Biomedical Commons^™

System Design And Control Optimization For Neurorehabilitation Exoskeleton, Rodrigo N. Ramon

FIU Electronic Theses and Dissertations

Neurorehabilitation is a comprehensive approach aimed at helping patients regain motor control after a neural injury, including spinal cord injury, stroke, or other ischemic events. Early-stage neurorehabilitation is particularly delicate due to voluntary muscular weakness and lack of motor control, presenting in the form of spasticity. Unfortunately, this period of elevated weakness is when most neural control improvement can be made through a phenomenon called brain plasticity. Early rehabilitation traditionally requires a human therapist due to the adaptive and dynamic interpretation of undesired neuromuscular events. While efforts have been made to develop devices to aid in neurorehabilitation, the considerations that …

A Machine Learning Framework For Identifying Molecular Biomarkers From Transcriptomic Cancer Data, Md Abdullah Al Mamun

FIU Electronic Theses and Dissertations

Cancer is a complex molecular process due to abnormal changes in the genome, such as mutation and copy number variation, and epigenetic aberrations such as dysregulations of long non-coding RNA (lncRNA). These abnormal changes are reflected in transcriptome by turning oncogenes on and tumor suppressor genes off, which are considered cancer biomarkers.

However, transcriptomic data is high dimensional, and finding the best subset of genes (features) related to causing cancer is computationally challenging and expensive. Thus, developing a feature selection framework to discover molecular biomarkers for cancer is critical.

Traditional approaches for biomarker discovery calculate the fold change for each …

Volitional Control Of Lower-Limb Prosthesis With Vision-Assisted Environmental Awareness, S M Shafiul Hasan

FIU Electronic Theses and Dissertations

Early and reliable prediction of user’s intention to change locomotion mode or speed is critical for a smooth and natural lower limb prosthesis. Meanwhile, incorporation of explicit environmental feedback can facilitate context aware intelligent prosthesis which allows seamless operation in a variety of gait demands. This dissertation introduces environmental awareness through computer vision and enables early and accurate prediction of intention to start, stop or change speeds while walking. Electromyography (EMG), Electroencephalography (EEG), Inertial Measurement Unit (IMU), and Ground Reaction Force (GRF) sensors were used to predict intention to start, stop or increase walking speed. Furthermore, it was investigated whether …

Smart Motor Syringe System, Connor Wilson

Electrical Engineering

In this document a proof-of-concept design is developed and implementation to showcase the latest development in an ongoing effort to produce a series of automated syringe pumps.

Verification Of A Digital Microfluidics Platform, Karanpartap Singh

Electrical Engineering

The electrowetting effect describes the change in contact angle between a solid surface and electrolyte in response to an applied electric potential difference. Given a planar array of individually-actuated electrodes, electrowetting can be used to transport, mix, and separate picoliter to microliter-sized droplets of liquid on a dielectric layer. Applications of this phenomenon range from lab-on-a-chip and other microfluidic devices to liquid lenses capable of altering their topology and focus within milliseconds.

This project extends prior work simulating the dependence of droplet velocity on actuation voltage and demonstrates observed physics on a physical platform. The simulation portion of this project …

Hsp90 Inhibitors Modulate Sars-Cov-2 Spike Protein Subunit 1-Induced Human Pulmonary Microvascular Endothelial Activation And Barrier Dysfunction, Ruben Manuel Luciano Colunga Biancatelli, Pavel Solopov, Betsy W. Gregory, Yara Khodour, John D. Catravas

Bioelectrics Publications

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused more than 5 million deaths worldwide. Multiple reports indicate that the endothelium is involved during SARS-Cov-2-related disease (COVID-19). Indeed, COVID-19 patients display increased thrombophilia with arterial and venous embolism and lung microcapillary thrombotic disease as major determinants of deaths. The pathophysiology of endothelial dysfunction in COVID-19 is not completely understood. We have investigated the role of subunit 1 of the SARS-CoV-2 spike protein (S1SP) in eliciting endothelial barrier dysfunction, characterized dose and time relationships, and tested the hypothesis that heat shock protein 90 (HSP90) inhibitors would prevent and repair such injury. S1SP …

Integration Of Electrical Impedance Spectroscopy For Multichannel Cell Culture Measurement, Conard Chan

Master's Theses

ELECTROCHEMICAL IMPEDANCE SPECTROSCOPY (EIS) has been widely used to study the electrical properties of biological material due to its non-invasive nature and experimental reliability. However, most of the precision impedance analyzers used in EIS only provide single- or two-channel measurements which are inadequate for larger-scale multiplexed measurements, such as those found in modern microfluidic cell culture experiments. The Biomedical Microsystems Laboratory has developed a 16-channel cell culture platform with integrated electrode arrays for monitoring cell growth and electrical properties (i.e., the so-called “electrical phenotype”). In this paper, a system consisting of a 16-channel solid-state analog multiplexer (MUX)paired with a low-cost, …

Design And Fabrication Of A Low-Cost, Portable, Battery-Operated Surface Enhanced Raman Scattering (Sers) Optical Device, Blessing Adewumi

LSU Doctoral Dissertations

Raman Spectroscopy is a time-honored, non-invasive method for analyzing and identifying the molecular composition of materials. However, unenhanced Raman Spectroscopy has extremely low sensitivity which limits its sensing capability. SERS brings rough nano-metallic surfaces in contact with the material molecules to enormously enhance the Raman signals.

The sensitivity of SERS can be exploited in probe applications where the spectrometer needs to be brought near the specimen. For example, a long optical fiber coupled to a SERS device can be used to characterize and identify easy-to-reach cancerous tissues in organisms. Unfortunately, background signals in a long fiber can easily mask any …

Development Of A Dual-Mode Cmos Microelectrode Array For The Simultaneous Study Of Electrochemical And Electrophysiological Activities Of The Brain, Geoffrey Mulberry

Electronic Theses and Dissertations, 2020-

Medical diagnostic devices are in high demand due to increasing cases of neurodegenerative diseases in the aging population and pandemic outbreaks in our increasingly connected global community. Devices capable of detecting the presence of a disease in its early stages can have dramatic impacts on how it can be treated or eliminated. High cost and limited accessibility to diagnostic tools are the main barriers preventing potential patients from receiving a timely disease diagnosis. This dissertation presents several devices that are aimed at providing higher quality medical diagnostics at a low cost. Brain function is commonly studied with systems detecting the …

Mos2 Based Memristive Synapses For Neuromorphic Computing, Adithi Pandrahal Krishnaprasad Sharada

Electronic Theses and Dissertations, 2020-

Brain inspired computing enabled by memristors have gained prominence over the years due to its nano-scale footprint, reduced complexity for implementing synapses and neurons. Several demonstrations show two-dimensional (2D) materials as a promising platform for realization of robust and energy-efficient memristive synapses. Ideally, a synapse should exhibit low cycle-to-cycle (C-C) and device-to-device (D-D) variability along with high maximum /minimum conductance (Gmax/Gmin) ratio, linearity and symmetry in weight update for obtaining high learning accuracy in neural networks (NNs). However, the demonstration of neuromorphic circuits using conventional materials systems has been limited by high C-C and D-D variability and non-linearity in the …

Uncertainty Estimation In Classification Of Mgnt Using Radiogenomics For Glioblastoma Patients, W. Farzana, Z. A. Shboul, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Glioblastoma Multiforme (GBM) is one of the most malignant brain tumors among all high-grade brain cancers. Temozolomide (TMZ) is the first-line chemotherapeutic regimen for glioblastoma patients. The methylation status of the O6-methylguanine-DNA-methyltransferase (MGMT) gene is a prognostic biomarker for tumor sensitivity to TMZ chemotherapy. However, the standardized procedure for assessing the methylation status of MGMT is an invasive surgical biopsy, and accuracy is susceptible to resection sample and heterogeneity of the tumor. Recently, radio-genomics which associates radiological image phenotype with genetic or molecular mutations has shown promise in the non-invasive assessment of radiotherapeutic treatment. This study proposes a machine-learning framework …

Qu-Brats: Miccai Brats 2020 Challenge On Quantifying Uncertainty In Brain Tumor Segmentation - Analysis Of Ranking Scores And Benchmarking Results, Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard Mckinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil Nalawade, Chandan Ganesh, Ben Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Daza, Catalina Gómez, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Reynaud, Yuan-Han Mo, Elsa Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Lin-Min Pei, Murat Ak, Sarahi Rosas-González, Ilyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Veronica Vilaplana, Hugh Mchugh, Gonzalo Maso Talou, Alan Wang, Jay Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicholas Boutry, Alexis Huard, Lasitha Vidyaratne, Md. Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Elodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Llado, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas Tustison, Craig Meyer, Nisarg A. Shah, Sanjay Talbar, Marc-André Weber, Abhishek Mahajan, Andras Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko1, Daniel Marcus, Aikaterini Kotrotsou, Rivka Colen, John Freymann, Justin Kirby, Christos Davatzikos, Bjoern Menze, Spyridon Bakas, Yarin Gal, Tal Arbel

Electrical & Computer Engineering Faculty Publications

Deep learning (DL) models have provided the state-of-the-art performance in a wide variety of medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e.g., tumor and lesion sub-regions) is particularly challenging, and potential errors hinder the translation of DL models into clinical workflows. Quantifying the reliability of DL model predictions in the form of uncertainties, could enable clinical review of the most uncertain regions, thereby building trust and paving the way towards clinical translation. Recently, a number of uncertainty estimation methods have been introduced for DL medical image segmentation tasks. …

Radiomic Texture Feature Descriptor To Distinguish Recurrent Brain Tumor From Radiation Necrosis Using Multimodal Mri, M. S. Sadique, A. Temtam, E. Lappinen, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Despite multimodal aggressive treatment with chemo-radiation-therapy, and surgical resection, Glioblastoma Multiforme (GBM) may recur which is known as recurrent brain tumor (rBT), There are several instances where benign and malignant pathologies might appear very similar on radiographic imaging. One such illustration is radiation necrosis (RN) (a moderately benign impact of radiation treatment) which are visually almost indistinguishable from rBT on structural magnetic resonance imaging (MRI). There is hence a need for identification of reliable non-invasive quantitative measurements on routinely acquired brain MRI scans: pre-contrast T1-weighted (T1), post-contrast T1-weighted (T1Gd), T2-weighted (T2), and T2 Fluid Attenuated Inversion Recovery (FLAIR) that can …

Speaker Encoding For Zero-Shot Speech Synthesis, Tristin W. Cory

MSU Graduate Theses

Spoken communication, for many, is an essential part of everyday life. Some individuals can lose or not be born with the ability to speak. To function on a day-to-day basis, these individuals find other ways of communication. Adaptive speech synthesis is one of those ways. It recreates a user’s previous voice or creates a voice that blends with their regional dialect. Current adaptive speech synthesis techniques that achieve human-like speech require thirty minutes, to a few hours of high-quality audio recordings of a target speaker. This amount of recorded audio is not commonly possessed by people in need of a …

Flexible Microfluidic Device With Nonplanar Interdigitated Microelectrodes, Saud Alssaidy

Theses

The lab-on-a-chip concept has improved significantly in recent years to meet global demand for various applications with the advent of new technologies. Much progress has been achieved, but many microfluidic devices still suffer from design limitations in terms of sensitivity and selectivity because they use rigid, fragile substrate materials and conventional electrodes, which do not provide high sensitivity or selectivity and suffer from signal-to-noise ratio issues. This work proposes a novel device architecture that uses flexible, transparent top and bottom layers integrated with (nonplanar interdigitated microelectrodes) to create a sandwich-like flexible substrate base. The top and bottom layers consist of …

Design And Implementation Of Real-Time Health Vital Sign Monitoring Device With Wireless Sensor-Based On Arduino Mega, Bekti Wulandari, Mentari Putri Jati

Elinvo (Electronics, Informatics, and Vocational Education)

This paper discusses the realization of vital sign monitoring devices and knowing their performance. This device is expected to assist medical personnel in measuring and monitoring vital signs without having to have physical contact with patients. The design phase of the patient's vital sign monitoring device with an Arduino Mega-based wireless sensor starts from the identification, needs analysis, design, manufacture, troubleshoot, and testing. Arduino Mega and ESP8266 as the main components that function for the controller and upload data to the server. Then MAX30100, DS18B20, and MPX5700AP sensors which function to detect the vital sign. Android smartphones are used to …

Effect Of Levodopa On Eeg Connectivity In Parkinson's Patients, Sepehr Torab Parhiz

Electronic Thesis and Dissertation Repository

Levodopa is a dopamine replacement medication administered to patients with Parkinson’s disease (PD) to alleviate their motor symptoms. However, its long-term use can cause adverse side effects, including involuntary motor movements. We studied 16 PD patients before and after taking Levodopa based on resting-state electroencephalography (EEG) recordings to determine how Levodopa affects the functional connectivity of their brain networks. We used several metrics from graph theory, in particular the minimum spanning tree (MST) metric, and analyzed how they change after subjects take Levodopa. We observed significant changes in the lower alpha band toward a more path-like and less globally efficient …

Methods For Inference And Analysis Of Gene Networks From Rna Sequencing Data, Himangi Srivastava

Theses and Dissertations

RNA (Ribonuceic Acid) sequencing technology is a powerful technology used to give re- searchers essential information about the functionality of genes. The transcriptomic study and downstream analysis highlight the functioning of the genes associated with a specific biological process/treatment. In practice, differentially expressed genes associated with a particular treatment or genotype are subjected to downstream analysis to find some critical set of genes. This critical set of genes/ genes pathways infers the effect of the treatment in a cell or tissue. This disserta- tion describes the multiple stages framework of finding these critical sets of genes using different analysis methodologies …

Anglo-American Nursing: A Historical Timeline Of The Field From The Renaissance To World War Ii, Carlyn Homann

Honors Projects

This timeline stands as an extensive- although not comprehensive- review of the evolution of Anglo-American nursing as a profession, but it will also explore the contributions of other nations where it is appropriate. It seeks to summarize the field and its limitations from the early 15th century to World War II, as well as the capability for upward movement within an existing hierarchy while also considering the education required of a nurse during the selected time period in order to provide context for current nursing students.

Hiv/Aids After The Crisis: The Evolution Of An Epidemic, Emma Paras

Honors Projects

HIV and AIDS has affected the world for over four decades. In the past, a positive HIV diagnosis could very well be a death sentence, as well as signal that an individual was a social outcast. In the past ten years, however, treatments for HIV/AIDS allow a person to live a long and relatively healthy life. In addition to examining current and future trends in HIV treatment, this paper will also discuss how the virus affects different regions of the world. Particularly in certain parts of Africa, HIV/AIDS remains deadly for many who don’t have proper access to health care …