Dissertation Defense Announcement for Michael Phi Nguyen – 03/18/2026 at 10 AM

When: 18 March 2026, 10:00-12:00 AM

Where: Virtually via MS Teams. Simrall 228 is reserved for committee members.

Candidate: Michael Phi Nguyen

Degree: Doctor of Philosophy in Electrical and Computer Engineering

Committee Members:
Dr. Ryan Green (Major advisor)
Dr. Junming Diao (Committee member)
Dr. John Ball (Committee member)
Dr. Reuben Burch (Committee member)
Dr. Chaomin Luo (Committee member)

Abstract:
According to the 2017 Centers for Disease Control (CDC) and Prevention Report, 60% of adults nationwide have been diagnosed with one chronic disease, while 40% of those diagnosed have more than one chronic co-occurring illness. Patients with chronic diseases, specifically diabetes, heart disease, and Parkinson’s disease, rely on continuous monitoring systems to mitigate their symptoms. Over 37 million adults have diabetes, and 96 million are diagnosed with prediabetes. People with prolonged diabetic complications can experience blindness and amputation, leading to death. Whereas the chances of chest pain and cardiac arrest are greater for individuals with heart disease. Moreover, people with Parkinson’s disease can cause self-inflicted injuries due to involuntary shaking and muscle stiffening. Most patients suffering from these chronic diseases are prescribed wearable and implantable monitoring systems by their physicians. Patients with wearable and implantable continuous glucose monitoring (CGM) systems can monitor their blood glucose levels, while implantable pacemakers and deep-brain stimulation (DBS) systems are prescribed for individuals with heart and Parkinson’s disease. Despite the effectiveness of these systems, patients are limited by discrete data sampling rates from wearable CGM systems. While providing a fully implantable modem, some CGM systems are relatively large due to the power system and antenna size. Additionally, DBS systems require a relatively large and uncomfortable over-the-shoulder unit to charge the implantable device. Meanwhile, other implantable systems, such as pacemakers, contain permanent lithium-battery clusters; these battery cluster subsystems can malfunction, shortening the system's lifespan after surgery.

One solution to the discomfort, data transfer, and power limitations are wearable and implantable antennas that provide data and wireless power transfer. Such antenna designs for this application must be flexible, durable, and adaptable to everyday use, body motion, and the dielectric properties of tissues between people. This dissertation introduces two wearable E-textile antennas and an implantable antenna design for biomedical applications. The wearable antennas are fabricated from conductive screen-print ink and conductive fabric. The implantable antenna is manufactured from Rogers 6010.2 and is optimized using an AI/ML PSO algorithm. This dissertation presents the antenna design and its performance, validated through simulation, fabrication, and in-vitro testing using tissue-mimicking gels.