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Mechanics and energetics of post-stroke walking aided by a powered ankle exoskeleton with speed-adaptive myoelectric control.

ABSTRACT: BACKGROUND:Ankle exoskeletons offer a promising opportunity to offset mechanical deficits after stroke by applying the needed torque at the paretic ankle. Because joint torque is related to gait speed, it is important to consider the user's gait speed when determining the magnitude of assistive joint torque. We developed and tested a novel exoskeleton controller for delivering propulsive assistance which modulates exoskeleton torque magnitude based on both soleus muscle activity and walking speed. The purpose of this research is to assess the impact of the resulting exoskeleton assistance on post-stroke walking performance across a range of walking speeds. METHODS:Six participants with stroke walked with and without assistance applied to a powered ankle exoskeleton on the paretic limb. Walking speed started at 60% of their comfortable overground speed and was increased each minute (n00, n01, n02, etc.). We measured lower limb joint and limb powers, metabolic cost of transport, paretic and non-paretic limb propulsion, and trailing limb angle. RESULTS:Exoskeleton assistance increased with walking speed, verifying the speed-adaptive nature of the controller. Both paretic ankle joint power and total limb power increased significantly with exoskeleton assistance at six walking speeds (n00, n01, n02, n03, n04, n05). Despite these joint- and limb-level benefits associated with exoskeleton assistance, no subject averaged metabolic benefits were evident when compared to the unassisted condition. Both paretic trailing limb angle and integrated anterior paretic ground reaction forces were reduced with assistance applied as compared to no assistance at four speeds (n00, n01, n02, n03). CONCLUSIONS:Our results suggest that despite appropriate scaling of ankle assistance by the exoskeleton controller, suboptimal limb posture limited the conversion of exoskeleton assistance into forward propulsion. Future studies could include biofeedback or verbal cues to guide users into limb configurations that encourage the conversion of mechanical power at the ankle to forward propulsion. TRIAL REGISTRATION:N/A.

SUBMITTER: McCain EM

PROVIDER: S-EPMC6521500 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Controllers for assistive robotic devices can be divided into two main categories: controllers using neural signals and controllers using mechanically intrinsic signals. Both approaches are prevalent in research devices, but a direct comparison between the two could provide insight into their relative advantages and disadvantages. We studied subjects walking with robotic ankle exoskeletons using two different control modes: dynamic gain proportional myoelectric control based on soleus muscle activity (neural signal), and timing-based mechanically intrinsic control based on gait events (mechanically intrinsic signal). We hypothesized that subjects would have different measures of metabolic work rate between the two controllers as we predicted subjects would use each controller in a unique manner due to one being dependent on muscle recruitment and the other not. METHODS:The two controllers had the same average actuation signal as we used the control signals from walking with the myoelectric controller to shape the mechanically intrinsic control signal. The difference being the myoelectric controller allowed step-to-step variation in the actuation signals controlled by the user's soleus muscle recruitment while the timing-based controller had the same actuation signal with each step regardless of muscle recruitment. RESULTS:We observed no statistically significant difference in metabolic work rate between the two controllers. Subjects walked with 11% less soleus activity during mid and late stance and significantly less peak soleus recruitment when using the timing-based controller than when using the myoelectric controller. While walking with the myoelectric controller, subjects walked with significantly higher average positive and negative total ankle power compared to walking with the timing-based controller. CONCLUSIONS:We interpret the reduced ankle power and muscle activity with the timing-based controller relative to the myoelectric controller to result from greater slacking effects. Subjects were able to be less engaged on a muscle level when using a controller driven by mechanically intrinsic signals than when using a controller driven by neural signals, but this had no affect on their metabolic work rate. These results suggest that the type of controller (neural vs. mechanical) is likely to affect how individuals use robotic exoskeletons for therapeutic rehabilitation or human performance augmentation.

Project description:BackgroundElastic ankle exoskeletons with intermediate stiffness springs in parallel with the human plantarflexors can reduce the metabolic cost of walking by ~ 7% at 1.25 m s- 1. In a move toward 'real-world' application, we examined whether the unpowered approach has metabolic benefit across a range of walking speeds, and if so, whether the optimal exoskeleton stiffness was speed dependent. We hypothesized that, for any walking speed, there would be an optimal ankle exoskeleton stiffness - not too compliant and not too stiff - that minimizes the user's metabolic cost. In addition, we expected the optimal stiffness to increase with walking speed.MethodsEleven participants walked on a level treadmill at 1.25, 1.50, and 1.75 m s- 1 while we used a state-of-the-art exoskeleton emulator to apply bilateral ankle exoskeleton assistance at five controlled rotational stiffnesses (kexo = 0, 50, 100, 150, 250 Nm rad- 1). We measured metabolic cost, lower-limb joint mechanics, and EMG of muscles crossing the ankle, knee, and hip.ResultsMetabolic cost was significantly reduced at the lowest exoskeleton stiffness (50 Nm rad- 1) for assisted walking at both 1.25 (4.2%; p = 0.0162) and 1.75 m s- 1 (4.7%; p = 0.0045). At these speeds, the metabolically optimal exoskeleton stiffness provided peak assistive torques of ~ 0.20 Nm kg- 1 that resulted in reduced biological ankle moment of ~ 12% and reduced soleus muscle activity of ~ 10%. We found no stiffness that could reduce the metabolic cost of walking at 1.5 m s- 1. Across all speeds, the non-weighted sum of soleus and tibialis anterior activation rate explained the change in metabolic rate due to exoskeleton assistance (p < 0.05; R2 > 0.56).ConclusionsElastic ankle exoskeletons with low rotational stiffness reduce users' metabolic cost of walking at slow and fast but not intermediate walking speed. The relationship between the non-weighted sum of soleus and tibialis activation rate and metabolic cost (R2 > 0.56) indicates that muscle activation may drive metabolic demand. Future work using simulations and ultrasound imaging will get 'under the skin' and examine the interaction between exoskeleton stiffness and plantarflexor muscle dynamics to better inform stiffness selection in human-machine systems.

Project description:Powered ankle exoskeletons that apply assistive torques with optimized timing and magnitude can reduce metabolic cost by ∼10% compared to normal walking. However, finding individualized optimal control parameters is time consuming and must be done independently for different walking modes (e.g., speeds, slopes). Thus, there is a need for exoskeleton controllers that are capable of continuously adapting torque assistance in concert with changing locomotor demands. One option is to use a biologically inspired, model-based control scheme that can capture the adaptive behavior of the human plantarflexors during natural gait. Here, based on previously demonstrated success in a powered ankle-foot prosthesis, we developed an ankle exoskeleton controller that uses a neuromuscular model (NMM) comprised of a Hill type musculotendon driven by a simple positive force feedback reflex loop. To examine the effects of NMM reflex parameter settings on (i) ankle exoskeleton mechanical performance and (ii) users' physiological response, we recruited nine healthy, young adults to walk on a treadmill at a fixed speed of 1.25 m/s while donning bilateral tethered robotic ankle exoskeletons. To quantify exoskeleton mechanics, we measured exoskeleton torque and power output across a range of NMM controller Gain (0.8-2.0) and Delay (10-40 ms) settings, as well as a High Gain/High Delay (2.0/40 ms) combination. To quantify users' physiological response, we compared joint kinematics and kinetics, ankle muscle electromyography and metabolic rate between powered and unpowered/zero-torque conditions. Increasing NMM controller reflex Gain caused increases in average ankle exoskeleton torque and net power output, while increasing NMM controller reflex Delay caused a decrease in net ankle exoskeleton power output. Despite systematic reduction in users' average biological ankle moment with exoskeleton mechanical assistance, we found no NMM controller Gain or Delay settings that yielded changes in metabolic rate. Post hoc analyses revealed weak association at best between exoskeleton and biological mechanics and changes in users' metabolic rate. Instead, changes in users' summed ankle joint muscle activity with powered assistance correlated with changes in their metabolic energy use, highlighting the potential to utilize muscle electromyography as a target for on-line optimization in next generation adaptive exoskeleton controllers.

Project description:BACKGROUND:The human ankle joint has an influential role in the regulation of the mechanics and energetics of gait. The human ankle can modulate its joint 'quasi-stiffness' (ratio of plantarflexion moment to dorsiflexion displacement) in response to various locomotor tasks (e.g., load carriage). However, the direct effect of ankle stiffness on metabolic energy cost during various tasks is not fully understood. The purpose of this study was to determine how net metabolic energy cost was affected by ankle stiffness while walking under different force demands (i.e., with and without additional load). METHODS:Individuals simulated an amputation by using an immobilizer boot with a robotic ankle-foot prosthesis emulator. The prosthetic emulator was controlled to follow five ankle stiffness conditions, based on literature values of human ankle quasi-stiffness. Individuals walked with these five ankle stiffness settings, with and without carrying additional load of approximately 30% of body mass (i.e., ten total trials). RESULTS:Within the range of stiffness we tested, the highest stiffness minimized metabolic cost for both load conditions, including a ~?3% decrease in metabolic cost for an increase in stiffness of about 0.0480?Nm/deg/kg during normal (no load) walking. Furthermore, the highest stiffness produced the least amount of prosthetic ankle-foot positive work, with a difference of ~?0.04?J/kg from the highest to lowest stiffness condition. Ipsilateral hip positive work did not significantly change across the no load condition but was minimized at the highest stiffness for the additional load conditions. For the additional load conditions, the hip work followed a similar trend as the metabolic cost, suggesting that reducing positive hip work can lower metabolic cost. CONCLUSION:While ankle stiffness affected the metabolic cost for both load conditions, we found no significant interaction effect between stiffness and load. This may suggest that the importance of the human ankle's ability to change stiffness during different load carrying tasks may not be driven to minimize metabolic cost. A prosthetic design that can modulate ankle stiffness when transitioning from one locomotor task to another could be valuable, but its importance likely involves factors beyond optimizing metabolic cost.

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Mechanics and energetics of post-stroke walking aided by a powered ankle exoskeleton with speed-adaptive myoelectric control.

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