Extremum Seeking Control of a Robotic Ankle-Foot Orthosis Targeting the Soleus Muscle Activation During Walking

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.

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Published
2024-08-21
DOI
https://doi.org/10.1109/ccta60707.2024.10666517
Primary Topic
Extremum Seeking Control Systems
Type
article
Field-Weighted Citation Impact
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article

Extremum Seeking Control of a Robotic Ankle-Foot Orthosis Targeting the Soleus Muscle Activation During Walking

Nicholas Rubino, Jade Carter, Aiko K. Thompson, Victor H. Duenas et al.
Extremum Seeking Control Systems
article

Extremum Seeking Control of a Robotic Ankle-Foot Orthosis Targeting the Soleus Muscle Activation During Walking

Nicholas Rubino, Jade Carter, Aiko K. Thompson, Victor H. Duenas, Evan Tulsky
article en

Abstract

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.

Medical University of South Carolina (US), Syracuse University (US)
National Science Foundation
Life below water
Openalex Percentile: Top 84%
Extremum Seeking Control Systems
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