The full text of this item is not available at this time because the student has placed this item under an embargo for a period of time. The Libraries are not authorized to provide a copy of this work during the embargo period, even for Texas A&M users with NetID.
Functional Locomotor Recovery After Spinal Cord Injury Using AI-Based Closed-Loop Stimulation
Abstract
Spinal cord injury (SCI) is a devastating condition that severely impairs locomotor function and affects multiple body systems. With millions of people worldwide affected by SCI and new injuries occurring frequently not only from diseases but also from everyday activities such as car accidents, falls, violence, sports, and so on, there is an urgent need to explore effective strategies for restoring motor abilities. This dissertation is divided into four chapters, aiming to investigate and develop innovative approaches to regain locomotor function after SCI.
The study begins with an examination of sensory feedback deficits following SCI and proposes the hypothesis that augmenting weakened sensory feedback through electrical stimulation augmenting plantar cutaneous sensory feedback can enhance motor output and improve locomotion. An in-depth analysis of spindle afferent feedback from ankle extensor muscles and the generation of afferent volleys corresponding to plantar cutaneous sensory feedback through electrical stimulation on the distal-tibial nerve is conducted in the first chapter.
The second chapter focuses on the development and validation of a fully implantable device designed for motion-dependent closed-loop plantar cutaneous augmentation. The system's functionality and performance are thoroughly assessed, ensuring its suitability for the intended purpose. Next, the dissertation explores the effects of augmented plantar cutaneous feedback on ankle plantarflexion and dorsiflexion during locomotion. Closed-loop distal-tibial nerve stimulation using the developed fully implantable device that is introduced in the second chapter was utilized to investigate its impact on ankle joint movement.
Lastly, an AI-based closed-loop peripheral nerve stimulation approach is introduced, employing state-of-the-art edge AI technology to restore locomotor function after SCI. The performance of this novel approach is evaluated using an SCI rat model, demonstrating its potential as an effective neural interface tool for enhancing locomotion, and reducing human intervention to generate optimized stimulation pulses for maximum effectiveness of closed-loop electrical stimulation on gait rehabilitation after SCI.
This dissertation contributes to the understanding of locomotor rehabilitation after SCI and presents innovative strategies for augmenting motor function. By addressing the deficits in sensory feedback and exploring novel stimulation techniques, this research opens new avenues for improving locomotor outcomes in individuals with SCI. The findings from this study have implications for the development of next-generation neural interface systems and provide valuable insights into the restoration of locomotor function in the context of spinal cord injury.
Subject
Spinal Cord InjuryNeuromodulation, Closed-loop Stimulation
AI
Ankle Joint
Plantarflexion
Sensory Augmentation
Ankle Joint
Citation
Shon, Ahnsei (2023). Functional Locomotor Recovery After Spinal Cord Injury Using AI-Based Closed-Loop Stimulation. Doctoral dissertation, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /200012.