Engineering Commons^™

Graphene-Conductive Polymer-Based Electrochemical Sensor For Dopamine Detection, Dipannita Ghosh, Md Ashiqur Rahman, Ali Ashraf, Nazmul Islam

Electrical and Computer Engineering Faculty Publications and Presentations

The central nervous system's (CNS) dopaminergic system dysfunction has been linked to neurological illnesses like schizophrenia and Parkinson's disease. As a result, sensitive and selective detection of dopamine is critical for the early diagnosis of illnesses associated with aberrant dopamine levels. In this research, we have investigated the performance of electrochemical screen-printed sensors for different concentrations of dopamine detection using graphene-based conductive PEDOT: PSS(G-PEDOT: PSS) and Polyaniline(GPANI) inks on the working electrode and compared the sensitivity. SEM characterization technique has been performed to visualize the microstructures of the proposed inks. We have investigated cyclic voltammetry (CV) electrochemical techniques with ferri/ferrocyanide …

Failure Detection In Deep Neural Networks For Medical Imaging, Sabeen Ahmed, Dimah Dera, Saud Ul Hassan, Nidhal Bouaynaya, Ghulam Rasool

Electrical and Computer Engineering Faculty Publications and Presentations

Deep neural networks (DNNs) have started to find their role in the modern healthcare system. DNNs are being developed for diagnosis, prognosis, treatment planning, and outcome prediction for various diseases. With the increasing number of applications of DNNs in modern healthcare, their trustworthiness and reliability are becoming increasingly important. An essential aspect of trustworthiness is detecting the performance degradation and failure of deployed DNNs in medical settings. The softmax output values produced by DNNs are not a calibrated measure of model confidence. Softmax probability numbers are generally higher than the actual model confidence. The model confidence-accuracy gap further increases for …

An Inkjet Printed Flexible Electrocorticography (Ecog) Microelectrode Array On A Thin Parylene-C Film, Yoontae Kim, Stella Alimperti, Paul Choi, Moses Noh

Electrical and Computer Engineering Faculty Publications and Presentations

Electrocorticography (ECoG) is a conventional, invasive technique for recording brain signals from the cortical surface using an array of electrodes. In this study, we developed a highly flexible 22-channel ECoG microelectrode array on a thin Parylene film using novel fabrication techniques. Narrow (<40 >µm) and thin (<500 >nm) microelectrode patterns were first printed on PDMS, then the patterns were transferred onto Parylene films via vapor deposition and peeling. A custom-designed, 3D-printed connector was built and assembled with the Parylene-based flexible ECoG microelectrode array without soldering. The impedance of the assembled ECoG electrode array was measured in vitro by electrochemical impedance …

Self-Learned Kernel Low Rank Approach To Accelerated High Resolution 3d Diffusion Mri, Abhijit Baul, Nian Wang, Choyi Zhang, Yuchou Chang, Leslie Ying, Yuchou Chang, Ukash Nakarmi

Electrical and Computer Engineering Faculty Publications and Presentations

Diffusion Magnetic Resonance Imaging (dMRI) is a promising method to analyze the subtle changes in the tissue structure. However, the lengthy acquisition time is a major limitation in the clinical application of dMRI. Different image acquisition techniques such as parallel imaging, compressed sensing, has shortened the prolonged acquisition time but creating high-resolution 3D dMRI slices still requires a significant amount of time. In this study, we have shown that high resolution 3D dMRI can be reconstructed from the highly undersampled k-space and q-space data using a Kernel Low Rank method. Our proposed method has outperformed the conventional CS methods in …

A Compendium Of Single Cell Analysis In Aging And Disease, Uday Chintapula, Samir M. Iqbal, Young-Tae Kim

Electrical and Computer Engineering Faculty Publications and Presentations

Cell is the fundamental structural and functional unit of complex multicellular organisms. Conventional methods which involve average analysis of cells in bulk populations can undermine physiologically significant cell populations, whereas analysis of cells at a single cell level may reveal unique biomarkers and other mechanisms that govern the genotype and phenotype in various physiological processes in presumed homogenous cell populations. Cellular abnormalities such as irregularities in cellular mechanisms have been linked to human aging and other major diseases including neurodegenerative, vascular, autoimmune, and cancer. Aging is a functional decline associated with various diseases in an organism, majorly arising from cellular …

Ion-Sensitive Field-Effect Transistors With Micropillared Gates For Measuring Cell Ion Exchange At Molecular Levels, Mohammad G. Abdallah, Rayan Khan, Christian Garcia, Young-Tae Kim, Samir M. Iqbal

Electrical and Computer Engineering Faculty Publications and Presentations

The detection of small concentrations of cancer cells before cancer takes over the primary organ completely, or metastasizes to other areas of the body is important for early screening of cancer. One approach to address cancer early screening is through cell ion exchange bioelectricity, which characterizes voltage potential in non-neuronal cells to regulate shape changing, proliferation, differentiation, migration, and cancer formation. Herein, novel ion-sensitive field-effective transistor (ISFET) modality is shown to measure cell behavior during the change of cell properties at molecular levels. ISFETs produce low resistance signals and consume low power. The small size of ISFETs enables miniature diagnosis …

Optical Imaging Of Finger For Blood Pressure Monitoring Of The Driver, Mohammad Motasim Bellah, Mohammad Raziul Hasan, Samir M. Iqbal

Electrical and Computer Engineering Faculty Publications and Presentations

Cardiovascular diseases (CVDs) are number one reason for human mortality around the world (Fig. 1) [1]. Pulse pressure (PP) and pulse rate (PR) are considered as the two most vital physiological markers for CVDs like myocardial infarction, cardiac arrhythmia, and heart failure. Currently, long-term PP and PR analysis is not possible due to the lack of systems that can frequently measure the data over a period of time. Motor vehicle drivers with known CVDs are at higher risk due to traffic air pollution.

This paper presents our work on an inexpensive and readily deployable approach that keeps track of PP …