AdjuSST: An Adjustable Surface Stiffness Treadmill.

Humans have the remarkable ability to manage foot-ground interaction seamlessly across terrain changes despite the high dynamic complexity of the task. Understanding how adaptation in the neuromotor system enables this level of robustness in the face of changing interaction dynamics is critical for developing more effective gait retraining interventions. We developed an adjustable surface stiffness treadmill (AdjuSST) to trigger these adaptation mechanisms and enable studies to better understand human adaptation to changing foot-ground dynamics. The AdjuSST system makes use of fundamental beam-bending principles; it controls surface stiffness by controlling the effective length of a cantilever beam. The beam acts as a spring suspension for the transverse endpoint load applied through the treadmill. The system is capable of enforcing a stiffness range of 15-300kN/m within 340 ms, deflecting linearly downwards up to 10 cm, and comfortably accommodating two full steps of travel along the belt. AdjuSST offers significant enhancements in effective walking surface length compared to similar systems, while also maintaining a useful stiffness range and responsive spring suspension. These improvements enhance our ability to study locomotor control and adaptation to changes in surface stiffness, as well as provide new avenues for gait rehabilitation.

Gait Adaptation to Asymmetric Hip Stiffness Applied by a Robotic Exoskeleton.

Wearable exoskeletons show significant potential for improving gait impairments, such as interlimb asymmetry. However, a more profound understanding of whether exoskeletons are capable of eliciting neural adaptation is needed. This study aimed to characterize how individuals adapt to bilateral asymmetric joint stiffness applied by a hip exoskeleton, similar to split-belt treadmill training. Thirteen unimpaired individuals performed a walking trial on the treadmill while wearing the exoskeleton. The right side of the exoskeleton acted as a positive stiffness torsional spring, pulling the thigh towards the neutral standing position, while the left acted as a negative stiffness spring pulling the thigh away from the neutral standing position. The results showed that this intervention applied by a hip exoskeleton elicited adaptation in spatiotemporal and kinetic gait measures similar to split-belt treadmill training. These results demonstrate the potential of the proposed intervention for retraining symmetric gait.

Gait adaptation to asymmetric hip stiffness applied by a robotic exoskeleton.

Wearable exoskeletons show significant potential for improving gait impairments, such as interlimb asymmetry. However, a more profound understanding of whether exoskeletons are capable of eliciting neural adaptation is needed. This study aimed to characterize how individuals adapt to bilateral asymmetric joint stiffness applied by a hip exoskeleton, similar to split-belt treadmill training. Thirteen unimpaired individuals performed a walking trial on the treadmill while wearing the exoskeleton. The right side of the exoskeleton acted as a positive stiffness torsional spring, pulling the thigh towards the neutral standing position, while the left acted as a negative stiffness spring pulling the thigh away from the neutral standing position. The results showed that this intervention applied by a hip exoskeleton elicited adaptation in spatiotemporal and kinetic gait measures similar to split-belt treadmill training. These results demonstrate the potential of the proposed intervention for retraining symmetric gait.

Minimum effort simulations of split-belt treadmill walking exploit asymmetry to reduce metabolic energy expenditure.

Walking on a split-belt treadmill elicits an adaptation response that changes baseline step length asymmetry. The underlying causes of this adaptation, however, are difficult to determine. It has been proposed that effort minimization may drive this adaptation, based on the idea that adopting longer steps on the fast belt, or positive step length asymmetry (SLA), can cause the treadmill to exert net-positive mechanical work on a bipedal walker. However, humans walking on split-belt treadmills have not been observed to reproduce this behavior when allowed to freely adapt. To determine if an effort-minimization motor control strategy would result in experimentally observed adaptation patterns, we conducted simulations of walking on different combinations of belt speeds with a human musculoskeletal model that minimized muscle excitations and metabolic rate. The model adopted increasing amounts of positive SLA and decreased its net metabolic rate with increasing belt speed difference, reaching +42.4% SLA and -5.7% metabolic rate relative to tied-belt walking at our maximum belt speed ratio of 3:1. These gains were primarily enabled by an increase in braking work and a reduction in propulsion work on the fast belt. The results suggest that a purely effort minimization driven split-belt walking strategy would involve substantial positive SLA, and that the lack of this characteristic in human behavior points to additional factors influencing the motor control strategy, such as aversion to excessive joint loads, asymmetry, or instability.NEW & NOTEWORTHY Behavioral observations of split-belt treadmill adaptation have been inconclusive toward its underlying causes. To estimate gait patterns when driven exclusively by one of these possible underlying causes, we simulated split-belt treadmill walking with a musculoskeletal model that minimized its summed muscle excitations. Our model took significantly longer steps on the fast belt and reduced its metabolic rate below tied-belt walking, unlike experimental observations. This suggests that asymmetry is energetically optimal, but human adaptation involves additional factors.

Bilateral asymmetric hip stiffness applied by a robotic hip exoskeleton elicits kinematic and kinetic adaptation.

Wearable robotic exoskeletons hold great promise for gait rehabilitation as portable, accessible tools. However, a better understanding of the potential for exoskeletons to elicit neural adaptation-a critical component of neurological gait rehabilitation-is needed. In this study, we investigated whether humans adapt to bilateral asymmetric stiffness perturbations applied by a hip exoskeleton, taking inspiration from asymmetry augmentation strategies used in split-belt treadmill training. During walking, we applied torques about the hip joints to repel the thigh away from a neutral position on the left side and attract the thigh toward a neutral position on the right side. Six participants performed an adaptation walking trial on a treadmill while wearing the exoskeleton. The exoskeleton elicited time-varying changes and aftereffects in step length and propulsive/braking ground reaction forces, indicating behavioral signatures of neural adaptation. These responses resemble typical responses to split-belt treadmill training, suggesting that the proposed intervention with a robotic hip exoskeleton may be an effective approach to (re)training symmetric gait.

Role of path information in visual perception of joint stiffness.

Humans have an astonishing ability to extract hidden information from the movement of others. In previous work, subjects observed the motion of a simulated stick-figure, two-link planar arm and estimated its stiffness. Fundamentally, stiffness is the relation between force and displacement. Given that subjects were unable to physically interact with the simulated arm, they were forced to make their estimates solely based on observed kinematic information. Remarkably, subjects were able to correctly correlate their stiffness estimates with changes in the simulated stiffness, despite the lack of force information. We hypothesized that subjects were only able to do this because the controller used to produce the simulated arm's movement, composed of oscillatory motions driving mechanical impedances, resembled the controller humans use to produce their own movement. However, it is still unknown what motion features subjects used to estimate stiffness. Human motion exhibits systematic velocity-curvature patterns, and it has previously been shown that these patterns play an important role in perceiving and interpreting motion. Thus, we hypothesized that manipulating the velocity profile should affect subjects' ability to estimate stiffness. To test this, we changed the velocity profile of the simulated two-link planar arm while keeping the simulated joint paths the same. Even with manipulated velocity signals, subjects were still able to estimate changes in simulated joint stiffness. However, when subjects were shown the same simulated path with different velocity profiles, they perceived motions that followed a veridical velocity profile to be less stiff than that of a non-veridical profile. These results suggest that path information (displacement) predominates over temporal information (velocity) when humans use visual observation to estimate stiffness.

Dynamic Primitives Limit Human Force Regulation during Motion.

Humans excel at physical interaction despite long feedback delays and low-bandwidth actuators. Yet little is known about how humans manage physical interaction. A quantitative understanding of how they do is critical for designing machines that can safely and effectively interact with humans, e.g. amputation prostheses, assistive exoskeletons, therapeutic rehabilitation robots, and physical human-robot collaboration. To facilitate applications, this understanding should be in the form of a simple mathematical model that not only describes humans' capabilities but also their limitations. In robotics, hybrid control allows simultaneous, independent control of both motion and force and it is often assumed that humans can modulate force independent of motion as well. This paper experimentally tested that assumption. Participants were asked to apply a constant 5N force on a robot manipulandum that moved along an elliptical path. After initial improvement, force errors quickly plateaued, despite practice and visual feedback. Within-trial analyses revealed that force errors varied with position on the ellipse, rejecting the hypothesis that humans have independent control of force and motion. The findings are consistent with a feed-forward motion command composed of two primitive oscillations acting through mechanical impedance to evoke force.

Gait Entrainment to Torque Pulses From a Hip Exoskeleton Robot.

Robot-aided locomotor rehabilitation has proven challenging. To facilitate progress, it is important to first understand the neuro-mechanical dynamics and control of unimpaired human locomotion. Our previous studies found that human gait entrained to periodic torque pulses at the ankle when the pulse period was close to preferred stride duration. Moreover, synchronized gait exhibited a constant phase relation with the pulses so that the robot provided mechanical assistance. To test the generality of mechanical gait entrainment, this study characterized unimpaired human subjects' responses to periodic torque pulses during overground walking. The intervention was applied by a hip exoskeleton robot, Samsung GEMS-H. Gait entrainment was assessed based on the time-course of the phase at which torque pulses occurred within each stride. Experiments were conducted for two consecutive days to evaluate whether the second day elicited more entrainment. Whether entrainment was affected by the difference between pulse period and preferred stride duration was also assessed. Results indicated that the intervention evoked gait entrainment that occurred more often when the period of perturbation was closer to subjects' preferred stride duration, but the difference between consecutive days was insignificant. Entrainment was accompanied by convergence of pulse phase to a similar value across all conditions, where the robot maximized mechanical assistance. Clear evidence of motor adaptation indicated the potential of the intervention for rehabilitation. This study quantified important aspects of the nonlinear neuro-mechanical dynamics underlying unimpaired human walking, which will inform the development of effective approaches to robot-aided locomotor rehabilitation, exploiting natural dynamics in a minimally-encumbering way.

Applying Hip Stiffness With an Exoskeleton to Compensate Gait Kinematics.

Neurological disorders and aging induce impaired gait kinematics. Despite recent advances, effective methods using lower-limb exoskeleton robots to restore gait kinematics are as yet limited. In this study, applying virtual stiffness using a hip exoskeleton was investigated as a possible method to guide users to change their gait kinematics. With a view to applications in locomotor rehabilitation, either to provide assistance or promote recovery, this study assessed whether imposed stiffness induced changes in the gait pattern during walking; and whether any changes persisted upon removal of the intervention, which would indicate changes in central neuro-motor control. Both positive and negative stiffness induced immediate and persistent changes of gait kinematics. However, the results showed little behavioral evidence of persistent changes in neuro-motor control, not even short-lived aftereffects. In addition, stride duration was little affected, suggesting that at least two dissociable layers exist in the neuro-motor control of human walking. The lack of neuro-motor adaptation suggests that, within broad limits, the central nervous system is surprisingly indifferent to the details of lower limb kinematics. The lack of neuro-motor adaptation also suggests that alternative methods may be required to implement a therapeutic technology to promote recovery. However, the immediate, significant, and reproducible changes in kinematics suggest that applying hip stiffness with an exoskeleton may be an effective assistive technology for compensation.

Rigid soles improve balance in beam walking, but improvements do not persist with bare feet.

Maintaining balance while walking on a narrow beam is a challenging motor task. One important factor is that the foot's ability to exert torque on the support surface is limited by the beam width. Still, the feet serve as a critical interface between the body and the external environment, and it is unclear how the mechanical properties of the feet affect balance. This study examined how constraining the motion of the foot joints with rigid soles influenced balance performance when walking on a beam. We recorded whole-body kinematics of subjects with varying skill levels as they walked on a narrow beam with and without wearing flat, rigid soles on their feet. We computed changes in whole-body motion and angular momentum across the two conditions. Results showed that walking with rigid soles improved balance performance in both expert and novice subjects, but that improvements in balance performance with rigid soles did not affect or transfer to subsequent task performance with bare feet. The absence of any aftereffects suggested that the improved balance performance resulting from constraining the foot joints by a rigid sole was the result of a mechanical effect rather than a change in neural control. Although wearing rigid soles can be used to assist balance, there appears to be limited benefit for training or rehabilitation of balance ability.

Learning and transfer of complex motor skills in virtual reality: a perspective review.

The development of more effective rehabilitative interventions requires a better understanding of how humans learn and transfer motor skills in real-world contexts. Presently, clinicians design interventions to promote skill learning by relying on evidence from experimental paradigms involving simple tasks, such as reaching for a target. While these tasks facilitate stringent hypothesis testing in laboratory settings, the results may not shed light on performance of more complex real-world skills. In this perspective, we argue that virtual environments (VEs) are flexible, novel platforms to evaluate learning and transfer of complex skills without sacrificing experimental control. Specifically, VEs use models of real-life tasks that afford controlled experimental manipulations to measure and guide behavior with a precision that exceeds the capabilities of physical environments. This paper reviews recent insights from VE paradigms on motor learning into two pressing challenges in rehabilitation research: 1) Which training strategies in VEs promote complex skill learning? and 2) How can transfer of learning from virtual to real environments be enhanced? Defining complex skills by having nested redundancies, we outline findings on the role of movement variability in complex skill acquisition and discuss how VEs can provide novel forms of guidance to enhance learning. We review the evidence for skill transfer from virtual to real environments in typically developing and neurologically-impaired populations with a view to understanding how differences in sensory-motor information may influence learning strategies. We provide actionable suggestions for practicing clinicians and outline broad areas where more research is required. Finally, we conclude that VEs present distinctive experimental platforms to understand complex skill learning that should enable transfer from therapeutic practice to the real world.

Visual perception of joint stiffness from multijoint motion.

Humans have an astonishing ability to extract hidden information from the movements of others. For example, even with limited kinematic information, humans can distinguish between biological and nonbiological motion, identify the age and gender of a human demonstrator, and recognize what action a human demonstrator is performing. It is unknown, however, whether they can also estimate hidden mechanical properties of another's limbs simply by observing their motions. Strictly speaking, identifying an object's mechanical properties, such as stiffness, requires contact. With only motion information, unambiguous measurements of stiffness are fundamentally impossible, since the same limb motion can be generated with an infinite number of stiffness values. However, we show that humans can readily estimate the stiffness of a simulated limb from its motion. In three experiments, we found that participants linearly increased their rating of arm stiffness as joint stiffness parameters in the arm controller increased. This was remarkable since there was no physical contact with the simulated limb. Moreover, participants had no explicit knowledge of how the simulated arm was controlled. To successfully map nontrivial changes in multijoint motion to changes in arm stiffness, participants likely drew on prior knowledge of human neuromotor control. Having an internal representation consistent with the behavior of the controller used to drive the simulated arm implies that this control policy competently captures key features of veridical biological control. Finding that humans can extract latent features of neuromotor control from kinematics also provides new insight into how humans interpret the motor actions of others. NEW & NOTEWORTHY Humans can visually perceive another's overt motion, but it is unknown whether they can also perceive the hidden dynamic properties of another's limbs from their motions. Here, we show that humans can correctly infer changes in limb stiffness from nontrivial changes in multijoint limb motion without force information or explicit knowledge of the underlying limb controller. Our findings suggest that humans presume others control motor behavior in such a way that limb stiffness influences motion.

Velocity-curvature patterns limit human-robot physical interaction.

Physical human-robot collaboration is becoming more common, both in industrial and service robotics. Cooperative execution of a task requires intuitive and efficient interaction between both actors. For humans, this means being able to predict and adapt to robot movements. Given that natural human movement exhibits several robust features, we examined whether human-robot physical interaction is facilitated when these features are considered in robot control. The present study investigated how humans adapt to biological and non-biological velocity patterns in robot movements. Participants held the end-effector of a robot that traced an elliptic path with either biological (two-thirds power law) or non-biological velocity profiles. Participants were instructed to minimize the force applied on the robot end-effector. Results showed that the applied force was significantly lower when the robot moved with a biological velocity pattern. With extensive practice and enhanced feedback, participants were able to decrease their force when following a non-biological velocity pattern, but never reached forces below those obtained with the 2/3 power law profile. These results suggest that some robust features observed in natural human movements are also a strong preference in guided movements. Therefore, such features should be considered in human-robot physical collaboration.

Author Correction: Low-dimensional organization of angular momentum during walking on a narrow beam.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Exploiting the geometry of the solution space to reduce sensitivity to neuromotor noise.

Throwing is a uniquely human skill that requires a high degree of coordination to successfully hit a target. Timing of ball release appears crucial as previous studies report required timing accuracies as short as 1-2ms, which however appear physiologically challenging. This study mathematically and experimentally demonstrates that humans can overcome these seemingly stringent timing requirements by shaping their hand trajectories to create extended timing windows, where ball releases achieve target hits despite temporal imprecision. Subjects practiced four task variations in a virtual environment, each with a distinct geometry of the solution space and different demands for timing. Model-based analyses of arm trajectories revealed that subjects first decreased timing error, followed by lengthening timing windows in their hand trajectories. This pattern was invariant across solution spaces, except for a control case. Hence, the exquisite skill that humans evolved for throwing is achieved by developing strategies that are less sensitive to temporal variability arising from neuromotor noise. This analysis also provides an explanation why coaches emphasize the "follow-through" in many ball sports.

Low-dimensional organization of angular momentum during walking on a narrow beam.

Walking on a beam is a challenging motor skill that requires the regulation of upright balance and stability. The difficulty in beam walking results from the reduced base of support compared to that afforded by flat ground. One strategy to maintain stability and hence avoid falling off the beam is to rotate the limb segments to control the body's angular momentum. The aim of this study was to examine the coordination of the angular momentum variations during beam walking. We recorded movement kinematics of participants walking on a narrow beam and computed the angular momentum contributions of the body segments with respect to three different axes. Results showed that, despite considerable variability in the movement kinematics, the angular momentum was characterized by a low-dimensional organization based on a small number of segmental coordination patterns. When the angular momentum was computed with respect to the beam axis, the largest fraction of its variation was accounted for by the trunk segment. This simple organization was robust and invariant across all participants. These findings support the hypothesis that control strategies for complex balancing tasks might be easier to understand by investigating angular momentum instead of the segmental kinematics.

CONTROLLING PHYSICAL INTERACTIONS: HUMANS DO NOT MINIMIZE MUSCLE EFFORT.

Physical interaction with tools is ubiquitous in functional activities of daily living. While tool use is considered a hallmark of human behavior, how humans control such physical interactions is still poorly understood. When humans perform a motor task, it is commonly suggested that the central nervous system coordinates the musculo-skeletal system to minimize muscle effort. In this paper, we tested if this notion holds true for motor tasks that involve physical interaction. Specifically, we investigated whether humans minimize muscle forces to control physical interaction with a circular kinematic constraint. Using a simplified arm model, we derived three predictions for how humans should behave if they were minimizing muscular effort to perform the task. First, we predicted that subjects would exert workless, radial forces on the constraint. Second, we predicted that the muscles would be deactivated when they could not contribute to work. Third, we predicted that when moving very slowly along the constraint, the pattern of muscle activity would not differ between clockwise (CW) and counterclockwise (CCW) motions. To test these predictions, we instructed human subjects to move a robot handle around a virtual, circular constraint at a constant tangential velocity. To reduce the effect of forces that might arise from incomplete compensation of neuro-musculoskeletal dynamics, the target tangential speed was set to an extremely slow pace (~1 revolution every 13.3 seconds). Ultimately, the results of human experiment did not support the predictions derived from our model of minimizing muscular effort. While subjects did exert workless forces, they did not deactivate muscles as predicted. Furthermore, muscle activation patterns differed between CW and CCW motions about the constraint. These findings demonstrate that minimizing muscle effort is not a significant factor in human performance of this constrained-motion task. Instead, the central nervous system likely prioritizes reducing other costs, such as computational effort, over muscle effort to control physical interactions.

Persistence of reduced neuromotor noise in long-term motor skill learning.

It is well documented that variability in motor performance decreases with practice, yet the neural and computational mechanisms that underlie this decline, particularly during long-term practice, are little understood. Decreasing variability is frequently examined in terms of error corrections from one trial to the next. However, the ubiquitous noise from all levels of the sensorimotor system is also a significant contributor to overt variability. While neuromotor noise is typically assumed and modeled as immune to practice, the present study challenged this notion. We investigated the long-term practice of a novel motor skill to test whether neuromotor noise can be attenuated, specifically when aided by reward. Results showed that both reward and self-guided practice over 11 days improved behavior by decreasing noise rather than effective error corrections. When the challenge for obtaining reward increased, subjects reduced noise even further. Importantly, when task demands were relaxed again, this reduced level of noise persisted for 5 days. A stochastic learning model replicated both the attenuation and persistence of noise by scaling the noise amplitude as a function of reward. More insight into variability and intrinsic noise and its malleability has implications for training and rehabilitation interventions.

Girls can play ball: Stereotype threat reduces variability in a motor skill.

The majority of research on stereotype threat shows what is expected: threat debilitates performance. However, facilitation is also possible, although seldom reported. This study investigated how stereotype threat influences novice females when performing the sensorimotor task of bouncing a ball to a target. We tested the predictions of two prevailing accounts for debilitation and facilitation due to sterotype threat effects: working memory and mere effort. Experimental results showed that variability in performance decreased more in stigmatized females than in control females, consistent with the prediction of the mere effort account, but inconsistent with the working memory account. These findings suggest that stereotype threat effects may be predicated upon the correctness of the dominant motor behavior, rather than on a novice-expert distinction or task difficulty. Further, a comprehensive understanding should incorporate the fact that stereotype threat can facilitate, as well as debilitate, performance.

Implicit guidance to stable performance in a rhythmic perceptual-motor skill.

Feedback about error or reward is regarded essential for aiding learners to acquire a perceptual-motor skill. Yet, when a task has redundancy and the mapping between execution and performance outcome is unknown, simple error feedback does not suffice in guiding the learner toward the optimal solutions. The present study developed and tested a new means of implicitly guiding learners to acquire a perceptual-motor skill, rhythmically bouncing a ball on a racket. Due to its rhythmic nature, this task affords dynamically stable solutions that are robust to small errors and noise, a strategy that is independent from actively correcting error. Based on the task model implemented in a virtual environment, a time-shift manipulation was designed to shift the range of ball-racket contacts that achieved dynamically stable solutions. In two experiments, subjects practiced with this manipulation that guided them to impact the ball with more negative racket accelerations, the indicator for the strategy with dynamic stability. Subjects who practiced under normal conditions took longer time to acquire this strategy, although error measures were identical between the control and experimental groups. Unlike in many other haptic guidance or adaptation studies, the experimental groups not only learned, but also maintained the stable solution after the manipulation was removed. These results are a first demonstration that more subtle ways to guide the learner to better performance are needed especially in tasks with redundancy, where error feedback may not be sufficient.