Medical diagnostic devices are in high demand due to increasing cases of neurodegenerative diseases in the aging population and pandemic outbreaks in our increasingly connected global community. Devices capable of detecting the presence of a disease in its early stages can have dramatic impacts on how it can be treated or eliminated. High cost and limited accessibility to diagnostic tools are the main barriers preventing potential patients from receiving a timely disease diagnosis. This dissertation presents several devices that are aimed at providing higher quality medical diagnostics at a low cost. Brain function is commonly studied with systems detecting the action potentials that are formed when neurons fire. CMOS technology enables extremely high-density electrode arrays to be produced with integrated amplifiers for high-throughput action potential measurement systems while greatly reducing the cost per measurement compared to traditional tools. Recently, CMOS technology has also been used to develop high-throughput electrochemical measurement systems. While action potentials are important, communication between neurons occurs by the flow of neurotransmitters at the synapses, so measurement of action potentials alone is incapable of fully studying neurotransmission. In many neurodegenerative diseases the breakdown in neurotransmission begins well before the disease manifests itself. The development of a dual-mode CMOS device that is capable of simultaneous high-throughput measurement of both action potentials and neurotransmitter flow via an on-chip electrode array is presented in this dissertation. This dual-mode technology is useful to those studying the dynamic decay of the neurotransmission process seen in many neurodegenerative diseases using a low-cost CMOS chip. This dissertation also discusses the development of more traditional diagnostic devices relying on PCR, a method commonly used only in centralized laboratories and not readily available at the point-of-care. These technologies will enable faster, cheaper, more accurate, and more accessible diagnostics to be performed closer to the patient.


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Graduation Date





Kim, Brian


Doctor of Philosophy (Ph.D.)


College of Engineering and Computer Science


Electrical and Computer Engineering

Degree Program

Electrical Engineering




CFE0009657; DP0027588





Release Date

February 2023

Length of Campus-only Access


Access Status

Doctoral Dissertation (Open Access)

Included in

Biomedical Commons