Behavior-driven obesity has become one of the most challenging global epidemics since the 1990s, and is presently associated with the leading causes of death in the U.S. and worldwide, including diabetes, cardiovascular disease, strokes, and some forms of cancer. The use of system identification and control engineering principles in the design of novel and perpetually adaptive behavioral health interventions for promoting physical activity and healthy eating has been the central theme in many recent contributions. However, the absence of experimental studies specifically designed with the purpose of developing control-oriented behavioral models has restricted prior efforts in this domain to the use of hypothetical simulations to demonstrate the potential viability of these interventions. In this dissertation, the use of first-of-a-kind, real-life experimental results to develop dynamic, participant-validated behavioral models essential for the design and evaluation of optimized and adaptive behavioral interventions is examined. Following an intergenerational approach, the first part of this work aims to develop a dynamical systems model of intrauterine fetal growth with the prime goal of predicting infant birth weight, which has been associated with subsequent childhood and adult-onset obesity. The use of longitudinal input-output data from the “Healthy Mom Zone” intervention study has enabled the estimation and validation of this fetoplacental model. The second part establishes a set of data-driven behavioral models founded on Social Cognitive Theory (SCT). The “Just Walk” intervention experiment, developed at Arizona State University using system identification principles, has lent a unique opportunity to estimate and validate both black-box and semiphysical SCT models for predicting physical activity behavior. Further, this dissertation addresses some of the model estimation challenges arising from the limitations of “Just Walk”, including the need for developing nontraditional modeling approaches for short datasets, as well as delivers a new theoretical and algorithmic framework for structured state-space model estimation that can be used in a broader set of application domains. Finally, adaptive closed-loop intervention simulations of participant-validated SCT models from “Just Walk” are presented using a Hybrid Model Predictive Control (HMPC) control law. A simple HMPC controller reconfiguration strategy for designing both single- and multi-phase intervention designs is proposed.

This work describes the development of a device for measuring CO2 in breath, which has applications in monitoring a variety of health issues, such as Chronic Obstructive Pulmonary Disease (COPD), asthma, and cardiovascular disease. The device takes advantage of colorimetric sensing technology in order to maintain a low cost and high user-friendliness. The sensor consists of a pH dye, reactive element, and base coated on a highly porous Teflon membrane. The transmittance of the sensor is measured in the device via a simple LED/photodiode system, along with the flow rate, ambient relative humidity, and barometric pressure. The flow is measured by a newly developed flow meter described in this work, the Confined Pitot Tube (CPT) flow meter, which provides a high accuracy with reduced flow-resistance with a standard differential pressure transducer. I demonstrate in this work that the system has a high sensitivity, high specificity, fast time-response, high reproducibility, and good stability. The sensor has a simple calibration method which requires no action by the user, and utilizes a sophisticated, yet lightweight, model in order to predict temperature changes on the sensor during breathing and track changes in water content. It is shown to be effective for measuring CO2 waveform parameters on a breath-by-breath basis, such as End-Tidal CO2, Alveolar Plateau Slope, and Beginning Exhalation Slope.

The accurate and fast determination of organic air pollutants for many applications and studies is critical. Exposure to volatile organic compounds (VOCs) has become an important public health concern, which may induce a lot of health effects such as respiratory irritation, headaches and dizziness. In order to monitor the personal VOCs exposure level at point-of-care, a wearable real time monitor for VOCs detection is necessary. For it to be useful in real world application, it requires low cost, small size and weight, low power consumption, high sensitivity and selectivity.

To meet these requirements, a novel mobile device for personal VOCs exposure monitor has been developed. The key sensing element is a disposable molecularly imprinted polymer based quartz tuning fork resonator. The sensor and fabrication protocol are low cost, reproducible and stable. Characterization on the sensing material and device has been done. Comparisons with gold standards in the field such as GC-MS have been conducted. And the device’s functionality and capability have been validated in field tests, proving that it’s a great tool for VOCs monitoring under different scenarios.

A low temperature amorphous oxide thin film transistor (TFT) and amorphous silicon PIN diode backplane technology for large area flexible digital x-ray detectors has been developed to create 7.9-in. diagonal backplanes. The critical steps in the evolution of the backplane process include the qualification and optimization of the low temperature (200 °C) metal oxide TFT and a-Si PIN photodiode process, the stability of the devices under forward and reverse bias stress, the transfer of the process to flexible plastic substrates, and the fabrication and assembly of the flexible detectors.

Mixed oxide semiconductor TFTs on flexible plastic substrates suffer from performance and stability issues related to the maximum processing temperature limitation of the polymer. A novel device architecture based upon a dual active layer improves both the performance and stability. Devices are directly fabricated below 200 ºC on a polyethylene naphthalate (PEN) substrate using mixed metal oxides of either zinc indium oxide (ZIO) or indium gallium zinc oxide (IGZO) as the active semiconductor. The dual active layer architecture allows for adjustment to the saturation mobility and threshold voltage stability without the requirement of high temperature annealing, which is not compatible with flexible plastic substrates like PEN. The device performance and stability is strongly dependent upon the composition of the mixed metal oxide; this dependency provides a simple route to improving the threshold voltage stability and drive performance. By switching from a single to a dual active layer, the saturation mobility increases from 1.2 cm2/V-s to 18.0 cm2/V-s, while the rate of the threshold voltage shift decreases by an order of magnitude. This approach could assist in enabling the production of devices on flexible substrates using amorphous oxide semiconductors.

Low temperature (200°C) processed amorphous silicon photodiodes were developed successfully by balancing the tradeoffs between low temperature and low stress (less than -70 MPa compressive) and device performance. Devices with a dark current of less than 1.0 pA/mm2 and a quantum efficiency of 68% have been demonstrated. Alternative processing techniques, such as pixelating the PIN diode and using organic photodiodes have also been explored for applications where extreme flexibility is desired.

The accurate and fast determination of carbon dioxide (CO2) levels is critical for many health and environmental applications. For example, the analysis of CO2 levels in exhaled breath allows for the evaluation of systemic metabolism, perfusion, and ventilation, and provides the doctors and patients with a non-invasive and simple method to predict the presence and severity of asthma, and Chronic Obstructive Pulmonary Disease (COPD). Similarly, the monitoring of CO2 levels in the atmosphere allows for assessment of indoor air quality (IAQ) as the indoor CO2 levels have been proved to be associated with increased prevalence of certain mucous membrane and respiratory sick building syndrome (SBS) symptoms. A pocket-sized CO2 analyzer has been developed for real-time analysis of breath CO2 and environmental CO2. This CO2 analyzer is designed to comprise two key components including a fluidic system for efficient gas sample delivery and a colorimetric detection unit integrated into the fluidic system. The CO2 levels in the gas samples are determined by a disposable colorimetric sensor chip. The sensor chip is a novel composite based sensor that has been optimized to provide fast and reversible response to CO2 over a wide concentration range, covering the needs of both environmental and health applications. The sensor is immune to the presence of various interfering gases in ambient or expired air. The performance of the sensor in real-time breath-by-breath analysis has also been validated by a commercial CO2 detector. Furthermore, a 3D model was created to simulate fluid dynamics of breath and chemical reactions for CO2 assessment to achieve overall understanding of the breath CO2 detection process and further optimization of the device.

The mitigation and conversion of carbon dioxide (CO2) to more useful carbon chemicals is a research topic that is at the forefront of current engineering and sustainability applications. Direct photocatalytic reduction of CO2 with water (H2O) vapor to C1-C4 hydrocarbons has significant potential in setting substantial groundwork for meeting the increasing energy demands with minimal environmental impact. Previous studies indicate that titanium dioxide (TiO2) containing materials serve as the best photocatalyst for CO2 and H2O conversion to higher-value products. An understanding of the CO2-H2O reaction mechanism over TiO2 materials allows one to increase the yield of certain products such as carbon monoxide (CO) and methane (CH4). The basis of the work discussed in this thesis, investigates the interaction of small molecules (CO, CH4,H2O) over the least studied TiO2 polymorph - brookite. Using the Gaussian03 computational chemistry software package, density functional theory (DFT) calculations were performed to investigate the adsorption behavior of CO, H2O, and CH4 gases on perfect and oxygen-deficient brookite TiO2 (210) and anatase TiO2 (101) surfaces. The most geometrically and energetically favorable configurations of these molecules on the TiO2 surfaces were computed using the B3LYP/6-31+G(2df,p) functional/basis set. Calculations from this theoretical study indicate all three molecules adsorb more favorably onto the brookite TiO2 (210) surface. Diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS) was used to investigate the adsorption and desorption behavior of H2O and CH4 on Evonik P25 TiO2. Results from the experimental studies and theoretical work will serve as a significant basis for reaction prediction on brookite TiO2 surfaces.

The release of organophosphorus compounds (OPs) and subsequent exposure to these compounds is of concern to humans and the environment. The goal of this work was to control the concentrations of gaseous OPs through interaction with sorbent oxides. Experimental and computational methods were employed to assess the interactions of dimethyl phosphite (DMHP), dimethyl methylphosphonate (DMMP), dimethyl ethylphosphonate (DMEP), diethyl ethylphosphonate (DEEP), and triethyl phosphate (TEP) with amorphous silica (a-silica), ã-alumina, and monoclinic zirconia (m-zirconia) for applications in air pollution control. Interactions of the selected OPs with a-silica were chosen as a baseline to determine the applicability of the computational predictions. Based on the a-silica results, computational methods were deemed valid for predicting the trends among materials with comparable interactions (e.g. -OH functionality of a-silica interacting with the phosphonyl O atoms of the OPs). Computational evaluations of the interactions with the OPs were extended to the oxide material, m-zirconia, and compared with the results for ã-alumina. It was hypothesized that m-zirconia had the potential to provide for the effective sorption of OPs in a manner superior to that of the a-silica and the ã-alumina surfaces due to the surface charges of the zirconium Lewis acid sites when coordinated in the oxidized form. Based on the computational study, the predicted heats of adsorption for the selected OPs onto m-zirconia were more favorable than those that were predicted for ã-alumina and a-silica. Experimental studies were carried out to confirm these computational results. M-zirconia nanoparticles were synthesized to determine if the materials could be utilized for the adsorption of the selected OPs. M-zirconia was shown to adsorb the OPs, and the heats of adsorption were stronger than those determined for commercial samples of a-silica. However, water interfered with the adsorption of the OPs onto m-zirconia, thus leading to heats of adsorption that were much weaker than those predicted computationally. Nevertheless, this work provides a first investigation of m-zirconia as a viable sorbent material for the ambient control of the selected gaseous OPs. Additionally, this work represents the first comparative study between computational predictions and experimental determination of thermodynamic properties for the interactions of the selected OPs and oxide surfaces.