Date of Award

12-2024

Degree Name

Doctor of Philosophy

Department

Electrical and Computer Engineering

First Advisor

Massood Z. Atashbar, Ph.D.

Second Advisor

Bradley J. Bazuin, Ph.D.

Third Advisor

Daryl Lawson, Ph.D.

Fourth Advisor

Simin Masihi, Ph.D.

Keywords

Diabetic foot ulcer, flexible hybrid electronics, intelligent health monitoring, machine learning, photoplethysmography, wearable electronics

Abstract

Advanced data analytics approaches, such as artificial intelligence (AI), are increasingly being integrated into all aspects of patient care. This integration is paving the way for minimally invasive or non-invasive treatment modalities. By combining recent advancements in fabrication technology and computing ingenuity, wearable devices now enable continuous health monitoring and provide data for AI-driven analysis. These intelligent devices seamlessly integrate with the Internet of Things (IoT), enabling remote or “at-home” patient monitoring.

This dissertation study investigates the integration of recent advancements in flexible hybrid electronics (FHE) and machine learning (ML) to develop intelligent health monitoring systems. The developed FHE-based health and condition monitoring systems, integrated with the IoT, utilize hardware and software components to record, transmit, store, and analyze data in real time. This is achieved through various sensor acquisition and data communication technologies, as well as software development algorithms. This dissertation encompasses three primary studies:

The first study investigates the development of a fully functional prototype of a flexible smart wearable oximeter insole that can monitor peripheral oxygen saturation (SpO2) levels at the foot of a diabetic patient using photoplethysmography (PPG) signals. Continuous monitoring of SpO2 levels at foot in patients with diabetic foot ulcer (DFU) can provide critical information on the severity of the ulcer, the wound healing process, and alerting clinicians for critical limb ischemia. The developed oximetry system seamlessly integrates the IoT via a custom-developed Android mobile application, enabling features for at-home monitoring.

In the second study, differences between finger and toe PPG and factors influencing signals including biometric variables such as age and skin thickness, as well as measurement conditions like varying wavelength of the light source, external contact pressure, and measurement sites have been investigated. Additionally, the potential of PPG as a non-invasive and cost-effective approach for monitoring vital health parameters and cardiac output (CO) has been examined, including measurements of SpO2, blood volume pulse (BVP), blood perfusion index (PI), and arterial stiffness index (SI). These capabilities enable personalized treatment for certain conditions like DFU by assessing changes in SpO2 and PI before, during, and after wound healing treatments such as electrical stimulation and heat therapy. A custom C# Windows application was developed to control the electrical stimulation and heat modules, manage data collection, perform signal processing, extract relevant features, and predict and visualize outcomes for clinical studies. The full potential of PPG in DFU care depends on the parameters that can influence it. These parameters have been investigated via advanced data analysis, where ML plays a significant role.

The third study investigates the development of an FHE solution that enables real-time condition monitoring across various applications, ranging from medical and pharmaceutical industries to military assets. Flexible hybrid electronics involve the combination of novel printing techniques and traditional electronic manufacturing processes, to create flexible devices with enhanced performance. A comparative study is presented between two advanced power-efficient FHE monitoring systems, the copper-flex system (CFS) and the printed-flex system (PFS), which utilize low-power components and optimized power management to extend battery life. These systems are specifically designed for accurately measuring temperature within storage containers. Furthermore, these systems, either CFS or PFS, have potential applications in medical treatments such as heat therapy for DFU, by measuring the internal temperature of a therapeutic boot integrated with the insole designed in the first study. After assembly, reliability and durability tests were conducted to validate the performance of the temperature sensor and the interconnections of the CFS and PFS prototypes. Additionally, environmental and mechanical characterizations including, moisture and insulation resistance, corrosion, elongation, bending, terminal bond strength, and peel tests were performed based on the Institute of Printed Circuits Test Method (IPC-TM) and American Society for Testing and Materials (ASTM) standards. The results from these mechanical and environmental tests provide valuable insights that can be applied to the development of any wearable flexible hybrid electronics (WFHE).

Comments

Fifth advisor: Dinesh Maddipatla, Ph.D.

Access Setting

Dissertation-Open Access

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