Matching Items (28)
Description
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.
ContributorsGhorband, Vishal (Author) / Blain Christen, Jennifer (Thesis advisor) / Song, Hongjiang (Committee member) / LaBelle, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2016
Description
This work explores how flexible electronics and display technology can be applied to develop new biomedical devices for medical, biological, and life science applications. It demonstrates how new biomedical devices can be manufactured by only modifying or personalizing the upper layers of a conventional thin film transistor (TFT) display process. This personalization was applied first to develop and demonstrate the world's largest flexible digital x-ray detector for medical and industrial imaging, and the world's first flexible ISFET pH biosensor using TFT technology. These new, flexible, digital x-ray detectors are more durable than conventional glass substrate x-ray detectors, and also can conform to the surface of the object being imaged. The new flexible ISFET pH biosensors are >10X less expensive to manufacture than comparable CMOS-based ISFETs and provide a sensing area that is orders of magnitude larger than CMOS-based ISFETs. This allows for easier integration with area intensive chemical and biological recognition material as well as allow for a larger number of unique recognition sites for low cost multiple disease and pathogen detection.
The flexible x-ray detector technology was then extended to demonstrate the viability of a new technique to seamlessly combine multiple smaller flexible x-ray detectors into a single very large, ultimately human sized, composite x-ray detector for new medical imaging applications such as single-exposure, low-dose, full-body digital radiography. Also explored, is a new approach to increase the sensitivity of digital x-ray detectors by selectively disabling rows in the active matrix array that are not part of the imaged region. It was then shown how high-resolution, flexible, organic light-emitting diode display (OLED) technology can be used to selectively stimulate and/or silence small groups of neurons on the cortical surface or within the deep brain as a potential new tool to diagnose and treat, as well as understand, neurological diseases and conditions. This work also explored the viability of a new miniaturized high sensitivity fluorescence measurement-based lab-on-a-chip optical biosensor using OLED display and a-Si:H PiN photodiode active matrix array technology for point-of-care diagnosis of multiple disease or pathogen biomarkers in a low cost disposable configuration.
The flexible x-ray detector technology was then extended to demonstrate the viability of a new technique to seamlessly combine multiple smaller flexible x-ray detectors into a single very large, ultimately human sized, composite x-ray detector for new medical imaging applications such as single-exposure, low-dose, full-body digital radiography. Also explored, is a new approach to increase the sensitivity of digital x-ray detectors by selectively disabling rows in the active matrix array that are not part of the imaged region. It was then shown how high-resolution, flexible, organic light-emitting diode display (OLED) technology can be used to selectively stimulate and/or silence small groups of neurons on the cortical surface or within the deep brain as a potential new tool to diagnose and treat, as well as understand, neurological diseases and conditions. This work also explored the viability of a new miniaturized high sensitivity fluorescence measurement-based lab-on-a-chip optical biosensor using OLED display and a-Si:H PiN photodiode active matrix array technology for point-of-care diagnosis of multiple disease or pathogen biomarkers in a low cost disposable configuration.
ContributorsSmith, Joseph T. (Author) / Allee, David (Thesis advisor) / Goryll, Michael (Committee member) / Kozicki, Michael (Committee member) / Blain Christen, Jennifer (Committee member) / Couture, Aaron (Committee member) / Arizona State University (Publisher)
Created2014
Description
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.
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.
ContributorsTipparaju, Vishal Varun (Author) / Xian, Xiaojun (Thesis advisor) / Forzani, Erica (Thesis advisor) / Blain Christen, Jennifer (Committee member) / Angadi, Siddhartha (Committee member) / Arizona State University (Publisher)
Created2020
Description
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.
ContributorsNanda, Tanya (Author) / Rege, Kaushal (Thesis advisor) / Blain Christen, Jennifer (Committee member) / Weaver, Jessica (Committee member) / Arizona State University (Publisher)
Created2020
Description
Quantifying molecular interactions is critical to the understanding of many biological processes and drug screening. To date, various detection techniques have been developed to determine the binding kinetics. However, because most of the mainstream detection technologies detect signals that scale with the mass of ligands bond to the sensor surface, it is still challenging to quantify the binding kinetics of small molecules. To address this problem, two different detection technologies, charge-sensitive optical detection (CSOD) and critical angle reflection (CAR), are developed for label-free detection of molecular interactions with the ability to detect a wide range of molecules including small molecules. In particular, CSOD technique detects the charge rather than the mass of a molecule with an optical fiber. However, the effective charge of a molecule decreases with the buffer ionic strength. For this reason, the previous CSOD works with diluted buffers, which could affect the measured molecular binding kinetics. Here a technique capable of detecting molecular binding kinetics in normal ionic strength buffers is presented. An H-shaped sample well was developed to overcome this problem. With this new design, the binding kinetics between G-protein-coupled receptors (GPCRs) and their small molecule ligands were measured in normal buffer. To further improve the signal-to-noise ratio of CSOD and move it toward high-throughput detection, CSOD was implemented with a quadrant-cell detector to achieve detection in higher frequency range and decrease low-frequency noise.This improved CSOD technique is capable for direct quantification of binding kinetics of phage-displayed peptides to their target protein using the whole phages. CAR imaging can be performed on surface plasmon resonance (SPR) imaging setups. It was shown that CAR is capable of measuring molecular interactions including proteins, nucleic acids and cell-based detections. In addition, it was shown that CAR can detect small molecule bindings and intracellular signals beyond SPR sensing limit. CAR exhibits several distinct characteristics over SPR, including tunable sensitivity and dynamic range, deeper vertical sensing range, and fluorescence compatibility. CAR is anticipated to have the ability to expand SPR capability in small molecule detection, whole cell-based detection, simultaneous fluorescence imaging, and broader conjugation chemistry.
ContributorsLiang, Runli (Author) / Wang, Shaopeng (Thesis advisor) / Blain Christen, Jennifer (Thesis advisor) / Jing, Tianwei (Committee member) / Wang, Chao (Committee member) / Arizona State University (Publisher)
Created2021
Description
Cameras have become commonplace with wide-ranging applications of phone photography, computer vision, and medical imaging. With a growing need to reduce size and costs while maintaining image quality, the need to look past traditional style of cameras is becoming more apparent. Several non-traditional cameras have shown to be promising options for size-constraint applications, and while they may offer several advantages, they also usually are limited by image quality degradation due to optical or a need to reconstruct a captured image. In this thesis, we take a look at three of these non-traditional cameras: a pinhole camera, a diffusion-mask lensless camera, and an under-display camera (UDC).
For each of these cases, I present a feasible image restoration pipeline to correct for their particular limitations. For the pinhole camera, I present an early pipeline to allow for practical pinhole photography by reducing noise levels caused by low-light imaging, enhancing exposure levels, and sharpening the blur caused by the pinhole. For lensless cameras, we explore a neural network architecture that performs joint image reconstruction and point spread function (PSF) estimation to robustly recover images captured with multiple PSFs from different cameras. Using adversarial learning, this approach achieves improved reconstruction results that do not require explicit knowledge of the PSF at test-time and shows an added improvement in the reconstruction model’s ability to generalize to variations in the camera’s PSF. This allows lensless cameras to be utilized in a wider range of applications that require multiple cameras without the need to explicitly train a separate model for each new camera. For UDCs, we utilize a multi-stage approach to correct for low light transmission, blur, and haze. This pipeline uses a PyNET deep neural network architecture to perform a majority of the restoration, while additionally using a traditional optimization approach which is then fused in a learned manner in the second stage to improve high-frequency features. I show results from this novel fusion approach that is on-par with the state of the art.
For each of these cases, I present a feasible image restoration pipeline to correct for their particular limitations. For the pinhole camera, I present an early pipeline to allow for practical pinhole photography by reducing noise levels caused by low-light imaging, enhancing exposure levels, and sharpening the blur caused by the pinhole. For lensless cameras, we explore a neural network architecture that performs joint image reconstruction and point spread function (PSF) estimation to robustly recover images captured with multiple PSFs from different cameras. Using adversarial learning, this approach achieves improved reconstruction results that do not require explicit knowledge of the PSF at test-time and shows an added improvement in the reconstruction model’s ability to generalize to variations in the camera’s PSF. This allows lensless cameras to be utilized in a wider range of applications that require multiple cameras without the need to explicitly train a separate model for each new camera. For UDCs, we utilize a multi-stage approach to correct for low light transmission, blur, and haze. This pipeline uses a PyNET deep neural network architecture to perform a majority of the restoration, while additionally using a traditional optimization approach which is then fused in a learned manner in the second stage to improve high-frequency features. I show results from this novel fusion approach that is on-par with the state of the art.
ContributorsRego, Joshua D (Author) / Jayasuriya, Suren (Thesis advisor) / Blain Christen, Jennifer (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2020
Description
Point-of-care molecular diagnostics can provide efficient and cost-effective medical care, and they have the potential to fundamentally change our approach to global health. However, most existing approaches are not scalable to include multiple biomarkers. As a solution, we have combined commercial flat panel OLED display technology with protein microarray technology to enable high-density fluorescent, programmable, multiplexed biorecognition in a compact and disposable configuration with clinical-level sensitivity. Our approach leverages advances in commercial display technology to reduce pre-functionalized biosensor substrate costs to pennies per cm[superscript 2]. Here, we demonstrate quantitative detection of IgG antibodies to multiple viral antigens in patient serum samples with detection limits for human IgG in the 10 pg/mL range. We also demonstrate multiplexed detection of antibodies to the HPV16 proteins E2, E6, and E7, which are circulating biomarkers for cervical as well as head and neck cancers.
ContributorsKatchman, Benjamin (Author) / Smith, Joseph (Author) / Obahiagbon, Uwadiae (Author) / Kesiraju, Sailaja (Author) / Lee, Yong Kyun (Author) / O'Brien, Barry (Author) / Kaftanoglu, Korhan (Author) / Blain Christen, Jennifer (Author) / Anderson, Karen (Author) / Biodesign Institute (Contributor)
Created2016-07-04
Description
Engineered nanoporous substrates made using materials such as silicon nitride or silica have been demonstrated to work as particle counters or as hosts for nano-lipid bilayer membrane formation. These mechanically fabricated porous structures have thicknesses of several hundred nanometers up to several micrometers to ensure mechanical stability of the membrane. However, it is desirable to have a three-dimensional structure to ensure increased mechanical stability. In this study, circular silica shells used from Coscinodiscus wailesii, a species of diatoms (unicellular marine algae) were immobilized on a silicon chip with a micrometer-sized aperture using a UV curable polyurethane adhesive. The current conducted by a single nanopore of 40 nm diameter and 50 nm length, during the translocation of a 27 nm polystyrene sphere was simulated using COMSOL multiphysics and tested experimentally. The current conducted by a single 40 nm diameter nanopore of the diatom shell during the translocation of a 27 nm polystyrene sphere was simulated using COMSOL Multiphysics (28.36 pA) and was compared to the experimental measurement (28.69 pA) and Coulter Counting theory (29.95 pA).In addition, a mobility of 1.11 x 10-8 m2s-1V-1 for the 27 nm polystyrene spheres was used to convert the simulated current from spatial dependence to time dependence.
To achieve a sensing diameter of 1-2 nanometers, the diatom shells were used as substrates to perform ion-channel reconstitution experiments. The immobilized diatom shell was functionalized using silane chemistry and lipid bilayer membranes were formed. Functionalization of the diatom shell surface improves bilayer formation probability from 1 out of 10 to 10 out of 10 as monitored by impedance spectroscopy. Self-insertion of outer membrane protein OmpF of E.Coli into the lipid membranes could be confirmed using single channel recordings, indicating that nano-BLMs had formed which allow for fully functional porin activity. The results indicate that biogenic silica nanoporous substrates can be simulated using a simplified two dimensional geometry to predict the current when a nanoparticle translocates through a single aperture. With their tiered three-dimensional structure, diatom shells can be used in to form nano-lipid bilayer membranes and can be used in ion-channel reconstitution experiments similar to synthetic nanoporous membranes.
To achieve a sensing diameter of 1-2 nanometers, the diatom shells were used as substrates to perform ion-channel reconstitution experiments. The immobilized diatom shell was functionalized using silane chemistry and lipid bilayer membranes were formed. Functionalization of the diatom shell surface improves bilayer formation probability from 1 out of 10 to 10 out of 10 as monitored by impedance spectroscopy. Self-insertion of outer membrane protein OmpF of E.Coli into the lipid membranes could be confirmed using single channel recordings, indicating that nano-BLMs had formed which allow for fully functional porin activity. The results indicate that biogenic silica nanoporous substrates can be simulated using a simplified two dimensional geometry to predict the current when a nanoparticle translocates through a single aperture. With their tiered three-dimensional structure, diatom shells can be used in to form nano-lipid bilayer membranes and can be used in ion-channel reconstitution experiments similar to synthetic nanoporous membranes.
ContributorsRamakrishnan, Shankar (Author) / Goryll, Michael (Thesis advisor) / Blain Christen, Jennifer (Committee member) / Dey, Sandwip (Committee member) / Thornton, Trevor (Committee member) / Arizona State University (Publisher)
Created2015