Reliability and minimal detectable change of stiffness and other mechanical properties of the ankle joint in standing and walking.

BACKGROUND: Ankle joint stiffness and viscosity are fundamental mechanical descriptions that govern the movement of the body and impact an individual's walking ability. Hence, these internal properties of a joint have been increasingly used to evaluate the effects of pathology (e.g., stroke) and in the design and control of robotic and prosthetic devices. However, the reliability of these measurements is currently unclear, which is important for translation to clinical use. RESEARCH QUESTION: Can we reliably measure the mechanical impedance parameters of the ankle while standing and walking? METHODS: Eighteen able-bodied individuals volunteered to be tested on two different days separated by at least 24 h. Participants received several small random ankle dorsiflexion perturbations while standing and during the stance phase of walking using a custom-designed robotic platform. Three-dimensional motion capture cameras and a 6-component force plate were used to quantify ankle joint motions and torque responses during normal and perturbed conditions. Ankle mechanical impedance was quantified by computing participant-specific ensemble averages of changes in ankle angle and torque due to perturbation and fitting a second-order parametric model consisting of stiffness, viscosity, and inertia. The test-retest reliability of each parameter was assessed using intraclass correlation coefficients (ICCs). We also computed the minimal detectable change (MDC) for each impedance parameter to establish the smallest amount of change that falls outside the measurement error of the instrument. RESULTS: In standing, the reliability of stiffness, viscosity, and inertia was good to excellent (ICCs=0.67-0.91). During walking, the reliability of stiffness and viscosity was good to excellent (ICCs=0.74-0.84) while that of inertia was fair to good (ICCs=0.47-0.68). The MDC for a single subject ranged from 20%- 65% of the measurement mean but was higher (>100%) for inertia during walking. SIGNIFICANCE: Results indicate that dynamic measures of ankle joint impedance were generally reliable and could serve as an adjunct clinical tool for evaluating gait impairments.

Design of a Quasi-Passive Ankle-Foot Orthosis with Customizable, Variable Stiffness.

Most commercial ankle-foot orthoses (AFOs) are passive structures that cannot modulate stiffness to assist with a diverse range of activities, such as stairs and ramps. It is sometimes possible to change the stiffness of passive AFOs through reassembly or benchtop adjustment, but they cannot change stiffness during use. Passive AFOs are also limited in their ankle mechanics and cannot replicate a biomimetic, nonlinear torque-angle relationship. Many research labs have developed ankle exoskeletons that show promise as viable alternatives to passive AFOs, but they face challenges with reliability, mass, and cost. Consequently, commercial translation has largely failed to date. Here we introduce the Variable Stiffness Orthosis (VSO), a quasi-passive variable stiffness ankle-foot orthosis that strikes a balance between powered and passive systems, in terms of mass, complexity, and onboard intelligence. The VSO has customizable torque-angle relationships via a cam transmission, and can make step-to-step stiffness adjustments via motorized reconfiguration of a spring support along a lead-screw. In this work, we introduce two versions: a nominal and a stiff prototype, which differ primarily in their mass and available stiffness levels. The available torque-angle relationships are measured on a custom dynamometer and closely match model predictions. The experimental results showed that the prototypes are capable of producing ankle stiffness coefficients between 9 - 330 Nm/rad.

User preference optimization for control of ankle exoskeletons using sample efficient active learning.

One challenge to achieving widespread success of augmentative exoskeletons is accurately adjusting the controller to provide cooperative assistance with their wearer. Often, the controller parameters are "tuned" to optimize a physiological or biomechanical objective. However, these approaches are resource intensive, while typically only enabling optimization of a single objective. In reality, the exoskeleton user experience is likely derived from many factors, including comfort, fatigue, and stability, among others. This work introduces an approach to conveniently tune the four parameters of an exoskeleton controller to maximize user preference. Our overarching strategy is to leverage the wearer to internally balance the experiential factors of wearing the system. We used an evolutionary algorithm to recommend potential parameters, which were ranked by a neural network that was pretrained with previously collected user preference data. The controller parameters that had the highest preference ranking were provided to the exoskeleton, and the wearer responded with real-time feedback as a forced-choice comparison. Our approach was able to converge on controller parameters preferred by the wearer with an accuracy of 88% on average when compared with randomly generated parameters. User-preferred settings stabilized in 43 ± 7 queries. This work demonstrates that user preference can be leveraged to tune a partial-assist ankle exoskeleton in real time using a simple, intuitive interface, highlighting the potential for translating lower-limb wearable technologies into our daily lives.

Real-Time Gait Phase and Task Estimation for Controlling a Powered Ankle Exoskeleton on Extremely Uneven Terrain.

Positive biomechanical outcomes have been reported with lower-limb exoskeletons in laboratory settings, but these devices have difficulty delivering appropriate assistance in synchrony with human gait as the task or rate of phase progression change in real-world environments. This paper presents a controller for an ankle exoskeleton that uses a data-driven kinematic model to continuously estimate the phase, phase rate, stride length, and ground incline states during locomotion, which enables the real-time adaptation of torque assistance to match human torques observed in a multi-activity database of 10 able-bodied subjects. We demonstrate in live experiments with a new cohort of 10 able-bodied participants that the controller yields phase estimates comparable to the state of the art, while also estimating task variables with similar accuracy to recent machine learning approaches. The implemented controller successfully adapts its assistance in response to changing phase and task variables, both during controlled treadmill trials (N=10, phase RMSE: 4.8 ± 2.4%) and a real-world stress test with extremely uneven terrain (N=1, phase RMSE: 4.8 ± 2.7%).

Data-Driven Variable Impedance Control of a Powered Knee-Ankle Prosthesis for Adaptive Speed and Incline Walking.

Most impedance-based walking controllers for powered knee-ankle prostheses use a finite state machine with dozens of user-specific parameters that require manual tuning by technical experts. These parameters are only appropriate near the task (e.g., walking speed and incline) at which they were tuned, necessitating many different parameter sets for variable-task walking. In contrast, this paper presents a data-driven, phase-based controller for variable-task walking that uses continuously-variable impedance control during stance and kinematic control during swing to enable biomimetic locomotion. After generating a data-driven model of variable joint impedance with convex optimization, we implement a novel task-invariant phase variable and real-time estimates of speed and incline to enable autonomous task adaptation. Experiments with above-knee amputee participants (N=2) show that our data-driven controller 1) features highly-linear phase estimates and accurate task estimates, 2) produces biomimetic kinematic and kinetic trends as task varies, leading to low errors relative to able-bodied references, and 3) produces biomimetic joint work and cadence trends as task varies. We show that the presented controller meets and often exceeds the performance of a benchmark finite state machine controller for our two participants, without requiring manual impedance tuning.

Designing Custom Mechanics in Running-Specific Prosthetic Feet via Shape Optimization.

OBJECTIVE: Running-specific prosthetic feet are curved cantilever springs, distinguished from ordinary prosthetic feet by their size, shape, and greater ability to store and return elastic potential energy. Finite element analyses show how modifications to prosthesis shape alter the multidimensional and nonlinear mechanics, but designers seeking to prescribe custom mechanics are limited by the complex constraints and high dimensionality of possible geometries. METHODS: We introduce two simple formulations for describing foot mechanics, and use them with a custom spline-based shape optimization to generate new prosthetic foot shapes given desired endpoint mechanics. We then tackle a relevant example problem using this approach, designing and characterizing three running-specific prosthetic feet with similar vertical and angular deflections but varied horizontal deflections, with the expectation that knee extension moments would increase with anterior deflection of the toe. Finally, we compare the prostheses' endpoint mechanics and resulting biomechanics in an athlete with unilateral transfemoral amputation. RESULTS: The shape optimization was able to derive shapes that substantially alter prosthesis mechanics along all dimensions of endpoint behavior, and benchtop testing validated the behavior of two new feet constructed from the optimization. The subject's knee moments increased with horizontal endpoint deflection as expected. CONCLUSION: We developed and validated a shape optimization tool using a simplified formulation of foot behavior to achieve desired running prosthesis mechanics. SIGNIFICANCE: With this framework, researchers can begin to elucidate the link between prosthesis mechanics and athlete biomechanics and performance.

Enhancing Voluntary Motion with Modular, Backdrivable, Powered Hip and Knee Orthoses.

Mobility disabilities are prominent in society with wide-ranging deficits, motivating modular, partial-assist, lower-limb exoskeletons for this heterogeneous population. This paper introduces the Modular Backdrivable Lower-limb Unloading Exoskeleton (M-BLUE), which implements high torque, low mechanical impedance actuators on commercial orthoses with sheet metal modifications to produce a variety of hip- and/or knee-assisting configurations. Benchtop system identification verifies the desirable backdrive properties of the actuator, and allows for torque prediction within ±0.4 Nm. An able-bodied human subject experiment demonstrates that three unilateral configurations of M-BLUE (hip only, knee only, and hip-knee) with a simple gravity compensation controller can reduce muscle EMG readings in a lifting and lowering task relative to the bare condition. Reductions in mean muscular effort and peak muscle activation were seen across the primary squat musculature (excluding biceps femoris), demonstrating the potential to reduce fatigue leading to poor lifting posture. These promising results motivate applications of M-BLUE to additional populations, and the expansion of M-BLUE to bilateral and ankle configurations.

Analysis of the Bayesian Gait-State Estimation Problem for Lower-Limb Wearable Robot Sensor Configurations.

Many exoskeletons today are primarily tested in controlled, steady-state laboratory conditions that are unrealistic representations of their real-world usage in which walking conditions (e.g., speed, slope, and stride length) change constantly. One potential solution is to detect these changing walking conditions online using Bayesian state estimation to deliver assistance that continuously adapts to the wearer's gait. This paper investigates such an approach in silico, aiming to understand 1) which of the various Bayesian filter assumptions best match the problem, and 2) which gait parameters can be feasibly estimated with different combinations of sensors available to different exoskeleton configurations (pelvis, thigh, shank, and/or foot). Our results suggest that the assumptions of the Extended Kalman Filter are well suited to accurately estimate phase, stride frequency, stride length, and ramp inclination with a wide variety of sparse sensor configurations.

Can humans perceive the metabolic benefit provided by augmentative exoskeletons?

BACKGROUND: The purpose of augmentative exoskeletons is to help people exceed the limitations of their human bodies, but this cannot be realized unless people choose to use these exciting technologies. Although human walking efficiency has been highly optimized over generations, exoskeletons have been able to consistently improve this efficiency by 10-15%. However, despite these measurable improvements, exoskeletons today remain confined to the laboratory. To achieve widespread adoption, exoskeletons must not only exceed the efficiency of human walking, but also provide a perceivable benefit to their wearers. METHODS: In this study, we quantify the perceptual threshold of the metabolic efficiency benefit provided during exoskeleton-assisted locomotion. Ten participants wore bilateral ankle exoskeletons during continuous walking. The assistance provided by the exoskeletons was varied in 2 min intervals while participants provided feedback on their metabolic rate. These data were aggregated and used to estimate the perceptual threshold. RESULTS: Participants were able to detect a change in their metabolic rate of 22.7% (SD: 17.0%) with 75% accuracy. This indicates that in the short term and on average, wearers cannot yet reliably perceive the metabolic benefits of today's augmentative exoskeletons. CONCLUSIONS: If wearers cannot perceive the benefits provided by these technologies, it will negatively affect their impact, including long-term adoption and product viability. Future exoskeleton researchers and designers can use these methods and results to inform the development of exoskeletons that reach their potential.

Validation of Methods for Estimation of Knee Joint Mechanical Impedance During Locomotion Using a Torque-Controllable Knee Exoskeleton.

The mechanical impedance of the joints of the leg governs the body's response to external disturbances, and its regulation is essential for the completion of tasks of daily life. However, it is still unclear how this quantity is regulated at the knee during dynamic tasks. In this work, we introduce a method to estimate the mechanical impedance of spring-mass systems using a torque-controllable exoskeleton with the intention of extending these methods to characterize the mechanical impedance of the human knee during locomotion. We characterize system bandwidth and intrinsic impedance and present a perturbation-based methodology to identify the mechanical impedance of known spring-mass systems. Our approach was able to obtain accurate estimates of stiffness and inertia, with errors under 3% and ∼13-16%, respectively. This work provides a qualitative and quantitative foundation that will enable accurate estimates of knee joint impedance during locomotion in future works.

How Does Ankle Mechanical Stiffness Change as a Function of Muscle Activation in Standing and During the Late Stance of Walking?

OBJECTIVE: Ankle joint stiffness is known to be modulated by co-contraction of the ankle muscles; however, it is unclear to what extent changes in agonist muscle activation alone affect ankle joint stiffness. This study tested the effects of varying levels of ankle muscle activation on ankle joint mechanical stiffness in standing and during the late stance phase of walking. METHODS: Dorsiflexion perturbations were applied at various levels of ankle muscle activation via a robotic platform in standing and walking conditions. In standing, muscle activation was modulated by having participants perform an EMG target matching task that required varying levels of plantarflexor activation. In walking, muscle activation was modulated by changing walking speeds through metronome-based auditory feedback. Ankle stiffness was evaluated by performing a Least-squares system identification using a parametric model consisting of stiffness, damping, and inertia. The association between ankle muscle activation and joint stiffness was evaluated using correlation analyses. Linear regression models were used to determine the extent to which muscle activation contributed to ankle stiffness. An inclusive statistical approach (both classical and Bayesian analyses) was adopted to measure the statistical significance (p-value) and Bayes Factor (BF10). RESULTS: Results indicate that plantarflexor activity was positively correlated with ankle stiffness in both standing and walking (p<0.001, BF10>900), whereas dorsiflexor activity was negatively correlated with ankle stiffness in walking (p = 0.014, BF10 = 3.9) but not in standing (p = 0.725). Regression analyses indicated that ankle muscle activation predicted about 84% of the variation in ankle stiffness in standing and 45% in walking (p<0.001, BF10>100). CONCLUSION: Ankle muscle activation significantly contributes to ankle stiffness during standing and walking. SIGNIFICANCE: The results highlight the role of muscle activation on maintaining joint stiffness and underscore the importance of accounting for muscle activation when measuring ankle stiffness in healthy as well as patient populations.

Characterization and clinical implications of ankle impedance during walking in chronic stroke.

Individuals post-stroke experience persisting gait deficits due to altered joint mechanics, known clinically as spasticity, hypertonia, and paresis. In engineering, these concepts are described as stiffness and damping, or collectively as joint mechanical impedance, when considered with limb inertia. Typical clinical assessments of these properties are obtained while the patient is at rest using qualitative measures, and the link between the assessments and functional outcomes and mobility is unclear. In this study we quantify ankle mechanical impedance dynamically during walking in individuals post-stroke and in age-speed matched control subjects, and examine the relationships between mechanical impedance and clinical measures of mobility and impairment. Perturbations were applied to the ankle joint during the stance phase of walking, and least-squares system identification techniques were used to estimate mechanical impedance. Stiffness of the paretic ankle was decreased during mid-stance when compared to the non-paretic side; a change independent of muscle activity. Inter-limb differences in ankle joint damping, but not joint stiffness or passive clinical assessments, strongly predicted walking speed and distance. This work provides the first insights into how stroke alters joint mechanical impedance during walking, as well as how these changes relate to existing outcome measures. Our results inform clinical care, suggesting a focus on correcting stance phase mechanics could potentially improve mobility of chronic stroke survivors.

Understanding patient preference in prosthetic ankle stiffness.

BACKGROUND: User preference has the potential to facilitate the design, control, and prescription of prostheses, but we do not yet understand which physiological factors drive preference, or if preference is associated with clinical benefits. METHODS: Subjects with unilateral below-knee amputation walked on a custom variable-stiffness prosthetic ankle and manipulated a dial to determine their preferred prosthetic ankle stiffness at three walking speeds. We evaluated anthropomorphic, metabolic, biomechanical, and performance-based descriptors at stiffness levels surrounding each subject's preferred stiffness. RESULTS: Subjects preferred lower stiffness values at their self-selected treadmill walking speed, and elected to walk faster overground with ankle stiffness at or above their preferred stiffness. Preferred stiffness maximized the kinematic symmetry between prosthetic and unaffected joints, but was not significantly correlated with body mass or metabolic rate. CONCLUSION: These results imply that some physiological factors are weighted more heavily when determining preferred stiffness, and that preference may be associated with clinically relevant improvements in gait.

Phase-Variable Control of a Powered Knee-Ankle Prosthesis over Continuously Varying Speeds and Inclines.

Most controllers for lower-limb robotic prostheses require individually tuned parameter sets for every combination of speed and incline that the device is designed for. Because ambulation occurs over a continuum of speeds and inclines, this design paradigm requires tuning of a potentially prohibitively large number of parameters. This limitation motivates an alternative control framework that enables walking over a range of speeds and inclines while requiring only a limited number of tunable parameters. In this work, we present the implementation of a continuously varying kinematic controller on a custom powered knee-ankle prosthesis. The controller uses a phase variable derived from the residual thigh angle, along with real-time estimates of ground inclination and walking speed, to compute the appropriate knee and ankle joint angles from a continuous model of able-bodied kinematic data. We modify an existing phase variable architecture to allow for changes in speeds and inclines, quantify the closed-loop accuracy of the speed and incline estimation algorithms for various references, and experimentally validate the controller by observing that it replicates kinematic trends seen in able-bodied gait as speed and incline vary.

A passive mechanism for decoupling energy storage and return in ankle-foot prostheses: A case study in recycling collision energy.

Individuals with lower limb amputation experience reduced ankle push-off work in the absence of functional muscles spanning the joint, leading to decreased walking performance. Conventional energy storage and return (ESR) prostheses partially compensate by storing mechanical energy during midstance and returning this energy during the terminal stance phase of gait. These prostheses can provide approximately 30% of the push-off work performed by a healthy ankle-foot during walking. Novel prostheses that return more normative levels of mechanical energy may improve walking performance. In this work, we designed a Decoupled ESR (DESR) prosthesis which stores energy usually dissipated at heel-strike and loading response, and returns this energy during terminal stance, thus increasing the mechanical push-off work done by the prosthesis. This decoupling is achieved by switching between two different cam profiles that produce distinct, nonlinear torque-angle mechanics. The cams automatically interchange at key points in the gait cycle via a custom magnetic switching system. Benchtop characterization demonstrated the successful decoupling of energy storage and return. The DESR mechanism was able to capture energy at heel-strike and loading response, and return it later in the gait cycle, but this recycling was not sufficient to overcome mechanical losses. In addition to its potential for recycling energy, the DESR mechanism also enables unique mechanical customizability, such as dorsiflexion during swing phase for toe clearance, or increasing the rate of energy release at push-off.

Comparing preference of ankle-foot stiffness in below-knee amputees and prosthetists.

When fitting prosthetic feet, prosthetists fuse information from their visual assessment of patient gait with the patient's communicated perceptions and preferences. In this study, we sought to simultaneously and independently assess patient and prosthetist preference for prosthetic foot stiffness using a custom variable-stiffness prosthesis. In the first part of the experiment, seven subjects with below-knee amputation walked on the variable-stiffness prosthetic foot set to a randomized stiffness, while several prosthetist subjects simultaneously observed their gait. After each trial, the amputee subjects and prosthetist subjects indicated the change to stiffness that they would prefer (increase or decrease). This paradigm allowed us to simultaneously measure amputee subject and prosthetist subject preferences, and provided a reliability index indicating the consistency of their preferences. In the second part of the experiment, amputee subjects were instructed to communicate verbally with one prosthetist subject to arrive at a mutually preferred stiffness. On average, prosthetist subjects preferred a 26% higher stiffness than amputee subjects (p < 0.001), though this depended on the amputee subject (p < 0.001). Prosthetist subjects were also considerably less consistent than amputee subjects in their preferences (CV of 5.6% for amputee subjects, CV of 23% for prosthetist subjects; p = 0.014). Mutual preference seemed to be dictated by the specific patient-prosthetist dynamic, and no clear trends emerged.

Design and clinical implementation of an open-source bionic leg.

In individuals with lower-limb amputations, robotic prostheses can increase walking speed, and reduce energy use, the incidence of falls and the development of secondary complications. However, safe and reliable prosthetic-limb control strategies for robust ambulation in real-world settings remain out of reach, partly because control strategies have been tested with different robotic hardware in constrained laboratory settings. Here, we report the design and clinical implementation of an integrated robotic knee-ankle prosthesis that facilitates the real-world testing of its biomechanics and control strategies. The bionic leg is open source, it includes software for low-level control and for communication with control systems, and its hardware design is customizable, enabling reduction in its mass and cost, improvement in its ease of use and independent operation of the knee and ankle joints. We characterized the electromechanical and thermal performance of the bionic leg in benchtop testing, as well as its kinematics and kinetics in three individuals during walking on level ground, ramps and stairs. The open-source integrated-hardware solution and benchmark data that we provide should help with research and clinical testing of knee-ankle prostheses in real-world environments.

Mapping the relationships between joint stiffness, modeled muscle stiffness, and shear wave velocity.

Joint stiffness is often measured to make inferences about the stiffness of muscle groups, but little can be gleaned about individual muscles. Decomposing the muscular origins of joint stiffness may inform treatment targets for conditions like spasticity. To complement joint stiffness, shear wave ultrasound elastography has been used to estimate the material properties of individual muscles. If shear wave measures are to be used to assess the muscular origins of joint stiffness, then changes in shear wave velocity should strongly relate to changes in joint stiffness. Here, we estimated the relationships between shear wave velocity in the primary plantar flexors [soleus (SOL) and medial gastrocnemius (MG)] and ankle joint stiffness. Participants performed isometric plantar flexion tasks at a range of activations (0-40%), while joint stiffness and muscle shear wave velocities were obtained. We observed a strong, linear relationship between plantar flexor shear wave velocities and joint stiffness. Remarkably, the parameter estimates of this stiffness-shear wave relationship strongly agreed with theoretical and literature-based estimates [SOL:MG parameter ratios = 2.83 (observed) vs. 2.85 (expected from theoretical stiffness ratio)]. Finally, a musculoskeletal model of the plantar flexors was able to accurately reproduce joint stiffness estimates, and shear wave velocities could explain 80-95% of the variance in modeled muscle stiffness. These findings suggest that shear wave velocity may be used to infer the muscular origins of changes in joint stiffness.NEW & NOTEWORTHY Shear wave velocity is commonly assessed to infer the muscular origins of changes in joint stiffness, but the exact relationship between shear wave velocity changes in muscle and joint stiffness changes remains unknown. Here, we systematically evaluated and quantified this relationship in the plantar flexors. Our results provide evidence for the ability of shear wave velocity to elucidate the muscular origins of joint stiffness changes.

Neuromotor Regulation of Ankle Stiffness is Comparable to Regulation of Joint Position and Torque at Moderate Levels.

Joint mechanical impedance, which describes the instantaneous relationship between kinematic perturbations and the resulting torque response, plays an important role in the way humans ambulate, interact with the environment, and respond to disturbances. Recent studies have quantified how the stiffness component of mechanical impedance varies during walking. However, the extent to which humans can voluntarily regulate leg joint stiffness is not yet known. Our study sought to quantify the accuracy and precision of the neuromotor system to voluntarily regulate ankle joint stiffness while seated, and compare these data to the well-known abilities to regulate ankle joint torque and position. We tested individuals' ability to to regulate these quantities at three different magnitudes: 20%, 40%, and 60% of a maximum value. Our results showed that subjects were able to voluntarily regulate ankle joint stiffness, and that the normalized accuracy and precision of stiffness regulation were not different than those of position or torque for targets at magnitudes of 20% of a maximum value. However, the accuracy and precision of stiffness regulation were statistically different than those of position and torque for targets at magnitudes of 40% of the maximum values. At moderate targets, the similarity of the ability to regulate ankle joint stiffness when compared to the abilities to regulate joint torque and position highlights the importance of a comprehensive description of lower-limb biomechanics that includes consideration of joint mechanical impedance, in addition to the common descriptions of joint torque and position.

Ankle Mechanical Impedance During the Stance Phase of Running.

OBJECTIVE: Differences in locomotor biomechanics between walking and running provide fundamental information about human ambulation. Joint mechanical impedance is a biomechanical property that governs the body's instantaneous response to disturbances, and is important for stability and energy transfer. Ankle impedance has been characterized during walking, but little is known about how humans alter joint impedance during running. The purpose of this study was to estimate ankle impedance during the stance phase of running, and compare to previously reported estimates during walking. METHODS: Perturbations were applied to the ankle using a one-degree-of-freedom (DOF) mechatronic platform. Least-squares system identification was performed using a parametric model consisting of stiffness, damping, and inertia. RESULTS: The model accounted for 89% ± 16% of variance. Ankle stiffness reached a maximum of 10 Nm/rad/kg at the end of mid-stance, decreasing in terminal stance phase to values previously reported during swing phase. Quasi-stiffness values differed significantly from stiffness across the stance phase of running. Comparing ankle impedance estimates between walking and running showed differences in both magnitude, and temporal variation. CONCLUSION: Ankle impedance differs significantly between walking and running. SIGNIFICANCE: This study provides novel information about the biomechanics of running and broadens our understanding of how the mechanical impedance of the ankle joint differs between locomotor tasks, motivating the need for future studies.