Biology subjects

Collins, S. H.

Publications and source records attributed to Collins, S. H..

18 recordsLinked to original sources

bioRxiv2026

Experiment-free learning of exoskeleton assistance remains an unsolved problem

In "Experiment-free exoskeleton assistance via learning in simulation", Luo et al. [1] present an ambitious framework for developing exoskeleton controllers through reinforcement learning exclusively in computer simulation. The authors report that a control policy trained on a small dataset from one subject was directly transferred to physical hardware, reducing human metabolic cost during walking, running, and stair climbing by more than any prior device. If confirmed, this would represent a major breakthrough for the field of wearable robotics and their clinical applications. However, a close examination of the published materials casts doubt on these claims. The reported experimental results violate physiological limits on the relationship between mechanical power and muscle energy use during gait2,3,4. The algorithmic claims are surprising and cannot be verified; in contrast with established replicability standards in machine learning5,6, executable code has not been made available. We conclude that the goals of this study have not yet been verifiably achieved and make recommendations for avoiding publication errors of this type in the future.

physiology↗

bioRxiv2025

Perturbation Recovery Time Identifies Subtle Human Balance Impairments and Features

Falls are a leading cause of injury and growing healthcare costs, particularly in aging populations. However, early-stage balance impairments often remain undetected until severe problems arise. Quantitative assessment of human balance therefore remains a critical challenge. Here, we introduce Perturbation Recovery Time, a novel state-space-based balance metric inspired by nonlinear dynamic system theory that quantifies the duration required for gait dynamics to consistently return to a steady-state neighborhood following a perturbation. Unlike conventional approaches based on steady-state walking, this framework evaluates balance through externally induced perturbations that reveal control mechanisms not observable during unperturbed gait. Using healthy participants with experimentally induced impairments, we identified key balance-related features, including the anterior-posterior center-of-mass-center-of-pressure distance, whole-body angular momentum in the frontal and sagittal planes, and vertical center-of-mass position and acceleration. These features capture the core mechanisms of balance control, including foot placement, inverted pendulum dynamics, push-off control, and trunk regulation. Perturbation Recovery Time reliably detected within-subject changes in balance associated with controlled impairments in sensory input, motor coordination, and movement consistency. These findings demonstrate that Perturbation Recovery Time provides a quantitative and sensitive measure of balance, offering a framework for early detection of balance impairments.

bioengineering↗

bioRxiv2025

Biofeedback speeds adaptation to exoskeleton gait assistance

Exoskeletons may enhance mobility, but users require extensive training to receive their full benefit. While augmented feedback can accelerate motor learning, its application to exoskeleton-assisted gait is limited by the complexity of locomotor function and human-robot interaction. We developed a visual biofeedback system to guide novice users of an ankle exoskeleton to modify their ankle joint kinematics and foot placement toward patterns associated with improved energy economy. Biofeedback-based training doubled the energy savings from exoskeleton use, enabling people to achieve benefits comparable to fully adapted users in one-quarter of the time. Notably, participants in this study had not fully adapted after the hour-long training session, underscoring the tasks difficulty and suggesting that greater benefit from exoskeletons may be unlocked with continued use of this approach. Energy savings were associated with increased exploration and progression toward lower-cost gait parameters in task-relevant dimensions. Our findings demonstrate that biofeedback can accelerate motor adaptation to exoskeletons, potentially enhancing their effectiveness and promoting broader device adoption.

bioengineering↗

bioRxiv2025

How peak knee loads are affected by changing the mass of lower-limb body segments during walking

For individuals with knee osteoarthritis, increased knee loading is linked to disease progression and pain. Some approaches to treating osteoarthritis, such as specialized footwear, braces, and powered exoskeletons, also increase the mass of the lower limbs, which could lead to increases in knee loads. Prior studies have investigated the effect of changes in torso mass and total body mass on peak knee contact forces, but the effects of increased leg mass remain unclear. In this study, we created musculoskeletal simulations informed by experimental data to estimate tibiofemoral knee contact force under different lower-limb segment mass conditions. The mass of the foot, shank, and thigh were varied by adding weights to each segment, separately and concurrently, as healthy young adults (N = 10) walked on a treadmill. Kinematics, kinetics, and muscle activity were recorded. Our simulations used an optimal control framework that enforced experimental kinematics while minimizing a combination of net joint moment errors and mismatch between measured and estimated muscle activity. The simulations revealed that adding mass to the lower-limb segments linearly increased early- and late-stance peaks in knee contact force, but that the slope of this relationship was different for each peak and each mass placement location. For each 1% of body weight (BW) added per limb (2% BW total) at the thigh, shank, and foot, early-stance peak knee contact force increased by 1.5%, 2.1%, and 5.9%, while late-stance peak contact force increased by 1.6%, 0.9% and 3.0%, respectively. Adding mass to the thigh and shank increases peak contact force at or below the rate of increase in body mass, while adding mass to the foot disproportionately increases peak knee contact force. These detrimental effects should be considered when designing interventions for osteoarthritis. Author summaryFor individuals with knee osteoarthritis, increased knee loading is linked to disease progression and pain. Some approaches to treating knee OA, such as specialized footwear, braces, and exoskeletons, increase the mass of the lower limbs, which could lead to increases in knee loads. However, the effects of changing lower limb segment mass on knee loading remain unclear. In this study, we created computer simulations informed by experimental data to estimate knee loads while walking with different amounts of added mass to the lower limb segments. We collected experimental data from 10 healthy participants while they walked on a treadmill with various amounts of mass added to their lower limb segments (thigh, shank, foot). We used these data and a biomechanically accurate model of each participant to construct realistic computer simulations, from which we obtained estimates of internal knee forces that contribute to total knee load. We found that peak knee load increased linearly with amount of added mass, but that this relationship differed by segment. Adding mass to the feet had the greatest effect on knee contact force. Our results can help to inform the design of interventions for knee osteoarthritis.

systems biology↗

bioRxiv2023

Frontal hip exoskeleton assistance does not appear promising for reducing the metabolic cost of walking: A preliminary experimental study

BackgroundDuring walking, humans exert a substantial hip abduction moment to maintain balance and prevent pelvic drop. This significant torque requirement suggests that assisting the frontal hip muscles could be a promising strategy to reduce the energy expenditure associated with walking. A previous musculoskeletal simulation study also predicted that providing hip abduction assistance through an exoskeleton could potentially result in a large reduction in whole-body metabolic rate. However, to date, no study has experimentally assessed the metabolic cost of walking with frontal hip assistance. MethodsIn this case study involving a single subject (N = 1), a tethered hip exoskeleton emulator was used to assess the feasibility of reducing metabolic expenditure through frontal-plane hip assistance. Human-in-the-loop optimization was conducted separately under torque and position control to determine energetically optimal assistance parameters for each control scheme. ResultsThe optimized profiles in both control schemes did not reduce metabolic rate compared to walking with assistance turned off. The optimal peak torque magnitude was found to be close to zero, suggesting that any hip abduction torque would increase metabolic rate. Both bio-inspired and simulation-inspired profiles substantially increased metabolic cost. ConclusionFrontal hip assistance does not appear to be promising in reducing the metabolic rate of walking. This could be attributed to the need for maintaining balance, as humans may refrain from relaxing certain muscles as a precaution against unexpected disturbances during walking. An investigation of different control architectures is needed to determine if frontal-plane hip assistance can yield successful results.

bioengineering↗

bioRxiv2023

AddBiomechanics: Automating model scaling, inverse kinematics, and inverse dynamics from human motion data through sequential optimization

Creating large-scale public datasets of human motion biomechanics could unlock data-driven breakthroughs in our understanding of human motion, neuromuscular diseases, and assistive devices. However, the manual effort currently required to process motion capture data and quantify the kinematics and dynamics of movement is costly and limits the collection and sharing of large-scale biomechanical datasets. We present a method, called AddBiomechanics, to automate and standardize the quantification of human movement dynamics from motion capture data. We use linear methods followed by a non-convex bilevel optimization to scale the body segments of a musculoskeletal model, register the locations of optical markers placed on an experimental subject to the markers on a musculoskeletal model, and compute body segment kinematics given trajectories of experimental markers during a motion. We then apply a linear method followed by another non-convex optimization to find body segment masses and fine tune kinematics to minimize residual forces given corresponding trajectories of ground reaction forces. The optimization approach requires approximately 3-5 minutes to determine a subjects skeleton dimensions and motion kinematics, and less than 30 minutes of computation to also determine dynamically consistent skeleton inertia properties and fine-tuned kinematics and kinetics, compared with about one day of manual work for a human expert. We used AddBiomechanics to automatically reconstruct joint angle and torque trajectories from previously published multi-activity datasets, achieving close correspondence to expert-calculated values, marker root-mean-square errors less than 2 cm, and residual force magnitudes smaller than 2% of peak external force. Finally, we confirmed that AddBiomechanics accurately reproduced joint kinematics and kinetics from synthetic walking data with low marker error and residual loads. We have published the algorithm as an open source cloud service at AddBiomechanics.org, which is available at no cost and asks that users agree to share processed and de-identified data with the community. As of this writing, hundreds of researchers have used the prototype tool to process and share about ten thousand motion files from about one thousand experimental subjects. Reducing the barriers to processing and sharing high-quality human motion biomechanics data will enable more people to use state-of-the-art biomechanical analysis, do so at lower cost, and share larger and more accurate datasets.

bioengineering↗

bioRxiv2022

Simulating the effect of ankle plantarflexion and inversion-eversion exoskeleton torques on center of mass kinematics during walking

Walking balance is central to independent mobility, and falls due to loss of balance are a leading cause of death for people 65 years of age and older. Bipedal gait is typically unstable, but healthy humans use corrective torques to counteract perturbations and stabilize gait. Exoskeleton assistance could benefit people with neuromuscular deficits by providing stabilizing torques at lower-limb joints to replace lost muscle strength and sensorimotor control. However, it is unclear how applied exoskeleton torques translate to changes in walking kinematics. This study used musculoskeletal simulation to investigate how exoskeleton torques applied to the ankle and subtalar joints alter center of mass kinematics during walking. We first created muscle-driven walking simulations using OpenSim Moco by tracking experimental kinematics and ground reaction forces recorded from five healthy adults. We then used forward integration to simulate the effect of exoskeleton torques applied to the ankle and subtalar joints while keeping muscle excitations fixed based on our previous tracking simulation results. Exoskeleton torque lasted for 15% of the gait cycle and was applied between foot-flat and toe-off during the stance phase, and changes in center of mass kinematics were recorded when the torque application ended. We found that changes in center of mass kinematics were dependent on both the type and timing of exoskeleton torques. Plantarflexion torques produced upward and backward changes in velocity of the center of mass in mid-stance and upward and forward velocity changes near toe-off. Eversion and inversion torques primarily produced lateral and medial changes in velocity in mid-stance, respectively. Intrinsic muscle properties reduced kinematic changes from exoskeleton torques. Our results provide mappings between ankle plantarflexion and inversion-eversion torques and changes in center of mass kinematics which can inform designers building exoskeletons aimed at stabilizing balance during walking. Our simulations and software are freely available and allow researchers to explore the effects of applied torques on balance and gait.

bioengineering↗

bioRxiv2021

Weighted Shoes in the Wild: Initial Insights into the Relationship Between the Effort of Walking and the Amount of Walking Performed

PurposeWalking comprises a large portion of active energy expenditure in humans. Interventions that increase or decrease the energy expended on each step, such as ankle weights or energy-saving orthoses, may therefore strongly impact fitness. The overall effect of increasing or decreasing per-step energy use is unclear, however, because people may choose to walk less or more, respectively, in response. MethodsIn this study, healthy college students with normal body mass index wore weighted and unweighted shoes embedded with an inertial measurement unit for one week each. Community-based walking data were analyzed for number of steps, distance traveled and walking speed. Oxygen consumption using each set of shoes at a range of speeds were measured in a laboratory setting and used to estimate metabolic energy expended during community-based walking. A survey measured subjective response to each pair of shoes. ResultsThe weighted shoes increased per-step energy cost by about 26%. Subjects strongly disliked the weighted shoes (P = 0.001) and found them tiring (P = 0.003). Despite this dislike, subjects did not significantly reduce distance walked (P = 0.6), number of steps (P = 0.7), or average speed (P = 0.9) compared to normal shoes. This led to a small but not statistically significant increase in energy expended during walking over a five-day period (12.3 {+/-} 9.6% increase, P = 0.2). On the final collection day this trend appeared to reverse, with fewer steps taken and lower metabolic energy expended with the weighted shoes. Twenty-four subjects were recruited but only ten completed the protocol, with dislike of the weighted shoe condition being the primary reason for dropout. ConclusionsIncreasing the energy cost of each step led to greater energy expended through walking. However, there are indications that behavioral changes would be greater with a longer intervention or increased retention. For example, the large dropout rate suggests that some subjects avoided walking with the weighted shoes entirely, simply by leaving the study. Follow-on studies among patient groups may reveal a fitness benefit to either increasing or reducing the energy cost of walking.

animal behavior and cognition↗

bioRxiv2021

Transcription factor induction of vascular blood stem cell niches in vivo

The hematopoietic niche is a supportive microenvironment comprised of distinct cell types, including specialized vascular endothelial cells that directly interact with hematopoietic stem and progenitor cells (HSPCs). The molecular factors that specify niche endothelial cells and orchestrate HSPC homeostasis remain largely unknown. Using multi-dimensional gene expression and chromatin accessibility analyses, we define a conserved gene expression signature and cis-regulatory landscape unique to sinusoidal endothelial cells in the HSPC niche. Using enhancer mutagenesis and transcription factor overexpression, we elucidate a transcriptional code involving members of the Ets, Sox and Nuclear Hormone Receptor families that is sufficient to induce ectopic niche endothelial cells that associate with mesenchymal stromal cells and support the recruitment, maintenance and division of HSPCs in vivo. These studies set forth an approach for generating synthetic HSPC niches, in vitro or in vivo, and for effective therapies to modulate the endogenous niche.

developmental biology↗

bioRxiv2021

The Effects of Incline Level on Optimized Lower-Limb Exoskeleton Assistance

For exoskeletons to be successful in real-world settings, they will need to be effective across a variety of terrains, including on inclines. While some single-joint exoskeletons have assisted incline walking, recent successes in level-ground assistance suggest that greater improvements may be possible by optimizing assistance of the whole leg. To understand how exoskeleton assistance should change with incline, we used human-in-the-loop optimization to find whole-leg exoskeleton assistance torques that minimized metabolic cost on a range of grades. We optimized assistance for three expert, able-bodied participants on 5 degree, 10 degree and 15 degree inclines using a hip-knee-ankle exoskeleton emulator. For all assisted conditions, the cost of transport was reduced by at least 50% relative to walking in the device with no assistance, a large improvement to walking that is comparable to the benefits of whole-leg assistance on level-ground. This corresponds to large absolute reductions in metabolic cost, with the most strenuous conditions reduced by 4.9 W/kg, more than twice the entire energy cost of level walking. Optimized extension torque magnitudes and exoskeleton power increased with incline, with hip extension, knee extension and ankle plantarflexion often growing as large as allowed by comfort-based limits. Applied powers on steep inclines were double the powers applied during level-ground walking, indicating that larger exoskeleton power may be optimal in scenarios where biological powers and costs are higher. Future exoskeleton devices can be expected to deliver large improvements in walking performance across a range of inclines, if they have sufficient torque and power capabilities.

bioengineering↗

bioRxiv2021

The Split-Belt Rimless Wheel

Split-belt treadmill training, common in stroke rehabilitation and motor learning experiments, reveals a mechanism through which energy can be extracted from the environment. People can extract net positive work from a split-belt treadmill by lengthening their step onto the fast belt. To understand how leg angles and belt speed differences affect energy transfer between the treadmill and the person during split-belt walking, we simulated a split-belt rimless wheel that alternates rotating on fast and slow treadmill belts. We found that the split-belt rimless wheel can passively walk steadily forward under a range of conditions, extracting enough energy from the treadmill to overcome losses during collisions. The simulated wheel can tolerate both speed disturbances and ground height variability, and it can even capture enough energy to walk uphill. We also built a physical split-belt rimless wheel robot, demonstrating the feasibility of energy extraction during split-belt treadmill walking. In comparing the wheel solutions to human split-belt gait, we found that humans do not maximize positive work performed by the treadmill; costs associated with balance and free vertical moments likely limit adaptation. This study characterizes the mechanics and energetics of split-belt walking, demonstrating that energy capture through intermittent contacts with the two belts is possible when the belt speed difference is paired with an asymmetry in leg angles at step-to-step transitions. This study demonstrates a novel way of harnessing energy through individual rotations rather than continuous contact and offers a simple model framework for understanding human choices during split-belt walking.

bioengineering↗

bioRxiv2021

How adaptation, training, and customization contribute to benefits from exoskeleton assistance

Exoskeletons can enhance human mobility, but we still know little about why they are effective. For example, we do not know the relative importance of training, how much is required, or what type is most effective; how people adapt with the device; or the relative benefits of customizing assistance. We conducted experiments in which naive users learned to walk with ankle exoskeletons under one of three training regimens characterized by different levels of variation in device behavior. Assistance was also customized for one group. Following moderate-variation training, the benefits of customized assistance were large; metabolic rate was reduced by 39% compared to walking with the exoskeleton turned off. Training contributed about half of this benefit and customization about one quarter; a generic controller reduced energy cost by 10% before training and 31% afterwards. Training required much more exposure than typical of exoskeleton studies, about 109 minutes of assisted walking. Type of training also had a strong effect; the low-variation group required twice as long as the moderate-variation group to become expert, while the high-variation group never acquired this level of expertise. Curiously, all users adapted in a way that resulted in less mechanical power from the exoskeleton as they gained expertise. Customizing assistance required less time than training for all parameters except peak torque magnitude, which grew slowly over the study, suggesting a longer time-scale adaptation in the person. These results underscore the importance of training to the benefits of exoskeleton assistance and suggest the topic deserves more attention.

neuroscience↗

bioRxiv2021

Optimized hip-knee-ankle exoskeleton assistance at a range of walking speeds

BackgroundEffective autonomous exoskeletons will need to be useful at a variety of walking speeds, but we do not know how optimal exoskeleton assistance should change with speed. Optimal exoskeleton assistance may increase with speed similar to biological torque changes or a well-tuned assistance profile may be effective at a variety of speeds. MethodsWe optimized hip-knee-ankle exoskeleton assistance to reduce metabolic cost for three participants walking at 1.0 m/s, 1.25 m/s and 1.5 m/s. We measured metabolic cost, muscle activity, exoskeleton assistance and kinematics. We performed two tailed paired t-tests to determine significance. ResultsExoskeleton assistance reduced the metabolic cost of walking compared to wearing the exoskeleton with no torque applied by 26%, 47% and 50% at 1.0, 1.25 and 1.5 m/s, respectively. For all three participants, optimized exoskeleton ankle torque was the smallest for slow walking, while hip and knee torque changed slightly with speed in ways that varied across participants. Total applied positive power increased with speed for all three participants, largely due to increased joint velocities, which consistently increased with speed. ConclusionsExoskeleton assistance is effective at a range of speeds and is most effective at medium and fast walking speeds. Exoskeleton assistance was less effective for slow walking, which may explain the limited success in reducing metabolic cost for patient populations through exoskeleton assistance. Exoskeleton designers may have more success when targeting activities and groups with faster walking speeds. Speed-related changes in optimized exoskeleton assistance varied by participant, indicating either the benefit of participant-specific tuning or that a wide variety of torque profiles are similarly effective.

bioengineering↗

bioRxiv2021

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 for three participants. 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. Knee-only assistance reduced the metabolic cost of walking by 13%, demonstrating that effective knee assistance is possible. Two-joint assistance reduced the metabolic cost of walking by between 34% and 42%, with the largest improvements coming from hip-ankle assistance. 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. 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.

bioengineering↗

bioRxiv2020

Shortcomings of human-in-the-loop optimization for an ankle-foot prosthesis: a case series

Human-in-the-loop optimization allows for individualized device control based on measured human performance. This technique has been used to produce large reductions in energy expenditure during walking with exoskeletons but has not yet been applied to prosthetic devices. In this series of case studies, we applied human-in-the-loop optimization to the control of an active ankle-foot prosthesis used by participants with unilateral transtibial amputation. We optimized the parameters of five control architectures that captured aspects of successful exoskeletons and commercial prostheses, but none resulted in significantly lower metabolic rate than generic control. In one control architecture, we increased the exposure time per condition by a factor of five, but the optimized controller still resulted in higher metabolic rate. Finally, we optimized for self-reported comfort instead of metabolic rate, but the resulting controller was not preferred. There are several reasons why human-in-the-loop optimization may have failed for people with amputation. Control architecture is an unlikely cause given the variety of controllers tested. The lack of effect likely relates to adaptation protocol or differences in the learning mechanisms or objectives of people with amputation. Future work should investigate these causes to determine whether human-in-the-loop optimization for prostheses could be successful.

bioengineering↗

bioRxiv2020

Teleoperation of an ankle-foot prosthesis with a wrist exoskeleton

ObjectiveWe aimed to develop a system for people with amputation that non-invasively restores missing control and sensory information for an ankle-foot prosthesis. MethodsIn our approach, a wrist exoskeleton allows people with amputation to control and receive feedback from their prosthetic ankle via teleoperation. We implemented two control schemes: position control with haptic feedback of ankle torque at the wrist; and torque control that allows the user to modify a baseline torque profile by moving their wrist against a virtual spring. We measured tracking error and frequency response for the ankle-foot prosthesis and the wrist exoskeleton. To demonstrate feasibility and evaluate system performance, we conducted an experiment in which one participant with a transtibial amputation tracked desired wrist trajectories during walking, while we measured wrist and ankle response. ResultsBenchtop testing demonstrated that for relevant walking frequencies, system error was below human perceptual error. During the walking experiment, the participant was able to voluntarily follow different wrist trajectories with an average RMS error of 1.55{degrees} after training. The ankle was also able to track desired trajectories below human perceptual error for both position control (RMSE = 0.8{degrees}) and torque control (RMSE = 8.4%). ConclusionWe present a system that allows a user with amputation to control an ankle-foot prosthesis and receive feedback about its state using a wrist exoskeleton, with accuracy comparable to biological neuromotor control. SignificanceThis bilateral teleoperation system enables novel prosthesis control and feedback strategies that could improve prosthesis control and aid motor learning.

bioengineering↗

bioRxiv2019

Using force data to self-pace an instrumented treadmill and measure self-selected walking speed

BackgroundSelf-selected speed is an important functional index of walking. A self-pacing controller that reliably matches walking speed without additional hardware can be useful for measuring self-selected speed in a treadmill-based laboratory. MethodsWe adapted a previously proposed self-pacing controller for force-instrumented treadmills and validated its use for measuring self-selected speeds. We first evaluated the controllers estimation of subject speed and position from the force-plates by comparing it to those from motion capture data. We then compared five tests of self-selected speed. Ten healthy adults completed a standard 10-meter walk test, a 150-meter walk test, a commonly used manual treadmill speed selection test, a two-minute self-paced treadmill test, and a 150-meter self-paced treadmill test. In each case, subjects were instructed to walk at or select their comfortable speed. We also assessed the time taken for a trial and a survey on comfort and ease of choosing a speed in all the tests. ResultsThe self-pacing algorithm estimated subject speed and position accurately, with root mean square differences compared to motion capture of 0.023 m s-1 and 0.014 m, respectively. Self-selected speeds from both self-paced treadmill tests correlated well with those from the 10-meter walk test (R > 0.93, p < 1 x 10-13). Subjects walked slower on average in the self-paced treadmill tests (1.23 {+/-} 0.27 m s-1) than in the 10-meter walk test (1.32 {+/-} 0.18 m s-1) but the speed differences within subjects were consistent. These correlations and walking speeds are comparable to those from the manual treadmill speed selection test (R = 0.89, p = 3 x 10-11; 1.18 {+/-} 0.24 m s-1). Comfort and ease of speed selection were similar in the self-paced tests and the manual speed selection test, but the self-paced tests required only about a third of the time to complete. Our results demonstrate that these self-paced treadmill tests can be a strong alternative to the commonly used manual treadmill speed selection test. ConclusionsThe self-paced force-instrumented treadmill well adapts to subject walking speed and reliably measures self-selected walking speeds. We provide the self-pacing software to facilitate use by gait researchers and clinicians.

bioengineering↗

bioRxiv2018

Rapid energy expenditure estimation for assisted and inclined loaded walking

BackgroundEstimating energy expenditure with indirect calorimetry requires expensive equipment and provides slow and noisy measurements. Rapid estimates using wearable sensors would enable techniques like optimizing assistive devices outside a lab. Existing methods correlate data from wearable sensors to measured energy expenditure without evaluating the accuracy of the estimated energy expenditure for activity conditions or subjects not included in the correlation process. Our goal is to assess data-driven models that are capable of rapidly estimating energy expenditure for new conditions and subjects.\n\nMethodsWe developed models that estimated energy expenditure from two datasets during walking conditions with (1) ankle exoskeleton assistance and (2) various loads and inclines. The estimation was portable and rapid, using input features that are possible to measure with wearable sensors and restricting the input data length to a single gait cycle or four second interval. The performance of the models was evaluated for three use cases. The first case estimated energy expenditure during walking conditions for subjects with some subject specific training data available. The second case estimated all conditions in the dataset for a new subject not included in the training data. The third case estimated new conditions for a new subject. The models also ordered the magnitude of energy expenditure across all conditions for a new subject.\n\nResultsThe average errors in energy expenditure estimation during assisted walking conditions were 4.4%, 8.0%, and 8.1% for the three use cases, respectively. The average errors in energy expenditure estimation during inclined and loaded walking conditions were 6.1%, 9.7%, and 11.7% for the three use cases. The models ordered the magnitude of energy expenditure with a maximum and average percentage of correctly ordered conditions of 56% and 43% for assisted walking and 85% and 55% for incline and loaded walking.\n\nConclusionsOur data-driven models determined the accuracy of energy expenditure estimation for three use cases. For experiments where the accuracy of a data-driven model is sufficient, standard indirect calorimetry can be replaced. The energy expenditure ordering could aid in selecting optimal assistance conditions. The models, code, and datasets are provided for reproduction and extension of our results.

bioengineering↗