Cellular assays are the backbone of biological studies - be it for tissue modeling, drug discovery, therapeutics, or diagnostics. Two-dimensional (2D) cell culture has been deployed for several decades to garner physiologically relevant information and predict data before the cost-intensive animal testing. Although 2D techniques have been valuable for cellular assays, they have a colossal limitation - they do not adequately consider the natural three-dimensional (3D) microenvironment of the cells. As a result, they sometimes provide misleading statistics. Therefore, it is important to develop a 3D model that predicts cellular behaviors and their interaction with neighboring cells and extracellular matrix (ECM) in a more realistic manner. In recent biomedical research, various platforms have been modeled to generate 3D prototypes of tissues, spheroids, in vitro that could allow the study of cellular responses resembling in vivo environments, such as matrices, scaffolds, and devices. But most of these platforms have drawbacks such as lack of spheroid size control, low yield, or high cost associated with them. On the other hand, Amikagel is a low cost, high-fidelity platform that can facilitate the convenient generation of tumor and stem cell spheroids. Furthermore, Amikabeads are aminoglycoside-derived hydrogel microbeads derived from the same monomers as Amikagel. They are a versatile platform with several chemical groups that can be exploited for encapsulating the spheroids and investigating the delivery of bioactive compounds to the cells. This thesis is focused on engineering novel 3D tumor and stem cell models generated on Amikagel and encapsulated in Amikabeads for proximal delivery of bioactive compounds and applications in regenerative medicine.

Wearable technology has brought in a rapid shift in the areas of healthcare and lifestyle management. The recent development and usage of wearable devices like smart watches has created significant impact in areas like fitness management, exercise tracking, sleep quality assessment and early diagnosis of diseases like asthma, sleep apnea etc. This thesis is dedicated to the development of wearable systems and algorithms to fulfill unmet needs in the area of cardiorespiratory monitoring.

First, a pneumotach based flow sensing technique has been developed and integrated into a face mask for respiratory profile tracking. Algorithms have been developed to convert the pressure profile into respiratory flow rate profile. Gyroscope-based correction is used to remove motion artifacts that arise from daily activities. By using Principal Component Analysis, the follow-up work established a unique respiratory signature for each subject based on the flow profile and lung parameters computed using the wearable mask system.

Next, wristwatch devices to track transcutaneous gases like oxygen (TcO2) and carbon dioxide (TcCO2), and oximetry (SpO2) have been developed. Two chemical sensing approaches have been explored. In the first approach, miniaturized low-cost commercial sensors have been integrated into the wristwatch for transcutaneous gas sensing. In the second approach, CMOS camera-based colorimetric sensors are integrated into the wristwatch, where a part of camera frame is used for photoplethysmography while the remaining part tracks the optical signal from colorimetric sensors.

Finally, the wireless connectivity using Bluetooth Low Energy (BLE) in wearable systems has been explored and a data transmission protocol between wearables and host for reliable transfer has been developed. To improve the transmission reliability, the host is designed to use queue-based re-request routine to notify the wearable device of the missing packets that should be re-transmitted. This approach avoids the issue of host dependent packet losses and ensures that all the necessary information is received.

The works in this thesis have provided technical solutions to address challenges in wearable technologies, ranging from chemical sensing, flow sensing, data analysis, to wireless data transmission. These works have demonstrated transformation of traditional bench-top medical equipment into non-invasive, unobtrusive, ergonomic & stand-alone healthcare devices.

The study of soft magnetic materials has been growing in popularity in recent years. Driving this interest are new applications for traditional electrical power-management components, such as inductors and transformers, which must be scaled down to the micro and nano scale while the frequencies of operation have been scaling up to the gigahertz range and beyond. The exceptional magnetic properties of the materials make them highly effective in these small-component applications, but the ability of these materials to provide highly-effective shielding has not been so thoroughly considered. Most shielding is done with traditional metals, such as aluminum, because of the relatively low cost of the material and high workability in shaping the material to meet size and dimensional requirements.

This research project focuses on analyzing the variance in shielding effectiveness and electromagnetic field effects of a thin film of Cobalt Zirconium Tantalum Boron (CZTB) in the band of frequencies most likely to require innovative solutions to long-standing problems of noise and interference. The measurements include Near H-Field attenuation and field effects, Far Field shielding, and Backscatter. Minor variances in the thickness and layering of sputter deposition can have significant changes electromagnetic signature of devices which radiate energy through the material.

The material properties presented in this research are H-Field attenuation, H-Field Flux Orientation, Far-Field Approximation, E Field Vector Directivity, H Field Vector Directivity, and Backscatter Magnitude. The results are presented, analyzed and explained using characterization techniques. Future work includes the effect of sputter deposition orientation, application to devices, and applicability in mitigating specific noise signals beyond the 5G band.

This paper presents work that was done to develop an energy-efficient electoral and frame count system for underwater sea turtle image and video recognition using convolutional neural networks, deep learning framework, and the Python programming language. An underwater sea turtle image recognition program is essential to protect turtles from the threat of bycatch - sea turtles are accidentally caught when fishermen aim for a different type of underwater species. This underwater image recognition system is used to detect the presence of sea turtles, then different kinds of acoustic and light stimuli are used to warn the turtles of approaching danger to reduce bycatch. This image detection system will be placed on a fishing boat to run on a machine at all times (24 hours and 7 days a week). A live video capture from a low-power underwater camera that is attached to the boat will be sent to the image detection system on the machine to analyze the presence of sea turtles in each frame of the video. To lower the computational time and energy of the machine, an energy-efficient electoral and frame count system is implemented on this image detection system.

Background: Recent interests in continuous biomonitoring and the surge of wearable biotechnology demand a better understanding of sweat as a noninvasive biomarker resource. The ability to use sweat as a biofluid provides the opportunity for noninvasive early and continuous diagnostics. This thesis serves to help fill the existing knowledge gap in sweat biomarker discovery and applications.

Experimental Design: In part one of this study, exercise-induced eccrine sweat was collected from 50 healthy individuals and analyzed using mass spectrometry, protein microarrays, and quantitative ELISAs to identify a broad range of proteins, antibody isotypes, and cytokines in sweat. In part two of this study, cortisol and melatonin levels were analyzed in exercise-induced sweat and plasma samples collected from 22 individuals.

Results: 220 unique proteins were identified by shotgun analysis in pooled sweat samples. Detectable antibody isotypes include IgA (100% positive; median 1230 ± 28 700 pg/mL), IgD (18%; 22.0 ± 119 pg/mL), IgG1 (96%;1640 ± 6750 pg/mL), IgG2 (37%; 292 ± 6810 pg/mL), IgG3 (71%;74.0 ± 119 pg/mL), IgG4 (69%; 43.0 ± 42.0 pg/mL), and IgM (41%;69.0 ± 1630 pg/mL). Of 42 cytokines, three were readily detected in all sweat samples (p<0.01). The median concentration for interleukin-1α was 352 ± 521 pg/mL, epidermal growth factor was 86.5 ± 147 pg/mL, and angiogenin was 38.3 ± 96.3 pg/mL. Multiple other cytokines were detected at lower levels. The median and standard deviation of cortisol was determined to be 4.17 ± 11.1 ng/mL in sweat and 76.4 ± 28.8 ng/mL in plasma. The correlation between sweat and plasma cortisol levels had an R-squared value of 0.0802 (excluding the 2 highest sweat cortisol levels). The median and standard deviation of melatonin was determined to be 73.1 ± 198 pg/mL in sweat and 194 ± 93.4 pg/mL in plasma. Similar to cortisol, the correlation between sweat and plasma melatonin had an R-squared value of 0.117.

Conclusion: These studies suggest that sweat holds more proteomic and hormonal biomarkers than previously thought and may eventually serve as a noninvasive biomarker resource. These studies also highlight many of the challenges associated with monitoring sweat content including differences between collection devices and hydration, evaporation losses, and sweat rate.

The growth of the medical diagnostic industry in the past several decades has largely been due to the creation and iterative optimization of bio sensors. Recent pushes towards value added as well as preventative health care has made point of care devices more attractive to health care providers. Rapid detection for diseases and cancers is done with a bio sensor, which a broad term used to describe an instrument which uses a bio chemical reaction to detect a chemical compound with the use of a bio recognition event in addition to a signal detection event. The bio sensors which are presented in this work are known as ion-sensitive field effects transistors (ISFETs) and are similar in function to a metal oxide field effect transistor (MOSFET). These ISFETs can be used to sense pH or the concentration of protons on the surface of the gate channel. These ISFETs can be used for certain bio recognition events and this work presents the application of these transistors for the quantification of tumor cell proliferation. This includes the development of a signal processing and acquisition system for the long term assessment of cellular metabolism and optimizing the system for use in an incubator. This thesis presents work done towards the optimization and implementation of complementary metal\u2014oxide\u2014semiconductor (CMOS) ISFETs as well as remote gate ISFETs for the continuous assessment of tumor cell extracellular pH. The work addresses the challenges faced with the fabrication and optimization of these sensors, which includes the mitigation of current drift with the use of pulse width modulation in addition to issues encountered with fabrication of electrodes on a quartz substrate. This work culminates in the testing of an autonomous system with mammary tumor cells as well as the assessment of cell viability in an incubator over extended periods. Future applications of this work include the creation of a remote gate ISFET array for multiplexed detection as well as the implementation of ISFETs for bio marker detection via an immunoassay.

The goal of this project was to explore biomimetics by creating a jellyfish flying device that uses propulsion of air to levitate while utilizing electromyography signals and infrared signals as mechanisms to control the device. Completing this project would require knowledge of biological signals, electrical circuits, computer programming, and physics to accomplish. An EMG sensor was used to obtain processed electrical signals produced from the muscles in the forearm and was then utilized to control the actuation speed of the tentacles. An Arduino microprocessor was used to translate the EMG signals to infrared blinking sequences which would propagate commands through a constructed circuit shield to the infrared receiver on jellyfish. The receiver will then translate the received IR sequence into actions. Then the flying device must produce enough thrust to propel the body upwards. The application of biomimetics would best test my skills as an engineer as well as provide a method of applying what I have learned over the duration of my undergraduate career.

This thesis dissertation presents design of portable low power Electrochemical Impedance Spectroscopy (EIS) system which can be used for biomedical applications such as tear diagnosis, blood diagnosis, or any other body-fluid diagnosis. Two design methodologies are explained in this dissertation (a) a discrete component-based portable low-power EIS system and (b) an integrated CMOS-based portable low-power EIS system. Both EIS systems were tested in a laboratory environment and the characterization results are compared. The advantages and disadvantages of the integrated EIS system relative to the discrete component-based EIS system are presented including experimental data. The specifications of both EIS systems are compared with commercially available non-portable EIS workstations. These designed EIS systems are handheld and very low-cost relative to the currently available commercial EIS workstations.

ABSTRACT

Designers creating the next generation remote sensing enabled smart devices need to overcome the challenges of prevailing ventures including time to market and expense.

To reduce the time and effort involved in initial prototyping, a good reference design is often desired and warranted. This paper provides the necessary reference materials for Designers to implement a wireless solution efficiently and effectively.

This document is intended for users with limited Bluetooth technology experience.

Many sensing-enabled devices require a ‘hard-wire’ or cable link to a host monitoring system. This can limit the potential for product advancements by anchoring the system to a single location preventing portability and the convenience of a remote system. By removing the “wired” or cabled portion from a design, a broader scope of devices becomes feasible.

One common problematic area for these types of sensors is within the internal medicine field. Proximity sensing is far more practical and less invasive to implement than surgical implantation. Bluetooth Low Energy (BLE) systems solve the hard wired problem by decoupling the physical sensor from the host system through a BLE transceiver that can send information to an external monitoring system. This wireless link enables new sensor technology to be leveraged into previously unobtainable markets; such as, internal medicine, wearable devices, and Infotainment to name a few. Wireless technology for sensor systems are a potentially disruptive technology changing the way environmental monitoring is implemented and considered.

With this BLE design reference, products can be created with new capabilities to advance current technologies for military, commercial, industrial and medical sectors in rapid succession.