Biomedical Engineering and Bioengineering Commons^™

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 …

Development Of A Real-Time Single-Lead Single-Beat Frequency-Independent Myocardial Infarction Detector, Harold Martin

FIU Electronic Theses and Dissertations

The central aim of this research is the development and deployment of a novel multilayer machine learning design with unique application for the diagnosis of myocardial infarctions (MIs) from individual heartbeats of single-lead electrocardiograms (EKGs) irrespective of their sampling frequencies over a given range. To the best of our knowledge, this design is the first to attempt inter-patient myocardial infarction detection from individual heartbeats of single-lead (lead II) electrocardiograms that achieves high accuracy and near real-time diagnosis. The processing time of 300 milliseconds to a diagnosis is just at the time range in between extremely fast heartbeats of around 300 …

Correlating The Effect Of Dynamic Variability In The Sensor Environment On Sensor Design, Pulak Bhushan

FIU Electronic Theses and Dissertations

This dissertation studies the effect of biofluid dynamics on the electrochemical response of a wearable sensor for monitoring of chronic wounds. The research investigates various dynamic in vivo parameters and correlates them with experimentally measured behavior with wound monitoring as a use case. Wearable electrochemical biosensors suffer from several unaddressed challenges, like stability and sensitivity, that need to be resolved for obtaining accurate data. One of the major challenges in the use of these sensors is continuous variation in biofluid composition. Wound healing is a dynamic process with wound composition changing continuously. This dissertation investigates the effects of several in …

Engineering Electromagnetic Systems For Next-Generation Brain-Machine Interface, Brayan Ricardo Navarrete

FIU Electronic Theses and Dissertations

MagnetoElectric Nanoparticles (MENPs) are known to be a powerful tool for a broad range of applications spanning from medicine to energy-efficient electronics. MENPs allow to couple intrinsic electric fields in the nervous system with externally controlled magnetic fields. This thesis exploited MENPs to achieve contactless brain-machine interface (BMIs). Special electromagnetic devices were engineered for controlling the MENPs’ magnetoelectric effect to enable stimulation and recording. The most important engineering breakthroughs of the study are summarized below.

(I) Metastable Physics to Localize Nanoparticles: One of the main challenges is to localize the nanoparticles at any selected site(s) in the brain. The fundamental …

Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang

FIU Electronic Theses and Dissertations

Alzheimer’s disease (AD) is the most common form of dementia affecting 10% of the population over the age of 65 and the growing costs in managing AD are estimated to be $259 billion, according to data reported in the 2017 by the Alzheimer's Association. Moreover, with cognitive decline, daily life of the affected persons and their families are severely impacted. Taking advantage of the diagnosis of AD and its prodromal stage of mild cognitive impairment (MCI), an early treatment may help patients preserve the quality of life and slow the progression of the disease, even though the underlying disease cannot …

Enhanced Surface Electrical Neurostimulation (Esens): A Non-Invasive Platform For Peripheral Neuromodulation, Andres Eduardo Pena

FIU Electronic Theses and Dissertations

Electrical stimulation of peripheral afferents has been used to study the sensory neural code and restore lost sensory function after amputation. Recently, implantable neural interfaces have prompted multiple breakthroughs in artificial somatosensory feedback for individuals with amputation, resulting in functional and psychological benefits. Although promising, the invasive nature of these approaches limits wide clinical applications, hindering the development of advanced neuromodulation strategies for intuitive sensory feedback. Transcutaneous (surface) stimulation is a potential non-invasive alternative. However, traditional surface stimulation methods are hampered by inadequate electrode and stimulation parameter fitting, localized discomfort, poor selectivity, and limited percept modulation.

An enhanced surface electrical …

Connectivity Analysis Of Electroencephalograms In Epilepsy, Panuwat Janwattanapong

FIU Electronic Theses and Dissertations

This dissertation introduces a novel approach at gauging patterns of informa- tion flow using brain connectivity analysis and partial directed coherence (PDC) in epilepsy. The main objective of this dissertation is to assess the key characteristics that delineate neural activities obtained from patients with epilepsy, considering both focal and generalized seizures. The use of PDC analysis is noteworthy as it es- timates the intensity and direction of propagation from neural activities generated in the cerebral cortex, and it ascertains the coefficients as weighted measures in formulating the multivariate autoregressive model (MVAR). The PDC is used here as a feature extraction …

Multivariate Analysis For The Quantification Of Transdermal Volatile Organic Compounds In Humans By Proton Exchange Membrane Fuel Cell System, Ahmed Hasnain Jalal

FIU Electronic Theses and Dissertations

In this research, a proton exchange membrane fuel cell (PEMFC) sensor was investigated for specific detection of volatile organic compounds (VOCs) for point-of-care (POC) diagnosis of the physiological conditions of humans. A PEMFC is an electrochemical transducer that converts chemical energy into electrical energy. A Redox reaction takes place at its electrodes whereas the volatile biomolecules (e.g. ethanol) are oxidized at the anode and ambient oxygen is reduced at the cathode. The compounds which were the focus of this investigation were ethanol (C₂H₅OH) and isoflurane (C₃H₂ClF₅O), but theoretically, the sensor …

Brain Connectivity Networks For The Study Of Nonlinear Dynamics And Phase Synchrony In Epilepsy, Hoda Rajaei

FIU Electronic Theses and Dissertations

Assessing complex brain activity as a function of the type of epilepsy and in the context of the 3D source of seizure onset remains a critical and challenging endeavor. In this dissertation, we tried to extract the attributes of the epileptic brain by looking at the modular interactions from scalp electroencephalography (EEG). A classification algorithm is proposed for the connectivity-based separation of interictal epileptic EEG from normal. Connectivity patterns of interictal epileptic discharges were investigated in different types of epilepsy, and the relation between patterns and the epileptogenic zone are also explored in focal epilepsy.

A nonlinear recurrence-based method is …

Quantitative Yttrium-90 Bremsstrahlung Spect/Ct And Pet/Ct Study For 3d Dosimetry In Radiomicrosphere Therapy, Senait Aknaw Debebe

FIU Electronic Theses and Dissertations

Liver cancer ranks the third most common cause of cancer related mortality worldwide. Radiomicrosphere therapy (RMT), a form of radiation therapy, involves administration of Yttrium-90 (90Y) microspheres to the liver via the hepatic artery. 90Y microspheres bremsstrahlung SPECT/CT or PET/CT imaging could potentially identify an extrahepatic uptake. An early detection of such an uptake, thus, could initiate preventative measures early on. However, the quantitative accuracy of bremsstrahlung SPECT/CT images is limited by the wide and continuous energy spectrum of 90Y bremsstrahlung photons. 90Y PET/CT imaging is also possible but limited by the extremely small internal pair production decay. These limitation …

A Biologically Plausible Supervised Learning Method For Spiking Neurons With Real-World Applications, Lilin Guo

FIU Electronic Theses and Dissertations

Learning is central to infusing intelligence to any biologically inspired system. This study introduces a novel Cross-Correlated Delay Shift (CCDS) learning method for spiking neurons with the ability to learn and reproduce arbitrary spike patterns in a supervised fashion with applicability tospatiotemporalinformation encoded at the precise timing of spikes. By integrating the cross-correlated term,axonaland synapse delays, the CCDS rule is proven to be both biologically plausible and computationally efficient. The proposed learning algorithm is evaluated in terms of reliability, adaptive learning performance, generality to different neuron models, learning in the presence of noise, effects of its learning parameters and classification …

Nanofabrication And Spectroscopy Of Magnetic Nanostructures Using A Focused Ion Beam, Ali Hadjikhani

FIU Electronic Theses and Dissertations

This research used a focused ion beam in order to fabricate record small nano-magnetic structures, investigate the properties of magnetic materials in the rarely studied range of nanometer size, and exploit their extraordinary characteristics in medicine and nano-electronics. This study consists of two parts: (i) Fabrication and study of record small magnetic tunnel junctions (ii) Introduction of a novel method for detection of magnetoelectric nanoparticles (MENs) in the tissue.

A key challenge in further scaling of CMOS devices is being able to perform non-volatile logic with near zero power consumption. Sub-10-nm nanomagnetic spin transfer torque (STT) magnetic tunneling junctions (MTJs) …

Cobalt Ferrite Nanoparticles Fabricated Via Co-Precipitation In Air: Overview Of Size Control And Magnetic Properties, Dennis Toledo

FIU Electronic Theses and Dissertations

Cobalt Ferrite has important, size-dependent magnetic properties. Consequently, an overview of particle size is important. Co-precipitation in air was the fabrication method used because it is comparatively simple and safe. The effects of three different reaction times including 1, 2, 3 hour(s) on particle size were compared. Also, the effectiveness of three different capping agents (Oleic Acid, Polyvinylpyrollidone (PVP), and Trisodium Citrate) in reducing aggregation and correspondingly particle size were examined. Using Welch’s analysis of variance (ANOVA) and the relevant post hoc tests, there was no significant difference (p=0.05) between reaction times of 1 hour and 2 hours, but there …

Development Of A Lab-On-A-Chip Device For Rapid Nanotoxicity Assessment In Vitro, Pratikkumar Shah

FIU Electronic Theses and Dissertations

Increasing useof nanomaterials in consumer products and biomedical applications creates the possibilities of intentional/unintentional exposure to humans and the environment. Beyond the physiological limit, the nanomaterialexposure to humans can induce toxicity. It is difficult to define toxicity of nanoparticles on humans as it varies by nanomaterialcomposition, size, surface properties and the target organ/cell line. Traditional tests for nanomaterialtoxicity assessment are mostly based on bulk-colorimetric assays. In many studies, nanomaterials have found to interfere with assay-dye to produce false results and usually require several hours or days to collect results. Therefore, there is a clear need for alternative tools that can …

A Novel Signal Processing Method For Intraoperative Neurophysiological Monitoring In Spinal Surgeries, Krishnatej Vedala

FIU Electronic Theses and Dissertations

Intraoperative neurophysiologic monitoring is an integral part of spinal surgeries and involves the recording of somatosensory evoked potentials (SSEP). However, clinical application of IONM still requires anywhere between 200 to 2000 trials to obtain an SSEP signal, which is excessive and introduces a significant delay during surgery to detect a possible neurological damage. The aim of this study is to develop a means to obtain the SSEP using a much less, twelve number of recordings. The preliminary step involved was to distinguish the SSEP with the ongoing brain activity. We first establish that the brain activity is indeed quasi-stationary whereas …

Network Construction And Graph Theoretical Analysis Of Functional Language Networks In Pediatric Epilepsy, Anas Salah Eddin

FIU Electronic Theses and Dissertations

This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ …

Bionano Electronics: Magneto-Electric Nanoparticles For Drug Delivery, Brain Stimulation And Imaging Applications, Rakesh Guduru

FIU Electronic Theses and Dissertations

Nanoparticles are often considered as efficient drug delivery vehicles for precisely dispensing the therapeutic payloads specifically to the diseased sites in the patient’s body, thereby minimizing the toxic side effects of the payloads on the healthy tissue. However, the fundamental physics that underlies the nanoparticles’ intrinsic interaction with the surrounding cells is inadequately elucidated. The ability of the nanoparticles to precisely control the release of its payloads externally (on-demand) without depending on the physiological conditions of the target sites has the potential to enable patient- and disease-specific nanomedicine, also known as Personalized NanoMedicine (PNM). In this dissertation, magneto-electric nanoparticles (MENs) …

Electrochemical Immunosensing Of Cortisol In An Automated Microfluidic System Towards Point-Of-Care Applications, Abhay Vasudev

FIU Electronic Theses and Dissertations

This dissertation describes the development of a label-free, electrochemical immunosensing platform integrated into a low-cost microfluidic system for the sensitive, selective and accurate detection of cortisol, a steroid hormone co-related with many physiological disorders. Abnormal levels of cortisol is indicative of conditions such as Cushing’s syndrome, Addison’s disease, adrenal insufficiencies and more recently post-traumatic stress disorder (PTSD). Electrochemical detection of immuno-complex formation is utilized for the sensitive detection of Cortisol using Anti-Cortisol antibodies immobilized on sensing electrodes. Electrochemical detection techniques such as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) have been utilized for the characterization and sensing of the …