Toward Personalized Stroke Rehabilitation in the Community With a Mobile FES Neuroprosthesis

Abstract

As the field of lower-limb assistive technology advances, there is growing interest in shifting gait rehabilitation from controlled clinical environments to community-based settings, aiming to enhance motor recovery through increased training dosage, intensity, and ecological validity. Functional electrical stimulation (FES) neuroprostheses targeting plantarflexion have emerged as promising tools to support gait rehabilitation by activating biological muscles directly, thus promoting neuroplasticity and yielding improvements that persist beyond active stimulation. However, existing FES systems primarily rely on preset stimulation patterns and controlled clinical conditions, limiting their real-world applicability, adaptability, and long-term effectiveness. To address these limitations, this thesis presents the development and evaluation of a mobile FES neuroprosthesis designed to provide personalized push-off propulsion and ground clearance assistance, two deficits widely observed in individuals post-stroke. The mobile platform enables adaptive control based on biomechanical responses and user preference, supported by wearable sensing frameworks to enable longitudinal monitoring and tuning in community settings. The first aim introduces the mobile FES system and demonstrates its capability to provide targeted stimulation during overground walking with stroke survivors. Through a series of technical pilot studies, we highlight critical design considerations for community deployment, including coordinated stimulation of dorsiflexion and plantarflexion, personalized control using biomechanical inputs, and management of physiological phenomena such as electromechanical delay and fatigue. Using this system, we explored the biomechanical effects of overground walking with FES, finding both immediate and short-term retained benefits, highlighting its potential to meaningfully enhance daily function and quality of life. Notably, optimal stimulation timing varied considerably between individuals, underscoring the necessity for personalized tuning to maximize biomechanical improvements and avoid exacerbating gait impairments. Building on these findings, the second aim investigates strategies for personalizing FES while balancing multiple competing objectives, including biomechanical effectiveness, comfort, and long-term adherence. We developed a multi-perspective personalization framework combining user preferences and biomechanical performance metrics. Interestingly, we observed that clinicians, who are often tasked with tuning and prescribing these devices, largely favored visible kinematic changes over critical kinetic features essential for effective propulsion. This finding suggests that human perception alone may be insufficient for optimal tuning and reinforces the need for objective biomechanical guidance that can ensure better clinical outcomes and more effective gait rehabilitation. The final aim focuses on addressing this gap by establishing estimation frameworks that use wearable sensing, such as inertial measurement units and pressure insoles, to provide accurate kinetic estimates for populations with neuromotor gait impairments outside laboratory environments. These methods lay the foundation for future expert-informed and automated device tuning, and facilitate comprehensive real-world monitoring of gait biomechanics. Furthermore, we demonstrated the feasibility of integrating these wearable-derived kinetic variables as inputs into adaptive control algorithms for wearable devices, including the mobile FES platform and an ankle exoskeleton, representing a meaningful step toward practical community deployment. Additionally, we investigated methods combining electrical stimulation with ultrasound imaging to reliably track muscle fatigue, offering an initial step toward characterizing muscle states in real-time and providing feedback to enable safe assistance that could respond to the onset of fatigue. Collectively, this thesis lays important groundwork toward achieving scalable, personalized, and clinically impactful gait rehabilitation in everyday community environments through a multifaceted approach that combines portability, user-specific adaptation, and biomechanics-informed control.