Herron, JeffreyRao, RajeshStrandquist, Gabrielle2024-10-162024-10-162024-10-162024Strandquist_washington_0250E_27575.pdfhttps://hdl.handle.net/1773/52461Thesis (Ph.D.)--University of Washington, 2024Neurological disorders are the leading cause of disability-adjusted life years and the second leading cause of death worldwide, with most having no cure. Ensuring people with neurological disorders have access to effective treatment and care is crucial.This dissertation presents a case study on the delivery and effectiveness of treatment for people with Parkinson's disease (PD), a progressive neurodegenerative disorder that negatively impacts mobility, sleep, vision, speech, psychological well-being, and more. Deep Brain Stimulation (DBS) is a neurosurgical treatment for PD that delivers electrical stimulation to deep brain structures. Adaptive DBS (aDBS) represents the next generation of this technology, dynamically adjusting stimulation parameters in real-time to treat symptoms more precisely. To deliver aDBS in home settings, infrastructure and remote symptom monitoring are needed. We conducted a two-year study building and deploying a prototype platform ecosystem to the home of a person receiving DBS therapy for PD. This novel system used in-home video cameras, wearable sensors, and chronic neural signal recordings to remotely evaluate treatment efficacy of aDBS during controlled tasks and naturalistic behavior. The open-source platform ecosystem supports remote updates to aDBS algorithms and can scale to many users. I next developed kinematic metrics of movement quality that significantly correlate with clinical symptom ratings from neurologists using data collected from our platform. Motivated by reviewer feedback and strategies in person-centered design, I explored the participant's experience through reflexive thematic analysis of an exit interview and non-numerical data collected throughout the study. This analysis revealed that actively viewing the participant as the Expert in living with PD, in living with DBS, and in interacting with our systems will improve the participant's experience and research outcomes. The analysis also provides important context to our collected data and kinematic metrics. I formulated key strategies for actively viewing study participants as experts as a guide for student researchers. Finally, I propose Participatory Action Research (PAR) as a strategy to guide researchers who want to collaborate with research participants in solving neurological problems. PAR is based on tenets for how to collaboratively conduct research, offering a flexible framework that engages with a community and centers the needs of the people that solutions are intended for. I call on the scientists, engineers, clinicians, and other authorities researching treatments for neurological disorders to stop excluding participants from the research process, and we outline ways that PAR can assist with the unique challenges of developing more effective treatments for neurological disorders.application/pdfen-USnoneComputer scienceNeurosciencesEngineeringComputer science and engineeringThesis