skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Propulsion Modulation Methods in People Post-Stroke during Resistive Ankle Exosuit Use
Locomotion requires careful coordination across the various joints and muscles of the body, which can be disrupted after neuromotor injuries such as stroke. People poststroke often have weakness in their paretic, or more impaired, ankle plantarflexors and a corresponding reliance on the hip joint to generate sufficient forward propulsion. The field of robotic rehabilitation has developed wearable systems that provide joint- and task-specific training for survivors of stroke, and in turn, increase use of the ankle muscles. However, capturing ankle use at the plantarflexor level remains a challenge with conventional tools given the unknown relative contributions of the dorsiflexor muscles. Moreover, variability across individuals complicates the interpretation of user response to these robotic interventions. In this work, we used standard biomechanical analysis as well as shear wave tensiometry in five people post-stroke to gain insight into user-specific ankle and hip adaptations in response to three levels of targeted plantarflexion exosuit resistance. We show that at a group and individual-level, evidence suggests a shift in biomechanical strategy from relying on the hip to using the ankle to modulate propulsion, with a subset of participants completely shifting to the ankle by the end of training. This work represents a step towards exploring more individualized methods for characterizing user response during adaptation to wearable robotic training interventions.  more » « less
Award ID(s):
2019621
PAR ID:
10570421
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ;
Publisher / Repository:
IEEE
Date Published:
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Stroke survivors experience muscle weakness and low weight-bearing capacity that impair their walking. The activation of the plantarflexor muscles is diminished following a stroke, which degrades propulsion and balance. Powered exoskeletons can improve gait capacity and restore impaired muscle activity. However, a technical barrier exists to generate systematic control methods to predictably and safely perturb the paretic leg using a wearable device to characterize the plantarflexors’ muscle output for gait training. In this paper, a closed-loop robust controller is designed to impose an ankle joint rotation (i.e., a kinematic perturbation) in the mid-late stance phase to target the soleus muscle using a powered cable-driven ankle-foot orthosis. The goal is to generate soleus muscle activity increments throughout a gait experiment by applying ankle perturbations. This ability to modulate plantarflexor activity can be used in future conditioning studies to improve push-off and propulsion during walking. However, the optimal perturbation magnitude for each participant is unknown. Hence, online adaptation of the ankle perturbation is well-motivated to modulate the soleus response measured using surface electromyography (EMG). An extremum seeking controller (ESC) is implemented in real-time to compute the ankle perturbation magnitude (i.e., dorsiflexion angle) exploiting the soleus EMG response from the previous perturbed step to maximize the soleus response in the next perturbed step. A Lyapunov-based stability analysis is used to guarantee exponential kinematic tracking of the ankle perturbation objective. 
    more » « less
  2. The gait patterns of stroke survivors become slow and metabolically inefficient as a result of muscle weakness and low weight-bearing capacity. Exoskeletons and assistive robots can improve gait kinematics and energetics. However, the use of these powered devices may cause a reliance on the device itself that results in limited lasting improvement of the paretic leg function. Specifically, there exists a need to strengthen and train the response of weak ankle muscles, such as the soleus muscle, in stroke survivors. Impaired activation of the soleus muscle induces unnatural gait kinematics and reduced propulsion. The mechanical modulation of the soleus muscle can improve its loading response and enhance gait performance after a stroke. This paper develops a closed-loop feedback controller to manipulate the ankle joint dynamics to mechanically control the soleus muscle response using a motorized ankle orthosis. The control method is inspired by backstepping control techniques and developed to connect the ankle joint angular velocity and the soleus muscle response during the stance phase of walking. The tracking objective is quantified using an integral-like muscle error between the desired soleus response and the actual muscle response, which is measurable using surface electromyography (EMG). The closed-loop electric motor controller is designed to apply ankle perturbations exploiting the backstepping error and an adaptive control term to cope with uncertain parameters that satisfy the linear-in-the-parameters property. A switching signal is developed using heel and toe ground reaction forces to strategically perturb the ankle and target the soleus muscle loading response in real-time during the mid-late stance phase of walking. A Lyapunov-based stability analysis is used to guarantee a globally uniformly ultimately bounded (GUUB) tracking result. 
    more » « less
  3. Current lower-limb prostheses do not provide active assistance in postural control tasks to maintain the user’s balance, particularly in situations of perturbation. In this study, we aimed to address this missing function by enabling neural control of robotic lower-limb prostheses. Specifically, electromyographic (EMG) signals (amplified neural control signals) recorded from antagonistic residual ankle muscles were used to drive a robotic prosthetic ankle directly and continuously. Participants with transtibial amputation were recruited and trained in using the EMG-driven robotic ankle. We studied how using the EMG-controlled ankle affected the participants’ anticipatory and compensatory postural control strategies and stability under expected perturbations compared with using their daily passive devices. We investigated the similarity of neuromuscular coordination (by analyzing motor modules) of the participants, using either device in a postural sway task, to that of able-bodied controls. Results showed that, compared with their passive prosthesis, the EMG-controlled prosthesis enabled participants to use near-normative postural control strategies, as evidenced by improved between-limb symmetry in intact-prosthetic center-of-pressure and joint angle excursions. Participants substantially improved postural stability, as evidenced by a reduction in steps or falls using the EMG-controlled prosthetic ankle. Furthermore, after relearning to use residual ankle muscles to drive the robotic ankle in postural control, nearly all participants’ motor module structure shifted toward that observed in individuals without limb amputations. Here, we have demonstrated the potential benefit of direct EMG control of robotic lower limb prostheses to restore normative postural control strategies (both neural and biomechanical) toward enhancing standing postural stability in amputee users. 
    more » « less
  4. Research on robotic lower-limb assistive devices over the past decade has generated autonomous, multiple degree-of-freedom devices to augment human performance during a variety of scenarios. However, the increase in capabilities of these devices is met with an increase in the complexity of the overall control problem and requirement for an accurate and robust sensing modality for intent recognition. Due to its ability to precede changes in motion, surface electromyography (EMG) is widely studied as a peripheral sensing modality for capturing features of muscle activity as an input for control of powered assistive devices. In order to capture features that contribute to muscle contraction and joint motion beyond muscle activity of superficial muscles, researchers have introduced sonomyography, or real-time dynamic ultrasound imaging of skeletal muscle. However, the ability of these sonomyography features to continuously predict multiple lower-limb joint kinematics during widely varying ambulation tasks, and their potential as an input for powered multiple degree-of-freedom lower-limb assistive devices is unknown. The objective of this research is to evaluate surface EMG and sonomyography, as well as the fusion of features from both sensing modalities, as inputs to Gaussian process regression models for the continuous estimation of hip, knee and ankle angle and velocity during level walking, stair ascent/descent and ramp ascent/descent ambulation. Gaussian process regression is a Bayesian nonlinear regression model that has been introduced as an alternative to musculoskeletal model-based techniques. In this study, time-intensity features of sonomyography on both the anterior and posterior thigh along with time-domain features of surface EMG from eight muscles on the lower-limb were used to train and test subject-dependent and task-invariant Gaussian process regression models for the continuous estimation of hip, knee and ankle motion. Overall, anterior sonomyography sensor fusion with surface EMG significantly improved estimation of hip, knee and ankle motion for all ambulation tasks (level ground, stair and ramp ambulation) in comparison to surface EMG alone. Additionally, anterior sonomyography alone significantly improved errors at the hip and knee for most tasks compared to surface EMG. These findings help inform the implementation and integration of volitional control strategies for robotic assistive technologies. 
    more » « less
  5. Healthy human locomotion functions with good gait symmetry depend on rhythmic coordination of the left and right legs, which can be deteriorated by neurological disorders like stroke and spinal cord injury. Powered exoskeletons are promising devices to improve impaired people's locomotion functions, like gait symmetry. However, given higher uncertainties and the time-varying nature of human-robot interaction, providing personalized robotic assistance from exoskeletons to achieve the best gait symmetry is challenging, especially for people with neurological disorders. In this paper, we propose a hierarchical control framework for a bilateral hip exoskeleton to provide the adaptive optimal hip joint assistance with a control objective of imposing the desired gait symmetry during walking. Three control levels are included in the hierarchical framework, including the high-level control to tune three control parameters based on a policy iteration reinforcement learning approach, the middle-level control to define the desired assistive torque profile based on a delayed output feedback control method, and the low-level control to achieve a good torque trajectory tracking performance. To evaluate the feasibility of the proposed control framework, five healthy young participants are recruited for treadmill walking experiments, where an artificial gait asymmetry is imitated as the hemiparesis post-stroke, and only the ‘paretic’ hip joint is controlled with the proposed framework. The pilot experimental studies demonstrate that the hierarchical control framework for the hip exoskeleton successfully (asymmetry index from 8.8% to − 0.5%) and efficiently (less than 4 minutes) achieved the desired gait symmetry by providing adaptive optimal assistance on the ‘paretic’ hip joint. 
    more » « less