Use of Acoustic Stimulation to Increase Slow-Wave Activity in Alzheimer’s Disease Patients/Analyzing Racial and Socioeconomic Differences in the Treatment and Outcomes of Adults with Alzheimer’s Disease

Teevan-Kamhawi, Saoirse, School of Engineering and Applied Science, University of Virginia
Earle, Joshua, Engineering and Society, University of Virginia
Barker, Shannon, EN-Biomed Engr Dep, University of Virginia
Allen, Timothy, EN-Biomed Engr Dept, University of Virginia

Alzheimer’s disease is a degenerative brain disease that progressively degrades a patient’s memory, thinking, and behavior over time. The technical project will focus on using sleep and the brain’s natural cleaning system to slow the progression of Alzheimer’s disease. The glymphatic system is a clearance system that uses cerebrospinal fluid flow through perivascular channels to remove soluble proteins and plaques in the brain. Alzheimer’s disease is characterized by the buildup of amyloid-β plaques in the brain, which can clump together and disrupt cell function. The goal of the technical project is to increase glymphatic activity in the brain to clear the plaques that build up in the early stages of the disease. The proposed technology for the technical project is a device that houses electrodes that will collect and monitor brain activity during sleep and deliver appropriate acoustic stimulation to enhance cerebrospinal fluid flow through the brain. In my STS component of the paper, I apply Actor-Network Theory to better understand how interactions between human and non-human actors in the medical system contribute to bias with treatment and diagnosis of the disease. This component of the thesis portfolio will highlight the racial biases that exist within the medical system, as these must be taken into account when trying to understand and address a disease such as Alzheimer’s disease.

BS (Bachelor of Science)
Alzheimer's Disease, Glymphatic, Biomedical Engineering, Slow Wave Activity

School of Engineering and Applied Science
Bachelor of Science in Biomedical Engineering
Technical Advisor: Shannon Barker
STS Advisor: Joshua Earle
Technical Team Members: Felix Donis Barrera, Patrick Lee, Laura Livingston, Saoirse Teevan-Kamhawi, Julia Yi

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