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This study will compare the performance of a novel data-driven model-predictive controller (MPC) based functional electrical stimulation (FES) system versus a conventional FES system for footdrop correction during treadmill and overground walking tasks in people post-stroke.
Full description
Functional electrical stimulation (FES) is a common rehabilitation tool that incorporates electrical stimulation timed with a functional task to augment paretic muscle function in people with neuro-pathologies such as stroke and spinal cord injury. The rigor of previous research has established the safety, as well as both neuro-prosthetic and therapeutic effects of FES systems for standing, walking, and grasping. Stroke is the leading cause of disability, and footdrop is a highly prevalent post-stroke gait deficit, leading to insufficient ankle dorsiflexion during the swing phase of gait, and contributing to reduced mobility. FES systems that correct footdrop to improve gait function and reduce fall risk are gaining popularity, with commercial systems such as enhancing translation potential. Despite their promising functional value, accessibility, and positive neuroplasticity effects, current FES systems have some fundamental limitations, which limit their clinical prescription.
The goal of this project is to overcome two major limitations and technical gaps in FES: rapid onset of muscle fatigue during FES and lack of sophisticated closed-loop control of FES intensity. Most existing FES systems do not automatically modulate stimulation intensity in response to muscle fatigue, and may overstimulate the muscles if fixed (open-loop) stimulation or a pure feedback-based stimulation strategy is used to control FES intensity. To address this limitation, the researchers aim to develop and clinically test FES for improving stroke gait using data-driven FES control systems.
Footdrop is a highly prevalent post-stroke gait deficit, leading to insufficient ankle dorsiflexion during the swing phase of gait, and reducing functional mobility. FES, which is an external application of stimulation to generate muscle contractions during a functional motor task, can achieve muscle force demands during standing and walking, and help persons with stroke and spinal cord injury recover mobility. FES for the correction of footdrop is one of the most popular gait applications of FES, which has been shown to improve mobility and reduce falls.
Although FES has positive effects on walking function, elicits active muscle contractions, and enhances corticomotor excitability, FES is not used as commonly as passive orthotics. Most current FES systems incorporate motion sensors to control the timing of FES during the gait cycle (paretic leg swing phase). However, none of these systems provide automatic closed-loop control of FES intensity, so that optimal stimulation can be delivered for each step, preventing over-stimulation, reducing fatigue, and maintaining optimal muscle performance for a greater number of steps. Additionally, rapid onset of muscle fatigue during FES is caused by synchronous, non-selective, repeated recruitment of largely fatigable muscle fibers.
The researchers will implement an innovative model-predictive controller (MPC) combined with real-time ultrasound-based feedback to deliver optimal FES intensities and minimize fatigue.
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20 participants in 2 patient groups
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Trisha Kesar, PT, PhD
Data sourced from clinicaltrials.gov
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