Muscle coordination retraining inspired by musculoskeletal simulations reduces knee contact force.

Humans typically coordinate their muscles to meet movement objectives like minimizing energy expenditure. In the presence of pathology, new objectives gain importance, like reducing loading in an osteoarthritic joint, but people often do not change their muscle coordination patterns to meet these new objectives. Here we use musculoskeletal simulations to identify simple changes in coordination that can be taught using electromyographic biofeedback, achieving the therapeutic goal of reducing joint loading. Our simulations predicted that changing the relative activation of two redundant ankle plantarflexor muscles-the gastrocnemius and soleus-could reduce knee contact force during walking, but it was unclear whether humans could re-coordinate redundant muscles during a complex task like walking. Our experiments showed that after a single session of walking with biofeedback of summary measures of plantarflexor muscle activation, healthy individuals reduced the ratio of gastrocnemius-to-soleus muscle activation by 25 ± 15% (p = 0.004, paired t test, n = 10). Participants who walked with this "gastrocnemius avoidance" gait pattern reduced late-stance knee contact force by 12 ± 12% (p = 0.029, paired t test, n = 8). Simulation-informed coordination retraining could be a promising treatment for knee osteoarthritis and a powerful tool for optimizing coordination for a variety of rehabilitation and performance applications.

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.

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.

Foot strike pattern during running alters muscle-tendon dynamics of the gastrocnemius and the soleus.

Running is thought to be an efficient gait due, in part, to the behavior of the plantar flexor muscles and elastic energy storage in the Achilles tendon. Although plantar flexor muscle mechanics and Achilles tendon energy storage have been explored during rearfoot striking, they have not been fully characterized during forefoot striking. This study examined how plantar flexor muscle-tendon mechanics during running differs between rearfoot and forefoot striking. We used musculoskeletal simulations, driven by joint angles and electromyography recorded from runners using both rearfoot and forefoot striking running patterns, to characterize plantar flexor muscle-tendon mechanics. The simulations revealed that foot strike pattern affected the soleus and gastrocnemius differently. For the soleus, forefoot striking decreased tendon energy storage and fiber work done while the muscle fibers were shortening compared to rearfoot striking. For the gastrocnemius, forefoot striking increased muscle activation and fiber work done while the muscle fibers were lengthening compared to rearfoot striking. These changes in gastrocnemius mechanics suggest that runners planning to convert to forefoot striking might benefit from a progressive eccentric gastrocnemius strengthening program to avoid injury.

Connecting the legs with a spring improves human running economy.

Human running is inefficient. For every 10 calories burned, less than 1 is needed to maintain a constant forward velocity - the remaining energy is, in a sense, wasted. The majority of this wasted energy is expended to support the bodyweight and redirect the center of mass during the stance phase of gait. An order of magnitude less energy is expended to brake and accelerate the swinging leg. Accordingly, most devices designed to increase running efficiency have targeted the costlier stance phase of gait. An alternative approach is seen in nature: spring-like tissues in some animals and humans are believed to assist leg swing. While it has been assumed that such a spring simply offloads the muscles that swing the legs, thus saving energy, this mechanism has not been experimentally investigated. Here, we show that a spring, or 'exotendon', connecting the legs of a human reduces the energy required for running by 6.4±2.8%, and does so through a complex mechanism that produces savings beyond those associated with leg swing. The exotendon applies assistive forces to the swinging legs, increasing the energy optimal stride frequency. Runners then adopt this frequency, taking faster and shorter strides, and reduce the joint mechanical work to redirect their center of mass. Our study shows how a simple spring improves running economy through a complex interaction between the changing dynamics of the body and the adaptive strategies of the runner, highlighting the importance of considering each when designing systems that couple human and machine.

Heuristic-Based Ankle Exoskeleton Control for Co-Adaptive Assistance of Human Locomotion.

Assisting human locomotion with exoskeletons is challenging, largely due to the complexity of the neuromusculoskeletal system, the time-varying dynamics that accompany motor learning, and the uniqueness of every individual's response to device assistance. Assistance strategies designed to keep the human "in-the-loop" can help overcome many of these challenges. The purpose of this study was to develop a human-in-the-loop assistance strategy that uses co-adaptive control to slowly and continuously respond to biomechanical changes thought to encode the user's needs. Online measurements of muscle activity and joint kinematics were used to guide the evolution of an exoskeleton torque pattern based on the following heuristics: 1) muscle activity that acts cooperatively with the exoskeleton indicates the user wants more torque; 2) muscle activity that acts antagonistically to the exoskeleton indicates the user wants less torque; and 3) torque should stop increasing if the user is not adapting. We applied our controller to tethered, bilateral ankle exoskeletons worn by naïve participants as they walked on a treadmill at 1.25 m · s-1 for 30 minutes. The evolved torque profiles reduced the root-mean-square of soleus muscle activity by 35±12% and metabolic rate by 22±8% compared to walking with the exoskeletons while they provided no torque. This was equivalent to a 9±12% reduction in metabolic rate when compared to normal walking. Furthermore, the algorithm was responsive to changes in each user's coordination patterns. These results confirm the effectiveness of the controller and suggest a new approach to exoskeleton assistance aimed at fostering co-adaptation with the user. This technique might particularly benefit individuals with age-related muscle weakness.

Human-in-the-loop optimization of exoskeleton assistance during walking.

Exoskeletons and active prostheses promise to enhance human mobility, but few have succeeded. Optimizing device characteristics on the basis of measured human performance could lead to improved designs. We have developed a method for identifying the exoskeleton assistance that minimizes human energy cost during walking. Optimized torque patterns from an exoskeleton worn on one ankle reduced metabolic energy consumption by 24.2 ± 7.4% compared to no torque. The approach was effective with exoskeletons worn on one or both ankles, during a variety of walking conditions, during running, and when optimizing muscle activity. Finding a good generic assistance pattern, customizing it to individual needs, and helping users learn to take advantage of the device all contributed to improved economy. Optimization methods with these features can substantially improve performance.

Muscle recruitment and coordination with an ankle exoskeleton.

Exoskeletons have the potential to assist and augment human performance. Understanding how users adapt their movement and neuromuscular control in response to external assistance is important to inform the design of these devices. The aim of this research was to evaluate changes in muscle recruitment and coordination for ten unimpaired individuals walking with an ankle exoskeleton. We evaluated changes in the activity of individual muscles, cocontraction levels, and synergistic patterns of muscle coordination with increasing exoskeleton work and torque. Participants were able to selectively reduce activity of the ankle plantarflexors with increasing exoskeleton assistance. Increasing exoskeleton net work resulted in greater reductions in muscle activity than increasing exoskeleton torque. Patterns of muscle coordination were not restricted or constrained to synergistic patterns observed during unassisted walking. While three synergies could describe nearly 95% of the variance in electromyography data during unassisted walking, these same synergies could describe only 85-90% of the variance in muscle activity while walking with the exoskeleton. Synergies calculated with the exoskeleton demonstrated greater changes in synergy weights with increasing exoskeleton work versus greater changes in synergy activations with increasing exoskeleton torque. These results support the theory that unimpaired individuals do not exclusively use central pattern generators or other low-level building blocks to coordinate muscle activity, especially when learning a new task or adapting to external assistance, and demonstrate the potential for using exoskeletons to modulate muscle recruitment and coordination patterns for rehabilitation or performance.

Muscle-tendon mechanics explain unexpected effects of exoskeleton assistance on metabolic rate during walking.

The goal of this study was to gain insight into how ankle exoskeletons affect the behavior of the plantarflexor muscles during walking. Using data from previous experiments, we performed electromyography-driven simulations of musculoskeletal dynamics to explore how changes in exoskeleton assistance affected plantarflexor muscle-tendon mechanics, particularly for the soleus. We used a model of muscle energy consumption to estimate individual muscle metabolic rate. As average exoskeleton torque was increased, while no net exoskeleton work was provided, a reduction in tendon recoil led to an increase in positive mechanical work performed by the soleus muscle fibers. As net exoskeleton work was increased, both soleus muscle fiber force and positive mechanical work decreased. Trends in the sum of the metabolic rates of the simulated muscles correlated well with trends in experimentally observed whole-body metabolic rate (R2=0.9), providing confidence in our model estimates. Our simulation results suggest that different exoskeleton behaviors can alter the functioning of the muscles and tendons acting at the assisted joint. Furthermore, our results support the idea that the series tendon helps reduce positive work done by the muscle fibers by storing and returning energy elastically. We expect the results from this study to promote the use of electromyography-driven simulations to gain insight into the operation of muscle-tendon units and to guide the design and control of assistive devices.

An experimental comparison of the relative benefits of work and torque assistance in ankle exoskeletons.

Techniques proposed for assisting locomotion with exoskeletons have often included a combination of active work input and passive torque support, but the physiological effects of different assistance techniques remain unclear. We performed an experiment to study the independent effects of net exoskeleton work and average exoskeleton torque on human locomotion. Subjects wore a unilateral ankle exoskeleton and walked on a treadmill at 1.25 m·s(-1) while net exoskeleton work rate was systematically varied from -0.054 to 0.25 J·kg(-1)·s(-1), with constant (0.12 N·m·kg(-1)) average exoskeleton torque, and while average exoskeleton torque was systematically varied from approximately zero to 0.18 N·m·kg(-1), with approximately zero net exoskeleton work. We measured metabolic rate, center-of-mass mechanics, joint mechanics, and muscle activity. Both techniques reduced effort-related measures at the assisted ankle, but this form of work input reduced metabolic cost (-17% with maximum net work input) while this form of torque support increased metabolic cost (+13% with maximum average torque). Disparate effects on metabolic rate seem to be due to cascading effects on whole body coordination, particularly related to assisted ankle muscle dynamics and the effects of trailing ankle behavior on leading leg mechanics during double support. It would be difficult to predict these results using simple walking models without muscles or musculoskeletal models that assume fixed kinematics or kinetics. Data from this experiment can be used to improve predictive models of human neuromuscular adaptation and guide the design of assistive devices.

Inducing self-selected human engagement in robotic locomotion training.

Stroke leads to severe mobility impairments for millions of individuals each year. Functional outcomes can be improved through manual treadmill therapy, but high costs limit patient exposure and, thereby, outcomes. Robotic gait training could increase the viable duration and frequency of training sessions, but robotic approaches employed thus far have been less effective than manual therapy. These shortcomings may relate to subconscious energy-minimizing drives, which might cause patients to engage less actively in therapy when provided with corrective robotic assistance. We have devised a new method for gait rehabilitation that harnesses, rather than fights, least-effort tendencies. Therapeutic goals, such as increased use of the paretic limb, are made easier than the patient's nominal gait through selective assistance from a robotic platform. We performed a pilot test on a healthy subject (N = 1) in which altered self-selected stride length was induced using a tethered robotic ankle-foot orthosis. The subject first walked on a treadmill while wearing the orthosis with and without assistance at unaltered and voluntarily altered stride length. Voluntarily increasing stride length by 5% increased metabolic energy cost by 4%. Robotic assistance decreased energy cost at both unaltered and voluntarily increased stride lengths, by 6% and 8% respectively. We then performed a test in which the robotic system continually monitored stride length and provided more assistance if the subject's stride length approached a target increase. This adaptive assistance protocol caused the subject to slowly adjust their gait patterns towards the target, leading to a 4% increase in stride length. Metabolic energy consumption was simultaneously reduced by 5%. These results suggest that selective-assistance protocols based on targets relevant to rehabilitation might lead patients to self-select desirable gait patterns during robotic gait training sessions, possibly facilitating better adherence and outcomes.