Lower-limb amputees can reduce the energy cost of walking when assisted by an Active Pelvis Orthosis

Exoskeletons could compete with active prostheses as effective aids to reduce the increased metabolic demands faced by lower-limb amputees during locomotion. However, little evidence of their efficacy with amputees has been provided so far. In this paper, a portable hip exoskeleton has been tested with seven healthy subjects and two transfemoral amputees, with the final goal to verify whether a hip flexion-extension assistance could be effective in reducing the metabolic cost of walking. The metabolic power of the participants was estimated through indirect calorimetry during alternated repetitions of three treadmill-based walking conditions: without the exoskeleton (NoExo), with the exoskeleton in zero-torque mode (ExoTM) and with the exoskeleton providing hip flexion-extension assistance (ExoAM). The results showed that the exoskeleton reduced the net metabolic power of the two amputees in ExoAM with respect to NoExo, by 5.0% and 3.4%. With healthy subjects, a 5.5±3.1% average reduction in the metabolic power was observed during ExoAM compared to ExoTM (differences were not statistically significant), whereas ExoAM required 3.9±3.0% higher metabolic power than NoExo (differences were not statistically significant). These results provide initial evidence of the potential of exoskeletal technologies for assisting lower-limb amputees, thereby paving the way for further experimentations

Reducing the metabolic cost of walking with an ankle exoskeleton: interaction between actuation timing and power

Background Powered ankle-foot exoskeletons can reduce the metabolic cost of human walking to below normal levels, but optimal assistance properties remain unclear. The purpose of this study was to test the effects of different assistance timing and power characteristics in an experiment with a tethered ankle-foot exoskeleton. Methods Ten healthy female subjects walked on a treadmill with bilateral ankle-foot exoskeletons in 10 different assistance conditions. Artificial pneumatic muscles assisted plantarflexion during ankle push-off using one of four actuation onset timings (36, 42, 48 and 54% of the stride) and three power levels (average positive exoskeleton power over a stride, summed for both legs, of 0.2, 0.4 and 0.5 W∙kg−1). We compared metabolic rate, kinematics and electromyography (EMG) between conditions. Results Optimal assistance was achieved with an onset of 42% stride and average power of 0.4 W∙kg−1, leading to 21% reduction in metabolic cost compared to walking with the exoskeleton deactivated and 12% reduction compared to normal walking without the exoskeleton. With suboptimal timing or power, the exoskeleton still reduced metabolic cost, but substantially less so. The relationship between timing, power and metabolic rate was well-characterized by a two-dimensional quadratic function. The assistive mechanisms leading to these improvements included reducing muscular activity in the ankle plantarflexors and assisting leg swing initiation. Conclusions These results emphasize the importance of optimizing exoskeleton actuation properties when assisting or augmenting human locomotion. Our optimal assistance onset timing and average power levels could be used for other exoskeletons to improve assistance and resulting benefits

A Biomechanical Comparison of Proportional Electromyography Control to Biological Torque Control Using a Powered Hip Exoskeleton

BackgroundDespite a large increase in robotic exoskeleton research, there are few studies that have examined human performance with different control strategies on the same exoskeleton device. Direct comparison studies are needed to determine how users respond to different types of control. The purpose of this study was to compare user performance using a robotic hip exoskeleton with two different controllers: a controller that targeted a biological hip torque profile and a proportional myoelectric controller.MethodsWe tested both control approaches on 10 able-bodied subjects using a pneumatically powered hip exoskeleton. The state machine controller targeted a biological hip torque profile. The myoelectric controller used electromyography (EMG) of lower limb muscles to produce a proportional control signal for the hip exoskeleton. Each subject performed two 30-min exoskeleton walking trials (1.0 m/s) using each controller and a 10-min trial with the exoskeleton unpowered. During each trial, we measured subjects’ metabolic cost of walking, lower limb EMG profiles, and joint kinematics and kinetics (torques and powers) using a force treadmill and motion capture.ResultsCompared to unassisted walking in the exoskeleton, myoelectric control significantly reduced metabolic cost by 13% (p = 0.005) and biological hip torque control reduced metabolic cost by 7% (p = 0.261). Subjects reduced muscle activity relative to the unpowered condition for a greater number of lower limb muscles using myoelectric control compared to the biological hip torque control. More subjects subjectively preferred the myoelectric controller to the biological hip torque control.ConclusionMyoelectric control had more advantages (metabolic cost and muscle activity reduction) compared to a controller that targeted a biological torque profile for walking with a robotic hip exoskeleton. However, these results were obtained with a single exoskeleton device with specific control configurations while level walking at a single speed. Further testing on different exoskeleton hardware and with more varied experimental protocols, such as testing over multiple types of terrain, is needed to fully elucidate the potential benefits of myoelectric control for exoskeleton technology

Adaptive Controllers for Assistive Robotic Devices

Lower extremity assistive robotic devices, such as exoskeletons and prostheses, have the potential to improve mobility for millions of individuals, both healthy and disabled. These devices are designed to work in conjunction with the user to enhance or replace lost functionality of a limb. Given the large variability in walking dynamics from person to person, it is still an open research question of how to optimally control such devices to maximize their benefit for each individual user. In this context, it is becoming more and more evident that there exists no "one size fits all" solution, but that each device needs to be tuned on a subject-specific basis to best account for each user's unique gait characteristics. However, the controllers that run in the background of these devices to dictate when and what type of actuation to deliver often have up to a hundred different parameters that can be tuned on a subject-specific basis. To hand tune each parameter can be an extremely tedious and time consuming process. Additionally, current tuning practices often rely on subjective measures to inform the fitting process. To address the current obstacles associated with device control and tuning, I have developed novel tools that overcome some of these issues through the design of control architectures that autonomously adapt to the user based upon real-time physiological measures. This approach frames the tuning process of a device as a real-time optimization and allows for the device to co-adapt with the wearer during use. As an outcome of these approaches, I have been able to investigate what qualities of a device controller are beneficial to users through the analysis of whole body kinematics, dynamics, and energetics. The framework of my research has been broken down into four major projects. First, I investigated how current standards of processing and analyzing physiological measures could be improved upon. Specifically, I focused on how to analyze non-steady-state measures of metabolic work rate in real time and how the noise content of theses measures can inform confidence analyses. Second, I applied the techniques I developed for analyzing non-steady-state measures of metabolic work rate to conduct a real-time optimization of powered bilateral ankle exoskeletons. For this study I employed a gradient descent optimization to tune and optimize an actuation timing parameter of these simple exoskeletons on a subject-specific basis. Third, I investigated how users may use an adaptive controller where they had a more direct impact on the adaptation via their own muscle recruitment. In this study, I designed and tested an adaptive gain proportional myoelectric controller with healthy subjects walking in bilateral ankle exoskeletons. Through this work I showed that subjects adapted to using increased levels of total ankle power compared to unpowered walking in the devices. As a result, subjects decreased power at their hip and were able to achieve large decreases in their metabolic work rate compared to unpowered walking. Fourth, I compared how subjects may use a controller driven by neural signals differently than one driven by mechanically intrinsic signals. The results of this project suggest that control based on neural signals may be better suited for therapeutic rehabilitation than control based on mechanically intrinsic signals. Together, these four projects have drastically improved upon subject-specific control of assistive devices in both a research and clinical setting.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144029/1/jrkoller_1.pd