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% (r = 0.71), while late-stance peak contact force increased by 1.6%, 0.9% and 3.0% (r = 0.67), 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.

Optimized assistance patterns have produced the greatest exoskeleton benefits to energy expenditure of any strategy to date. This strategy may be effective due to the customization of the applied torque profiles to the user as well as the locomotion condition; however, it is currently unclear how sensitive participants are to their unique torque profile. To investigate, we applied previously optimized hip-knee-ankle torque profiles to expert users (N=3; 1.25 m/s; 0 deg incline). The participants walked with the profile optimized to them, the two profiles optimized to the other two participants, and the average of the three torque profiles while we measured their energy expenditure. Relative to walking with the device turned off, on average, participants experienced a 47.5% (range 12%) metabolic reduction when walking with the torque profile optimized to them and a 46% (range 15%) reduction when walking with the other profiles. Interestingly, within-subject performance was more consistent than across subjects (P1: 52% range 5%, P2: 49% range 6%, P3: 39% range 3%) suggesting that, for expert users of some devices, there may be a range of nearly equally effective torque profiles to reduce the metabolic cost of walking. The torque timing was remarkably similar across the four torque profiles while the torque magnitude varied; participants may be much more sensitive to torque timing than torque magnitude, and there may be a set of torque timing parameters that are generally effective.

Falls are the leading cause of fatal and non-fatal injuries, particularly for older persons. Imbalance can result from the body's internal causes (illness), or external causes (active or passive perturbation). Active perturbation results from applying an external force to a person, while passive perturbation results from human motion interacting with a static obstacle. This work proposes a metric that allows for the monitoring of the persons torso and its correlation to active and passive perturbations. We show that large changes in the torso sway can be strongly correlated to active perturbations. We also show that we can reasonably predict the future path and expected change in torso sway by conditioning the expected path and torso sway on the past trajectory, torso motion, and the surrounding scene. This could have direct future applications to fall prevention. Results demonstrate that the torso sway is strongly correlated with perturbations. And our model is able to make use of the visual cues presented in the panorama and condition the prediction accordingly.

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 smaller 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.

Actuator power consumption is a limiting factor in mobile robot design. In this paper we introduce the concept of an energy-recycling actuator, which uses an array of springs and clutches to capture and return elastic energy in parallel with an electric motor. Engaging and disengaging clutches appropriately could reduce electrical energy consumption without sacrificing controllability, but presents a challenging control problem. We formulated the optimal control objective of minimizing actuator power consumption as a mixed-integer quadratic program (MIQP) and solved for the global minimum. For a given actuator design and a wide range of simulated torque and rotation patterns, all corresponding to zero net work over one cycle, we compared optimized actuator energy consumption to that of an optimized gear motor with simple parallel elasticity. The simulated energy-recycling actuator consumed less electrical energy: 57% less on average and 80% less in the best case. These results demonstrate an effective approach to optimal control of this type of system, and suggest that energy-recycling actuators could substantially reduce power consumption in some robotics applications.

Fall-related injury is a significant health problem on a global scale and is expected to grow with the aging population. Laboratory-based perturbation systems have the capability of simulating various modes of fall-inducing perturbations in a repeatable way. These systems enable fundamental research on human gait and balance and facilitate the development of devices to assist human balance. We present a robotic, rope-driven system capable of rendering bumps and force-fields at a person's pelvis in any direction in the transverse plane with forces up to 200 N, and a 90% rise time of as little as 44 ms, which is faster than a human's ability to sense and respond to the force. These capabilities enable experiments that require stabilizing or destabilizing subjects as they stand or walk on a treadmill. To facilitate use by researchers from all backgrounds, we designed both a configuration with simpler open-loop force control, and another with higher-performance, closed-loop force control. Both configurations are modular, and the open-loop system is made entirely from 3D-printed and catalog components. The design files and assembly instructions for both are freely available in an online repository.

Ankle inversion-eversion compliance is an important feature of conventional prosthetic feet, and control of inversion, or roll, in active prostheses could improve balance for people with amputation. We designed a tethered ankle-foot prosthesis with two independently actuated toes that are coordinated to provide plantarflexion and inversion-eversion torques. A Bowden cable tether provides series elasticity. The prosthesis is simple and lightweight, with a mass of 0.72kg. Strain gauges on the toes measure torque with less than 1% root mean squared (RMS) error. Benchtop tests demonstrated a step response rise time of less than 33 ms, peak torques of 250 N·m in plantarflexion and ±30 N·m in inversion-eversion, and peak power above 3 kW. The phase-limited closed-loop torque bandwidth is 20 Hz with a chirp from 10 to 90 N·m in plantarflexion, and 24 Hz with a chirp from -20 to 20 N·m in inversion. The system has low sensitivity to toe position disturbances at frequencies of up to 18 Hz. Walking trials with an amputee subject demonstrated RMS torque tracking errors of less than 5.1 N·m in plantarflexion and less than 1.5 N·m in inversion-eversion. These properties make the platform suitable for testing inversion-related prosthesis features and controllers in experiments with humans.

Individuals with lower limb amputation have a high fall risk, which could be partially due to a lack of stabilizing control in conventional prostheses. Inspired by walking robots, we hypothesized that modulating prosthetic ankle push-off could help improve amputee balance. We developed a three-dimensional walking model, found limit cycles at two speeds, and designed state-feedback controllers that made once-per-step adjustments to ankle push-off work, fore-aft and medial-lateral foot placement, and ankle roll resistance. To assess balance, we applied increasing levels of random changes in ground height and lateral impulses until the model fell down within 100 steps. Although foot placement is known to be important for balance, we found that push-off control was at least twice as effective at recovering from both disturbances at both speeds. Push-off work affected both fore-aft and mediolateral motions, leading to good controllability, and was particularly well suited to recovery from steps up or down. Our results suggest that discrete control of ankle push-off may be more important than previously thought, and may guide the design of robotic prostheses that improve balance.

Clutches can be used to enhance the functionality of springs or actuators in robotic devices. Here we describe a lightweight, low-power clutch used to control spring engagement in an ankle exoskeleton. The clutch is based on electrostatic adhesion between thin electrode sheets coated with a dielectric material. Each electrode pair weighs 1.5 g, bears up to 100 N, and changes states in less than 30 ms. We placed clutches in series with elastomer springs to allow control of spring engagement, and placed several clutched springs in parallel to discretely adjust stiffness. By engaging different numbers of springs, the system produced six different levels of stiffness. Force at peak displacement ranged from 14 to 501 N, and the device returned 95% of stored mechanical energy. Each clutched spring element weighed 26 g. We attached one clutched spring to an ankle exoskeleton and used it to engage the spring only while the foot was on the ground during 150 consecutive walking steps. Peak torque was 7.3 N·m on an average step, and the device consumed 0.6 mW of electricity. Compared to other electrically-controllable clutches, this approach results in three times higher torque density and two orders of magnitude lower power consumption per unit torque. We anticipate this technology will be incorporated into exoskeletons that tune stiffness online and into new actuator designs that utilize many lightweight, low-power clutches acting in concert.

Robotic prostheses can improve walking performance for amputees, but prescription of these devices has been hindered by their high cost and uncertainty about the degree to which individuals will benefit. The typical prescription process cannot well predict how an individual will respond to a device they have never used because it bases decisions on subjective assessment of an individual's current activity level. We propose a new approach in which individuals `test drive' candidate devices using a prosthesis emulator while their walking performance is quantitatively assessed and results are distilled to inform prescription. In this system, prosthesis behavior is controlled by software rather than mechanical implementation, so users can quickly experience a broad range of devices. To test the viability of the approach, we developed a prototype emulator and assessment protocol, leveraging hardware and methods we previously developed for basic science experiments. We demonstrated emulations across the spectrum of commercially available prostheses, including traditional (e.g. SACH), dynamic-elastic (e.g. FlexFoot), and powered robotic (e.g. BiOM®T2) prostheses. Emulations exhibited low error with respect to reference data and provided subjectively convincing representations of each device. We demonstrated an assessment protocol that differentiated device classes for each individual based on quantitative performance metrics, providing feedback that could be used to make objective, personalized device prescriptions.

Ankle inversion-eversion compliance is an important feature of conventional prosthetic feet, and control of inversion, or roll, in robotic prostheses could improve balance for people with amputation. We designed a tethered ankle-foot prosthesis with two independently-actuated toes that are coordinated to provide plantarflexion and inversion-eversion torques. This configuration allows a simple lightweight structure with a total mass of 0.72 kg. Strain gages on the toes measure torque with less than 2.7% RMS error, while compliance in the Bowden cable tether provides series elasticity. Benchtop tests demonstrated a 90% rise time of less than 33 ms and peak torques of 180 N·m in plantarflexion and ±30 N·m in inversion-eversion. The phase-limited closedloop torque bandwidth is 20 Hz with a 90 N·m amplitude chirp in plantarflexion, and 24 Hz with a 20 N·m amplitude chirp in inversion-eversion. The system has low sensitivity to toe position disturbances at frequencies of up to 18 Hz. Walking trials with five values of constant inversion-eversion torque demonstrated RMS torque tracking errors of less than 3.7% in plantarflexion and less than 5.9% in inversion-eversion. These properties make the platform suitable for haptic rendering of virtual devices in experiments with humans, which may reveal strategies for improving balance or allow controlled comparisons of conventional prosthesis features. A similar morphology may be effective for autonomous devices.

Lower-limb exoskeletons capable of comfortably applying high torques at high bandwidth can be used to probe the human neuromuscular system and assist gait. We designed and built two tethered ankle exoskeletons with strong lightweight frames, comfortable three-point contact with the leg, and series elastic elements for improved torque control. Both devices have low mass (< 0.88 kg), are modular, structurally compliant in selected directions, and instrumented to measure joint angle and torque. The exoskeletons are actuated by an off-board motor, and torque is controlled using a combination of proportional feedback and damping injection with iterative learning during walking tests. We tested closed-loop torque control by commanding 50 N·m and 20 N·m linear chirps in desired torque while the exoskeletons were worn by human users, and measured bandwidths greater than 16 Hz and 21 Hz, respectively. During walking trials, we demonstrated 120 N·m peak torque and 2.0 N·m RMS torque tracking error. These performance measures compare favorably with existing devices and with human ankle musculature, and show that these exoskeletons can be used to rapidly explore a wide range of control techniques and robotic assistance paradigms as elements of versatile, high-performance testbeds. Our results also provide insights into desirable properties of lower-limb exoskeleton hardware, which we expect to inform future designs.

Few comparisons have been performed across torque controllers for exoskeletons, and differences among devices have made interpretation difficult. In this study, we designed, developed and compared the torque-tracking performance of nine control methods, including variations on classical feedback control, model-based control, adaptive control and iterative learning. Each was tested with four high-level controllers that determined desired torque based on time, joint angle, a neuromuscular model, or electromyography. Controllers were implemented on a tethered ankle exoskeleton with series elastic actuation. Measurements were taken while one human subject walked on a treadmill at 1.25 m·s−1for one hundred steady-state steps. The combination of proportional control with damping injection and iterative learning resulted in the lowest errors for all high-level controllers. With time-based desired torque, root-mean-squared errors were 0.6 N·m (1.3% of peak desired torque) step by step, and 0.1 N·m (0.2%) on average. These results indicate that model-free, integration-free feedback control is suited to the uncertain dynamics of the human-robot system, while iterative learning is effective in the cyclic task of walking.

Biomechatronic devices show promise for restoring human performance, but development has been made inefficient by the need for specialized autonomous devices prior to testing benefits of proposed functionalities. This has severely limited exploration within and across intervention strategies. We have developed a laboratory testbed suitable for emulating and rapidly assessing wearable robot designs. The testbed is comprised of powerful off-board motor and control hardware, a flexible tether, and lightweight instrumented end-effectors worn by a person. We performed a series of benchtop tests to gauge mechatronic performance, and found significant improvements over prior candidate testbed platforms. In particular, this system has an unusual combination of low worn mass (less than 1 kg), high closed-loop torque bandwidth (17 Hz), and high peak torque (175 N·m), key to emulating specialized devices. We also performed walking trials to gauge dynamic torque control and versatility. Walking trials with a prosthesis end-effector demonstrated precise torque tracking (4 N·m RMS error), both in time and joint-angle space, and versatile mechanical behavior through systematic changes in high-level control law parameters. For example, we widely varied net ankle work (from -3 J to 9 J per step) using an impedance law relating joint angle and velocity to desired torque. These results suggest such testbeds could be used to emulate and evaluate novel assistive robot concepts prior to laborious product design.

Research on rehabilitation robotics has been rising as a substitute to human practice to help neuro-damaged patients to restore impaired or lost functionalities. Most control methods for rehabilitative robotics do not consider the closed-loop system stability in presence of uncertainty of nonlinear dynamics, and conflicting movements between patient and robots. In this paper, we present a theoretical framework which allows rigorous stability analysis of human-robot interaction in rehabilitative robotic system. Position-dependant stiffness and desired trajectory are proposed to resolve the possible conflicts in motions between patient and robot. The proposed method also realizes the assist-as-needed policy and possesses the ability to be customized for operations during different stages of patient recovery. In addition, the proposed controller handles human-robot interactions in such a way that correct movements are encouraged and incorrect ones are suppressed to make the training process more effective. Experimental results are presented to illustrate the performance of the controller.

Here we present the design of a passive-dynamics based, fully autonomous, 3-D, bipedal walking robot that uses simple control, consumes little energy, and has human-like morphology and gait. Design aspects covered here include the freely rotating hip joint with angle bisecting mechanism; freely rotating knee joints with latches; direct actuation of the ankles with a spring, release mechanism, and reset motor; wide feet that are shaped to aid lateral stability; and the simple control algorithm. The biomechanics context of this robot is discussed in more detail in [1], and movies of the robot walking are available at Science Online and http://www.tam.cornell.edu/~ruina/powerwalk.html. This robot adds evidence to the idea that passive-dynamic approaches might help design walking robots that are simpler, more efficient and easier to control.

Exoskeletons that enhance human strength, endurance, and speed while being transparent to the wearer are feasible. In order to be transparent, the exoskeleton must determine the user's intent, apply forces when and where appropriate, and present low impedance to the wearer. We present a one degree of freedom exoskeleton called the RoboKnee which achieves a high level of transparency. User intent is determined through the knee joint angle and ground reaction forces. Torque is applied across the knee in order to allow the user's quadriceps muscles to relax. Low impedance is achieved through the use of series elastic actuators. The RoboKnee allows the wearer to climb stairs and perform deep knee bends while carrying a significant load in a backpack. The device provides most of the energy required to work against gravity while the user stays in control, deciding when and where to walk, as well as providing balance and control. Videos, photographs, and more information about the RoboKnee can be found at http://www.yobotics.com.