Search for: All records

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. 

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. 

For individuals with movement impairments due to neurological injuries, rehabilitative therapies such as functional electrical stimulation (FES) and rehabilitation robots hold vast potential to improve their mobility and activities of daily living. Combining FES with rehabilitation robots results in intimately coordinated human–robot interaction. An example of such interaction is FES cycling, where motorized assistance can provide high-intensity and repetitive practice of coordinated limb motion, resulting in physiological and functional benefits. In this paper, the development of multiple FES cycling testbeds and safeguards is described, along with the switched nonlinear dynamics of the cycle–rider system. Closed-loop FES cycling control designs are described for cadence and torque tracking. For each tracking objective, the authors’ past work on robust and adaptive controllers used to compute muscle stimulation and motor current inputs is presented and discussed. Experimental results involving both able-bodied individuals and participants with neurological injuries are provided for each combination of controller and tracking objective. Trade-offs for the control algorithms are discussed based on the requirements for implementation, desired rehabilitation outcomes and resulting rider performance. Lastly, future works and the applicability of the developed methods to additional technologies including teleoperated robotics are outlined.