of raising the center of mass as a potential variable affecting preferred walking speed, such that the cost of transport is no longer minimized. 12 healthy, college-aged male participants completed walking trials on a treadmill at inclines of 0%, 5%, 10%, 15%, and 20% at three different continuous speeds (1mph, 2mph and 3mph) and a preferred walking speed for 4-5 min. Cost of transport was calculated using the oxygen consumption collected during the last minute of each stage. Up to 20% incline, the cost of transport was lowest on each incline for the preferred walking speed trials. On inclines greater than 20%, many participants were unable to complete the task with respiratory exchange ratios less than 1.0. We conclude that inclines up to 20% do not induce an alternative challenge affecting the established relationship that humans prefer to walk at speeds that minimize the cost of transport despite the increased need to raise the center of mass.

Evaluating the energetics of entrainment in a human-machine coupled oscillator system

During locomotion, humans sometimes entrain (i.e. synchronize) their steps to external oscillations: e.g. swaying bridges, tandem walking, bouncy harnesses, vibrating treadmills, exoskeletons. Previous studies have discussed the role of nonlinear oscillators (e.g. central pattern generators) in facilitating entrainment. However, the energetics of such interactions are unknown. Given substantial evidence that humans prioritize economy during locomotion, we tested whether reduced metabolic expenditure is associated with human entrainment to vertical force oscillations, where frequency and amplitude were prescribed via a custom mechatronics system during walking. Although metabolic cost was not significantly reduced during entrainment, individuals expended less energy when the oscillation forces did net positive work on the body and roughly selected phase relationships that maximize positive work. It is possible that individuals use mechanical cues to infer energy cost and inform effective gait strategies. If so, an accurate prediction may rely on the relative stability of interactions with the environment. Our results suggest that entrainment occurs over a wide range of oscillation parameters, though not as a direct priority for minimizing metabolic cost. Instead, entrainment may act to stabilize interactions with the environment, thus increasing predictability for the effective implementation of internal models that guide energy minimization.

Evaluating cost function criteria in predicting healthy gait

Accurate predictive simulations of human gait rely on optimisation criteria to solve the system's redundancy. Defining such criteria is challenging, as the objectives driving the optimization of human gait are unclear. This study evaluated how minimising various physiologically-based criteria (i.e., cost of transport, muscle activity, head stability, foot-ground impact, and knee ligament use) affects the predicted gait, and developed and evaluated a combined, weighted cost function tuned to predict healthy gait. A generic planar musculoskeletal model with 18 Hill-type muscles was actuated using a reflex-based, parameterized controller. First, the criteria were applied into the base simulation framework separately. The gait pattern predicted by minimising each criterion was compared to experimental data of healthy gait using coefficients of determination (R²) and root mean square errors (RMSE) averaged over all biomechanical variables. Second, the optimal weighted combined cost function was created through stepwise addition of the criteria. Third, performance of the resulting combined cost function was evaluated by comparing the predicted gait to a simulation that was optimised solely to track experimental data. Optimising for each of the criteria separately showed their individual contribution to distinct aspects of gait (overall R²: 0.37-0.56; RMSE: 3.47-4.63 SD). An optimally weighted combined cost function provided improved overall agreement with experimental data (overall R²: 0.72; RMSE: 2.10 SD), and its performance was close to what is maximally achievable for the underlying simulation framework. This study showed how various optimisation criteria contribute to synthesising gait and that careful weighting of them is essential in predicting healthy gait.

The metabolic and mechanical consequences of altered propulsive force generation in walking

Older adults walk with greater metabolic energy consumption than younger for reasons that are not well understood. We suspect that a distal-to-proximal redistribution of leg muscle demand, from muscles spanning the ankle to those spanning the hip, contributes to greater metabolic energy costs. Recently, we found that when younger adults using biofeedback target smaller than normal peak propulsive forces (F_P), they do so via a similar redistribution of leg muscle demand during walking. This alludes to an experimental paradigm that emulates characteristics of elderly gait independent of other age-related changes relevant to metabolic energy cost. Thus, our purpose was to quantify the metabolic and limb- and joint-level mechanical energy costs associated with modulating propulsive forces during walking in younger adults. Walking with larger F_P increased net metabolic power by 47% (main effect, p = 0.001), which was accompanied by small by relatively uniform increases in hip, knee, and ankle joint power and which correlated with total joint power (R² = 0.151, p = 0.019). Walking with smaller F_P increased net metabolic power by 58% (main effect, p < 0.001), which was accompanied by higher step frequencies and increased total joint power due to disproportionate increases in hip joint power. Increases in hip joint power when targeting smaller than normal F_P accounted for more than 65% of the variance in the measured changes in net metabolic power. Our findings suggest that walking with a diminished push-off exacts a metabolic penalty because of higher step frequencies and more total limb work due to an increased demand on proximal leg muscles.

Lower limb kinematic, kinetic, and EMG data from young healthy humans during walking at controlled speeds

Understanding the lower limb kinematic, kinetic, and electromyography (EMG) data interrelation in controlled speeds is challenging for fully assessing human locomotion conditions. This paper provides a complete dataset with the above-mentioned raw and processed data simultaneously recorded for sixteen healthy participants walking on a 10 meter-flat surface at seven controlled speeds (1.0, 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0 km/h). The raw data include 3D joint trajectories of 24 retro-reflective markers, ground reaction forces (GRF), force plate moments, center of pressures, and EMG signals from Tibialis Anterior, Gastrocnemius Lateralis, Biceps Femoris, and Vastus Lateralis. The processed data present gait cycle-normalized data including filtered EMG signals and their envelope, 3D GRF, joint angles, and torques. This study details the experimental setup and presents a brief validation of the data quality. The presented dataset may contribute to (i) validate and enhance human biomechanical gait models, and (ii) serve as a reference trajectory for personalized control of robotic assistive devices, aiming an adequate assistance level adjusted to the gait speed and user's anthropometry.

Perspective on musculoskeletal modelling and predictive simulations of human movement to assess the neuromechanics of gait

Locomotion results from complex interactions between the central nervous system and the musculoskeletal system with its many degrees of freedom and muscles. Gaining insight into how the properties of each subsystem shape human gait is challenging as experimental methods to manipulate and assess isolated subsystems are limited. Simulations that predict movement patterns based on a mathematical model of the neuro-musculoskeletal system without relying on experimental data can reveal principles of locomotion by elucidating cause-effect relationships. New computational approaches have enabled the use of such predictive simulations with complex neuro-musculoskeletal models. Here, we review recent advances in predictive simulations of human movement and how those simulations have been used to deepen our knowledge about the neuromechanics of gait. In addition, we give a perspective on challenges towards using predictive simulations to gain new fundamental insight into motor control of gait, and to help design personalized treatments in patients with neurological disorders and assistive devices that improve gait performance. Such applications will require more detailed neuro-musculoskeletal models and simulation approaches that take uncertainty into account, tools to efficiently personalize those models, and validation studies to demonstrate the ability of simulations to predict gait in novel circumstances.

Multiple-Joint Pedestrian Tracking Using Periodic Models

Estimating accurate positions of multiple pedestrians is a critical task in robotics and autonomous cars. We propose a tracker based on typical human motion patterns to track multiple pedestrians. This paper assumes that the legs' reflection and extension angles are approximately changing periodically during human motion. A Fourier series is fitted in order to describe the moving, such as describing the position and velocity of the hip, knee, and ankle. Our tracker receives the position of the ankle, knee, and hip as measurements. As a proof of concept, we compare our tracker with state-of-the-art methods. The proposed models have been validated by experimental data, the Human Gait Database (HuGaDB), and the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) tracking benchmark. The results indicate that our tracker is able to estimate the reflection and extension angles with a precision of 90.97%. Moreover, the comparison shows that the tracking precision increases up to 1.3% with the proposed tracker when compared to a constant velocity based tracker.

Estimating Walking Speed in the Wild

An individual's physical activity substantially impacts the potential for prevention and recovery from diverse health issues, including cardiovascular diseases. Precise quantification of a patient's level of day-to-day physical activity, which can be characterized by the type, intensity, and duration of movement, is crucial for clinicians. Walking is a primary and fundamental physical activity for most individuals. Walking speed has been shown to correlate with various heart pathologies and overall function. As such, it is often used as a metric to assess health performance. A range of clinical walking tests exist to evaluate gait and inform clinical decision-making. However, these assessments are often short, provide qualitative movement assessments, and are performed in a clinical setting that is not representative of the real-world. Technological advancements in wearable sensing and associated algorithms enable new opportunities to complement in-clinic evaluations of movement during free-living. However, the use of wearable devices to inform clinical decisions presents several challenges, including lack of subject compliance and limited sensor battery life. To bridge the gap between free-living and clinical environments, we propose an approach in which we utilize different wearable sensors at different temporal scales and resolutions. Here, we present a method to accurately estimate gait speed in the free-living environment from a low-power, lightweight accelerometer-based bio-logging tag secured on the thigh. We use high-resolution measurements of gait kinematics to build subject-specific data-driven models to accurately map stride frequencies extracted from the bio-logging system to stride speeds. The model-based estimates of stride speed were evaluated using a long outdoor walk and compared to stride parameters calculated from a foot-worn inertial measurement unit using the zero-velocity update algorithm. The proposed method presents an average concordance correlation coefficient of 0.80 for all subjects, and 97% of the error is within ±0.2m· s -1. The approach presented here provides promising results that can enable clinicians to complement their existing assessments of activity level and fitness with measurements of movement duration and intensity (walking speed) extracted at a week time scale and in the patients' free-living environment.

The human preference for symmetric walking often disappears when one leg is constrained

KEY POINTS

We hypothesized that minimization of metabolic power could drive people to walk asymmetrically when one leg is constrained We studied healthy young adults and independently constrained one or both step lengths to be markedly shorter or longer than preferred using visual feedback When one leg was constrained to take a shorter or longer step than preferred, asymmetric walking patterns were less metabolically costly than symmetric walking patterns When one leg was constrained to take a shorter or longer step than preferred and the other leg was allowed to move freely, most participants naturally adopted an asymmetric gait People may prefer to walk asymmetrically to minimize metabolic power when the function of one leg is constrained during fixed-speed treadmill walking ABSTRACT: The bilateral symmetry inherent in healthy human walking is often disrupted in clinical conditions that primarily affect one leg (e.g. stroke). This seems intuitive: with one leg constrained, gait becomes asymmetric. However, the emergence of asymmetry is not inevitable. Consider that symmetric walking could be preserved by matching the movement of the unconstrained leg to that of the constrained leg. While this is theoretically possible, it is rarely observed in clinical populations. Here, we hypothesized that minimization of metabolic power could drive people to walk asymmetrically when one leg is constrained, even when symmetric walking remains possible. We tested this hypothesis by performing two experiments in healthy adults. In Experiment 1, we constrained one step to be markedly shorter or longer than preferred. We observed that participants could significantly reduce metabolic power by adopting an asymmetric gait (one short/long step, one preferred step) rather than maintaining a symmetric gait (bilateral short/long steps). Indeed, when allowed to walk freely in this situation, participants naturally adopted a less effortful asymmetric gait. In Experiment 2, we applied a milder constraint that more closely approximated magnitudes of step length asymmetry that are observed in clinical populations. Responses in this experiment were more heterogeneous, though most participants adopted an asymmetric gait. These findings support two central conclusions: (1) symmetry is not necessarily energetically optimal in constrained human walking, and (2) people may prefer to walk asymmetrically to minimize metabolic power when one leg is constrained during fixed-speed treadmill walking, especially when the constraint is large.

How automatic speed control based on distance affects user behaviours in telepresence robot navigation within dense conference-like environments

Telepresence robots allow users to be spatially and socially present in remote environments. Yet, it can be challenging to remotely operate telepresence robots, especially in dense environments such as academic conferences or workplaces. In this paper, we primarily focus on the effect that a speed control method, which automatically slows the telepresence robot down when getting closer to obstacles, has on user behaviors. In our first user study, participants drove the robot through a static obstacle course with narrow sections. Results indicate that the automatic speed control method significantly decreases the number of collisions. For the second study we designed a more naturalistic, conference-like experimental environment with tasks that require social interaction, and collected subjective responses from the participants when they were asked to navigate through the environment. While about half of the participants preferred automatic speed control because it allowed for smoother and safer navigation, others did not want to be influenced by an automatic mechanism. Overall, the results suggest that automatic speed control simplifies the user interface for telepresence robots in static dense environments, but should be considered as optionally available, especially in situations involving social interactions.

Quantification of spatiotemporal parameter behavior during walking speed transitions

The biomechanics of constant speed walking have been well quantified, but little is known about transitions between walking speeds. Spatiotemporal behavior (step time, length, and speed) has been investigated in starting, stopping, and walking to running transitions, but speed transitions during walking have yet to be investigated. This study quantified the spatiotemporal parameter behavior during walking speed transitions with a range of magnitudes (or differences between pre- and post-transition normalized speeds ranging from 0.03 to 0.13, or approximately 1.18 m/s to 1.58 m/s). 23 healthy adults walked on a treadmill at five different constant speeds for one minute each to establish a baseline. They then performed walking speed transitions, in which they walked on the treadmill as it randomly changed between the five speeds. Linear mixed effect models showed that subjects converged to slightly different post-transition step time and step length averages than established in the constant speed baseline, but the differences are likely too small to be meaningful (on the order of 0.01 s and 0.01 m). When diverging from the pre-transition speed, subjects either diverged in only step time (with step length remaining the same), only step length (with step time remaining the same), or both step time and step length to reach the post-transition speed, with the behavior strongly tied to the magnitude of the speed transition (p<0.001). Step time often overshot the new value before converging. The number of steps required for each parameter to converge increased with increasing transition magnitude (p<0.001) and was consistently higher at all magnitudes for speed than step time and length (p<0.001). In summary, transition magnitude affected the spatiotemporal behavior during walking speed transitions. Further, step time, length, and speed all exhibited slightly different divergence and convergence behavior during transitions.

Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles

Motion capture laboratories can measure multiple variables at high frame rates, but we can only measure the average metabolic rate of a stride using respiratory measurements. Biomechanical simulations with equations for calculating metabolic rate can estimate the time profile of metabolic rate within the stride cycle. A variety of methods and metabolic equations have been proposed, including metabolic time profile estimations based on joint parameters. It is unclear whether differences in estimations are due to differences in experimental data or due to methodological differences. This study aimed to compare two methods for estimating the time profile of metabolic rate, within a single dataset. Knowledge about the consistency of different methods could be useful for applications such as detecting which part of the gait cycle causes increased metabolic cost in patients. Here we compare estimations of metabolic rate time profiles using a musculoskeletal and a joint-space method. The musculoskeletal method was driven by kinematics and electromyography data and used muscle metabolic rate equations, whereas the joint-space method used metabolic rate equations based on joint parameters. Both estimations of changes in stride average metabolic rate correlated significantly with large changes in indirect calorimetry from walking on different grades showing that both methods accurately track changes. However, estimations of changes in stride average metabolic rate did not correlate significantly with more subtle changes in indirect calorimetry due to walking with different shoe inclinations, and both the musculoskeletal and joint-space time profile estimations did not correlate significantly with each other except in the most downward shoe inclination. Estimations of the relative cost of stance and swing matched well with previous simulations with similar methods and estimations from experimental perturbations. Rich experimental datasets could further advance time profile estimations. This knowledge could be useful to develop therapies and assistive devices that target the least metabolically economic part of the gait cycle.

Exploring the Contribution of Proprioceptive Reflexes to Balance Control in Perturbed Standing

Humans control balance using different feedback loops involving the vestibular system, the visual system, and proprioception. In this article, we focus on proprioception and explore the contribution of reflexes based on force and length feedback to standing balance. In particular, we address the questions of how much proprioception alone could explain balance control, and whether one modality, force or length feedback, is more important than the other. A sagittal plane neuro-musculoskeletal model was developed with six degrees of freedom and nine muscles in each leg. A controller was designed using proprioceptive reflexes and a dead zone. No feedback control was applied inside the dead zone. Reflexes were active once the center of mass moved outside the dead zone. Controller parameters were found by solving an optimization problem, where effort was minimized while the neuro-musculoskeletal model should remain standing upright on a perturbed platform. The ground was perturbed with random square pulses in the sagittal plane with different amplitudes and durations. The optimization was solved for three controllers: using force and length feedback (base model), using only force feedback, and using only length feedback. Simulations were compared to human data from previous work, where an experiment with the same perturbation signal was performed. The optimized controller yielded a similar posture, since average joint angles were within 5 degrees of the experimental average joint angles. The joint angles of the base model, the length only model, and the force only model correlated weakly (ankle) to moderately with the experimental joint angles. The ankle moment correlated weakly to moderately with the experimental ankle moment, while the hip and knee moment were only weakly correlated, or not at all. The time series of the joint angles showed that the length feedback model was better able to explain the experimental joint angles than the force feedback model. Changes in time delay affected the correlation of the joint angles and joint moments. The objective of effort minimization yielded lower joint moments than in the experiment, suggesting that other objectives are also important in balance control, which cause an increase in effort and thus larger joint moments.

Form in the context of function: Fundamentals of an energy effective striding walk, the role of the plantigrade foot and its expected size

What morphological and functional factors allow for the unique and characteristic upright striding walk of the hominin lineage? Predictive models of locomotion that arise from considering mechanisms of energy loss indicate that collision-like losses at the transition between stance limbs are important determinants of bipedal gait. Theoretical predictions argue that these collisional losses can be reduced by having "functional extra legs" which are physically the heel and the toe part of a single anatomical foot. The ideal spacing for these "functional legs" are up to a quarter of a stride length, depending on the model employed. We evaluate the foot in the context of the dynamics of a bipedal system and compare predictions of optimal foot size against empirical data from modern humans, the Laetoli footprint trackways, and chimpanzees walking bipedally. The dynamics-based modeling approach provides substantial insight into how, and why, walking works as it does, even though current models are too simple to make predictions at a level adequate to anticipate specific morphology except at the most general level.

Self-selected step length asymmetry is not explained by energy cost minimization in individuals with chronic stroke

Background

Asymmetric gait post-stroke is associated with decreased mobility, yet individuals with chronic stroke often self-select an asymmetric gait despite being capable of walking more symmetrically. The purpose of this study was to test whether self-selected asymmetry could be explained by energy cost minimization. We hypothesized that short-term deviations from self-selected asymmetry would result in increased metabolic energy consumption, despite being associated with long-term rehabilitation benefits. Other studies have found no difference in metabolic rate across different levels of enforced asymmetry among individuals with chronic stroke, but used methods that left some uncertainty to be resolved.

Methods

In this study, ten individuals with chronic stroke walked on a treadmill at participant-specific speeds while voluntarily altering step length asymmetry. We included only participants with clinically relevant self-selected asymmetry who were able to significantly alter asymmetry using visual biofeedback. Conditions included targeting zero asymmetry, self-selected asymmetry, and double the self-selected asymmetry. Participants were trained with the biofeedback system in one session, and data were collected in three subsequent sessions with repeated measures. Self-selected asymmetry was consistent across sessions. A similar protocol was conducted among unimpaired participants.

Results

Participants with chronic stroke substantially altered step length asymmetry using biofeedback, but this did not affect metabolic rate (ANOVA, p = 0.68). In unimpaired participants, self-selected step length asymmetry was close to zero and corresponded to the lowest metabolic energy cost (ANOVA, p = 6e-4). While the symmetry of unimpaired gait may be the result of energy cost minimization, self-selected step length asymmetry in individuals with chronic stroke cannot be explained by a similar least-effort drive.

Conclusions

Interventions that encourage changes in step length asymmetry by manipulating metabolic energy consumption may be effective because these therapies would not have to overcome a metabolic penalty for altering asymmetry.

Auditory and Visual External Cues Have Different Effects on Spatial but Similar Effects on Temporal Measures of Gait Variability

Walking synchronized to external cues is a common practice in clinical settings. Several research studies showed that this popular gait rehabilitation tool alters gait variability. There is also recent evidence which suggests that alterations in the temporal structure of the external cues could restore gait variability at healthy levels. It is unknown, however, if such alterations produce similar effects if the cueing modalities used are different; visual or auditory. The modality could affect gait variability differentially, since there is evidence that auditory cues mostly act in the temporal domain of gait, while visual cues act in the spatial domain of gait. This study investigated how synchronizing steps with visual and auditory cues that are presented with different temporal structures could affect gait variability during treadmill walking. Three different temporal structured stimuli were used, invariant, fractal and random, in both modalities. Stride times, length and speed were determined, and their fractal scaling (an indicator of complexity) and coefficient of variation (CV) were calculated. No differences were observed in the CV, regardless of the cueing modality and the temporal structure of the stimuli. In terms of the stride time's fractal scaling, we observed that the fractal stimulus induced higher values compared to random and invariant stimuli. The same was also observed in stride length, but only for the visual cueing modality. No differences were observed for stride speed. The selection of the cueing modality seems to be an important feature of gait rehabilitation. Visual cues are possibly a better choice due to the dependency on vision during walking. This is particularly evident during treadmill walking, a common practice in a clinical setting. Because of the treadmill effect on the temporal domain of gait, the use of auditory cues can be minimal, compared to visual cues.

Load carrying with flexible bamboo poles: optimization of a coupled oscillator system

In Asia, flexible bamboo poles are routinely used to carry substantial loads on the shoulder. Various advantages have been attributed to this load-carrying strategy (e.g. reduced energy consumption), but experimental evidence remains inconsistent – possibly because carriers in previous studies were inexperienced. Theoretical models typically neglect the individual's capacity to optimize interactions with the oscillating load, leaving the complete dynamics underexplored. This study used a trajectory optimization model to predict gait adaptations that minimize work-based costs associated with carrying compliant loads and compared the outcomes with naturally selected gait adaptations of experienced pole carriers. Gait parameters and load interactions (e.g. relative amplitude and frequency, phase) were measured in rural farmworkers in Vietnam. Participants carried a range of loads with compliant and rigid poles and the energetic consequences of step frequency adjustments were evaluated using the model. When carrying large loads, the empirical step frequency changes associated with pole type (compliant versus rigid) were largely consistent with model predictions, in terms of direction (increase or decrease) and magnitude (by how much). Work-minimizing strategies explain changes in leg compliance, harmonic frequency oscillations and fluctuations in energetic cost associated with carrying loads on a compliant bamboo pole.

Inverse dynamic estimates of muscle recruitment and joint contact forces are more realistic when minimizing muscle activity rather than metabolic energy or contact forces

BACKGROUND

Assessment of contact forces is essential for a better understanding of mechanical factors affecting progression of osteoarthritis. Since contact forces cannot be measured non-invasively, computer simulations are often used to assess joint loading. Contact forces are to a large extent determined by muscle forces. These muscle forces are computed using optimization techniques that solve the muscle redundancy problem by assuming that muscles are coordinated in a way that optimizes performance (e.g., minimizes muscle activity or metabolic energy). However, it is unclear which of the many proposed performance criteria best describes muscle coordination.

RESEARCH QUESTION

Which performance criterion best describes muscle recruitment patterns and knee contact forces recorded using electromyography (EMG) and load cell instrumented prostheses?.

METHODS

We solved the muscle redundancy problem based on six different groups of performance criteria: muscle activations, volume-scaled activations, forces, stresses, metabolic energy, and joint contact forces. Computed muscle excitations and knee contact forces during over-ground walking were validated against recorded EMG signals and measured contact forces for four subjects with instrumented knee prostheses in the "Grand Challenge Competition to Predict in Vivo Knee Loads" dataset.

RESULTS

Performance criteria based on either stress or muscle activation (either unscaled or scaled by muscle volume), both to a power of 3 or 4, resulted in the best agreement between measured and simulated values. These performance criteria outperformed all other criteria in terms of agreement between simulated muscle excitations and EMG, whereas good agreement between measured and predicted contact forces was also observed for minimization of contact forces and metabolic energy.

SIGNIFICANCE

Given the large differences in accuracy obtained with different performance criteria (e.g., root mean square errors of contact forces differed up to 0.45 body weight), the results of our study are important to improve the validity of in silico assessment of joint loading.

Using Music-Based Cadence Entrainment to Manipulate Walking Intensity

BACKGROUND

While previous studies indicate an auditory metronome can entrain cadence (in steps per minute), music may also evoke prescribed cadences and metabolic intensities.

PURPOSE

To determine how modulating the tempo of a single commercial song influences adults' ability to entrain foot strikes while walking and how this entrainment affects metabolic intensity.

METHODS

Twenty healthy adults (10 men and 10 women; mean [SD]: age 23.7 [2.7] y, height 172.8 [9.0] cm, mass 71.5 [16.2] kg) walked overground on a large circular pathway for six 5-min conditions; 3 self-selected speeds (slow, normal, and fast); and 3 trials listening to a song with its tempo modulated to 80, 100, and 125 beats per minute. During music trials, participants were instructed to synchronize their step timing with the music tempo. Cadence was measured via direct observation, and metabolic intensity (metabolic equivalents) was assessed using indirect calorimetry.

RESULTS

Participants entrained their cadences to the music tempos (mean absolute percentage error = 5.3% [5.8%]). Entraining to a music tempo of 100 beats per minute yielded ≥3 metabolic equivalents in 90% of participants. Trials with music entrainment exhibited greater metabolic intensity compared with self-paced trials (repeated-measures analysis of variance, F1,19 = 8.05, P = .01).

CONCLUSION

This study demonstrates the potential for using music to evoke predictable metabolic intensities.

Rapid predictive simulations with complex musculoskeletal models suggest that diverse healthy and pathological human gaits can emerge from similar control strategies

Physics-based predictive simulations of human movement have the potential to support personalized medicine, but large computational costs and difficulties to model control strategies have limited their use. We have developed a computationally efficient optimal control framework to predict human gaits based on optimization of a performance criterion without relying on experimental data. The framework generates three-dimensional muscle-driven simulations in 36 min on average—more than 20 times faster than existing simulations—by using direct collocation, implicit differential equations and algorithmic differentiation. Using this framework, we identified a multi-objective performance criterion combining energy and effort considerations that produces physiologically realistic walking gaits. The same criterion also predicted the walk-to-run transition and clinical gait deficiencies caused by muscle weakness and prosthesis use, suggesting that diverse healthy and pathological gaits can emerge from the same control strategy. The ability to predict the mechanics and energetics of a broad range of gaits with complex three-dimensional musculoskeletal models will allow testing novel hypotheses about gait control and hasten the development of optimal treatments for neuro-musculoskeletal disorders.

The Metabolic Cost of Walking in healthy young and older adults - A Systematic Review and Meta Analysis

The Metabolic Cost of Walking (MCoW) is an important variable of daily life that has been studied extensively. Several studies suggest that MCoW is higher in Older Adults (OA) than in Young Adults (YA). However, it is difficult to compare values across studies due to differences in the way MCoW was expressed, the units in which it was reported and the walking speed at which it was measured. To provide an overview of MCoW in OA and YA and to investigate the quantitative effect of age on MCoW, we have conducted a literature review and performed two meta-analyses. We extracted data on MCoW in healthy YA (18-41 years old) and healthy OA (≥59 years old) and calculated, if not already reported, the Gross (GCoW) and Net MCoW (NCoW) in J/kg/m. If studies reported MCoW measured at multiple speeds, we selected those values for YA and OA at which MCoW was minimal. All studies directly comparing YA and OA were selected for meta-analyses. From all studies reviewed, the average GCoW in YA was 3.4 ± 0.4 J/kg/m and 3.8 ± 0.4 J/kg/m in OA (~12% more in OA), and the average NCoW in YA was 2.4 ± 0.4 J/kg/m and 2.8 ± 0.5 J/kg/m in OA (~17% more in OA). Our meta-analyses indicated a statistically significant elevation of both GCoW and NCoW (p < 0.001) for OA. In terms of GCoW, OA expended about 0.3 J/kg/m more metabolic energy than YA and about 0.4 J/kg/m more metabolic energy than YA in terms of NCoW. Our study showed a statistically significant elevation in MCoW of OA over YA. However, from the literature it is unclear if this elevation is directly caused by age or due to an interaction between age and methodology. We recommend further research comparing MCoW in healthy OA and YA during "natural" over-ground walking and treadmill walking, after sufficient familiarization time.

Trading Symmetry for Energy Cost During Walking in Healthy Adults and Persons Poststroke

Background. Humans typically walk in ways that minimize energy cost. Recent work has found that healthy adults will even adopt new ways of walking when a new pattern costs less energy. This suggests potential for rehabilitation to drive changes in walking by altering the energy costs of walking patterns so that the desired pattern becomes energetically optimal (ie, costs least energy of all available patterns). Objective. We aimed to change gait symmetry in healthy adults and persons poststroke by creating environments where changing symmetry allowed the participants to save energy. Methods. Across 3 experiments, we tested healthy adults (n = 12 in experiment 1, n = 20 in experiment 2) and persons poststroke (n = 7 in experiment 3) in a novel treadmill environment that linked asymmetric stepping and gait speed-2 factors that influence energy cost-to create situations where walking with one's preferred gait symmetry (or asymmetry, in the case of the persons poststroke) was no longer the least energetically costly way to walk. Results. Across the 3 experiments, we found that most participants changed their gait when experiencing the new energy landscape. Healthy adults often adopted an asymmetric gait if it saved energy, and persons poststroke often began to step more symmetrically than they prefer to walk in daily life. Conclusions. We used a novel treadmill environment to show that people with and without stroke change clinically relevant features of walking to save energy. These findings suggest that rehabilitation approaches aimed at making symmetric walking energetically "easier" may promote gait symmetry after stroke.

Topological assessment of gait synchronisation in overground walking groups

Walking is one of the fundamental forms of human gross motor activity in which spatiotemporal movement coordination can occur. While considerable body of evidence already exists on pedestrian movement coordination while walking in pairs, little is known about gait control while walking in more complex topological arrangements. To this end, this study provides some of the first evidence of spontaneous gait synchronisation while walking in a group. Nine subjects covered the total distance of 40 km at different speeds while assembled in a three-by-three formation. Two experimental protocols were applied in which the subjects were either not specifically asked to or specifically asked to synchronise their gait. To obtain results representative from the point of view of gait control, the movement coordination was quantified using the indirectly measured vertical component of ground reaction force, based on output from a network of wireless motion monitors. Bivariate phase difference analysis was conducted using wavelet transform, synchronisation strength measures derived from Shannon entropy, and circular statistics. A fundamental relationship describing the influence of the group walking speed on individuals' pacing frequency was established, showing a positive correlation different from that previously reported for walking in solitude. A positive correlation was found between the average synchronisation strength within a group and group's walking speed. The most persistent coordination patterns were identified for pedestrians walking front-to-back and side-by-side. Overall, the spontaneous gait synchronisation while walking in a group is relatively weak, well below the levels reported for walking in pairs.

Influence of arm swing on cost of transport during walking

Normal arm swing plays a role in decreasing the cost of transport during walking. However, whether excessive arm swing can reduce the cost of transport even further is unknown. Therefore, we tested the effects of normal and exaggerated arm swing on the cost of transport in the current study. Healthy participants (n=12) walked on a treadmill (1.25 m/s) in seven trials with different arm swing amplitudes (in-phase, passive restricted, active restricted, normal, three gradations of extra arm swing), while metabolic energy cost and the vertical angular momentum (VAM) and ground reaction moment (GRM) were measured. In general, VAM and GRM decreased as arm swing amplitude was increased, except for in the largest arm swing amplitude condition. The decreases in VAM and GRM were accompanied by a decrease in cost of transport from in-phase walking (negative amplitude) up to a slightly increased arm swing (non-significant difference compared to normal arm swing). The most excessive arm swings led to an increase in the cost of transport, most likely due to the cost of swinging the arms. In conclusion, increasing arm swing amplitude leads to a reduction in VAM and GRM, but it does not lead to a reduction in cost of transport for the most excessive arm swing amplitudes. Normal or slightly increased arm swing amplitude appear to be optimal in terms of cost of transport in young and healthy individuals.

This article has an associated First Person interview with the first author of the paper.

Summary: Excessive arm swing reduces the vertical angular momentum and ground reaction moment, but not necessarily the energetic cost of transport.

Motor Control: No Constant but Change

We rely on predictions to rapidly select our walking gaits. New research suggests that the formation of these predictions is driven by the difference between the walk we expect and the walk we get.

Is natural variability in gait sufficient to initiate spontaneous energy optimization in human walking?

In new walking contexts, the nervous system can adapt preferred gaits to minimize energetic cost. During treadmill walking, this optimization is not usually spontaneous but instead requires experience with the new energetic cost landscape. Experimenters can provide subjects with the needed experience by prescribing new gaits or instructing them to explore new gaits. Yet in familiar walking contexts, people naturally prefer energetically optimal gaits: the nervous system can optimize cost without an experimenter's guidance. Here we test the hypothesis that the natural gait variability of overground walking provides the nervous system with sufficient experience with new cost landscapes to initiate spontaneous minimization of energetic cost. We had subjects walk over paths of varying terrain while wearing knee exoskeletons that penalized walking as a function of step frequency. The exoskeletons created cost landscapes with minima that were, on average, 8% lower than the energetic cost at the initially preferred gaits and achieved at walking speeds and step frequencies that were 4% lower than the initially preferred values. We found that our overground walking trials amplified gait variability by 3.7-fold compared with treadmill walking, resulting in subjects gaining greater experience with new cost landscapes, including frequent experience with gaits at the new energetic minima. However, after 20 min and 2.0 km of walking in the new cost landscapes, we observed no consistent optimization of gait, suggesting that natural gait variability during overground walking is not always sufficient to initiate energetic optimization over the time periods and distances tested in this study. NEW & NOTEWORTHY While the nervous system can continuously optimize gait to minimize energetic cost, what initiates this optimization process during every day walking is unknown. Here we tested the hypothesis that the nervous system leverages the natural variability in gait experienced during overground walking to converge on new energetically optimal gaits created using exoskeletons. Contrary to our hypothesis, we found that participants did not adapt toward optimal gaits: natural variability is not always sufficient to initiate spontaneous energy optimization.

The Landscape of Movement Control in Locomotion: Cost, Strategy, and Solution

Features of gait are determined at multiple levels, from the selection of the gait itself (e.g., walk or run) through the specific parameters utilized (stride length, frequency, etc.) to the pattern of muscular excitation. The ultimate choices are determined neurally, but what is involved with deciding on the appropriate strategy? Human locomotion appears stereotyped not so much because the pattern is predetermined, but because these movement patterns are good solutions for providing movement utilizing the machinery available to the individual (the legs and their requisite components). Under different circumstances the appropriate solution may differ broadly (different gait) or subtly (different parameters). Interpretation of the neural decision making process would benefit from understanding the influences that are utilized in the selection of the appropriate solution in any set of circumstances, including normal conditions. In this review we survey an array of studies that point to energetic cost as a key input to the gait coordination system, and not just an outcome of the gait pattern implemented. We then use that information to rigorously define the construct proposed by Sparrow and Newell (1998) where the effects of environment, organism, and task act as constraints determining the solution set available, and the coordination pattern is then implemented under pressure for energetic economy. The fit between the environment and the organism define affordances that can be actualized. We rely on a novel conceptualization of task that recognizes that the task goal needs to be separated from the mechanisms that achieve it so that the selection of a particular implementation strategy can be exposed and understood. This reformulation of the Sparrow and Newell construct is then linked to the proposed pressure for economy by considering it as an optimization problem, where the most readily selected gait strategy will be the one that achieves the task goal at (or near) the energetic minimum.

Design of a Low Profile, Unpowered Ankle Exoskeleton That Fits Under Clothes: Overcoming Practical Barriers to Widespread Societal Adoption

Here, we present the design of a novel unpowered ankle exoskeleton that is low profile, lightweight, quiet, and low cost to manufacture, intrinsically adapts to different walking speeds, and does not restrict non-sagittal joint motion; while still providing assistive ankle torque that can reduce demands on the biological calf musculature. This paper is an extension of the previously-successful ankle exoskeleton concept by Collins, Wiggin, and Sawicki. We created a device that blends the torque assistance of the prior exoskeleton with the form-factor benefits of clothing. Our design integrates a low profile under-the-foot clutch and a soft conformal shank interface, coupled by an ankle assistance spring that operates in parallel with the user's calf muscles. We fabricated and characterized technical performance of a prototype through benchtop testing and then validated device functionality in two gait analysis case studies. To our knowledge, this is the first ankle plantarflexion assistance exoskeleton that could be feasibly worn under typical daily clothing, without restricting ankle motion, and without components protruding substantially from the shoe, leg, waist, or back. Our new design highlights the potential for performance-enhancing exoskeletons that are inexpensive, unobtrusive, and can be used on a wide scale to benefit a broad range of individuals throughout society, such as the elderly, individuals with impaired plantarflexor muscle strength, or recreational users. In summary, this paper demonstrates how an unpowered ankle exoskeleton could be redesigned to more seamlessly integrate into daily life, while still providing performance benefits for common locomotion tasks.

Using smartphone accelerometry to assess the relationship between cognitive load and gait dynamics during outdoor walking

Research has demonstrated that an increase in cognitive load can result in increased gait variability and slower overall walking speed, both of which are indicators of gait instability. The external environment also imposes load on our cognitive systems; however, most gait research has been conducted in a laboratory setting and little work has demonstrated how load imposed by natural environments impact gait dynamics during outdoor walking. Across four experiments, young adults were exposed to varying levels of cognitive load while walking through indoor and outdoor environments. Gait dynamics were concurrently recorded using smartphone-based accelerometry. Results suggest that, during indoor walking, increased cognitive load impacted a range of gait parameters such as step time and step time variability. The impact of environmental load on gait, however, was not as pronounced, with increased load associated only with step time changes during outdoor walking. Overall, the present work shows that cognitive load is related to young adult gait during both indoor and outdoor walking, and importantly, smartphones can be used as gait assessment tools in environments where gait dynamics have traditionally been difficult to measure.

Large Propulsion Demands Increase Locomotor Adaptation at the Expense of Step Length Symmetry

There is an interest to identify factors facilitating locomotor adaptation induced by split-belt walking (i.e., legs moving at different speeds) because of its clinical potential. We hypothesized that augmenting braking forces, rather than propulsion forces, experienced at the feet would increase locomotor adaptation during and after split-belt walking. To test this, forces were modulated during split-belt walking with distinct slopes: incline (larger propulsion than braking), decline (larger braking than propulsion), and flat (similar propulsion and braking). Step length asymmetry was compared between groups because it is a clinically relevant measure robustly adapted on split-belt treadmills. Unexpectedly, the group with larger propulsion demands (i.e., the incline group) changed their gait the most during adaptation, reached their final adapted state more quickly, and had larger after-effects when the split-belt perturbation was removed. We also found that subjects who experienced larger disruptions of propulsion forces in early adaptation exhibited greater after-effects, which further highlights the catalytic role of propulsion forces on locomotor adaptation. The relevance of mechanical demands on shaping our movements was also indicated by the steady state split-belt behavior, during which each group recovered their baseline leg orientation to meet leg-specific force demands at the expense of step length symmetry. Notably, the flat group was nearly symmetric, whereas the incline and decline group overshot and undershot step length symmetry, respectively. Taken together, our results indicate that forces propelling the body facilitate gait changes during and after split-belt walking. Therefore, the particular propulsion demands to walk on a split-belt treadmill might explain the gait symmetry improvements in hemiparetic gait following split-belt training.