Current Student Projects

Past Project Archive

Modeling Arteriovenous Fistula Hemodynamics in ESRD Patients with Pulmonary Hypertension

Faculty Mentor:  Fatemeh Bahmani, PhD, Postdoctoral Fellow, Department of Engineering

Permanent structural damage to the kidneys results in chronic kidney disease, a condition affecting over 15% of Americans. Over time, this can develop into end-stage renal disease (ESRD) where patients require hemodialysis, through a surgically-created arteriovenous fistula, to filter and purify circulating blood. One comorbidity of ESRD is pre-capillary pulmonary hypertension (PH) which is believed to be connected to the creation of the arteriovenous fistulas; however, there is little conclusive evidence supporting this hypothesis. The overall objective of this project is to correlate fistula and pulmonary artery hemodynamics to better understand PH development in ESRD patients and engage in a preliminary analyses to connect these parameters to standard clinical measures for early identification and monitoring.  Previous REU projects have focused on modeling hemodynamics in the pulmonary artery. Here, we focus on modeling fistula flow in patients with pulmonary hypertension. To accomplish these purposes, the student will: 1) use Mimics (Materialise) to segment fistula geometry from MR images; 2) mesh geometries using ANSYS Workbench; 3) develop computational fluid dynamics models (ANSYS FLUENT) with appropriate boundary conditions; 3) visualize results; and 4) compare fistula flow parameters to PH metrics (pulmonary artery pressure and vascular resistance).

Effect of concurrent visual and auditory attention tasks on brain activity during postural control

Faculty Mentor:  James Lin, PhD, PT, MS, Assistant Professor, Department of Physical Therapy

Project description: Cognitive demands for human postural control, especially attention, can be evaluated by dual-task paradigms, in which a secondary cognitive task is performed spontaneously with a balance task. Previous studies have used auditory tasks as the secondary cognitive task to examine the effect of attention on human postural control. However, besides the auditory task, people are occupied by various visual attention tasks in daily life. Little is known regarding how the human brain processes concurrent auditory and visual attention tasks while maintaining postural control. The purpose of Dr. Lin’s project is to investigate brain activity during concurrent visual and auditory attention tasks in a standing position. Functional near-infrared spectroscopy (fNIRS) will be used to detect brain activity and visual attention tasks will be provided via a virtual reality headset. Specifically, students will be expected to: 1) complete research training for the human subjects research and project specific tasks; 2) help with data collection and processing; and 3) conduct analyses to determine the effect of concurrent visual and attention on human postural control.

Ultrasound elastography to measure in vivo muscle force

Faculty Mentor: Zac Domire, PhD, Associate Professor, Department of Kinesiology

Coming Soon!

Modeling Skeletal Loads during Recreational, Sport and Tactical Activities

Faculty Mentor: Stacey A. Meardon, PhD, PT, Associate Professor, Department of Physical Therapy

Skeletal injuries are common in tactical, recreational, and competitive athletes. The ability to estimate forces acting within the skeleton will provide a basis for understanding loads experienced during physical activity, potentially influencing rehabilitative and preventative efforts.  Skeletal loads experienced by the human body during physical activity can be obtained through a combination of experimental data collection and musculoskeletal modeling. Ongoing work aims to identify efficient and valid approaches to estimate skeletal loads in large scale studies of physically active populations. Nested within this work, current studies seek to identify factors (e.g., bone strength, footwear, technique, speed, fatigue) that influence skeletal loading. Subject-specific skeletal loads and bone strength estimates during lower limb motor tasks will be estimated using a series of musculoskeletal models and cross validated with cadaver strain gauge data, full tibial finite element models, and/or existing literature values. For this project, the student will: 1) assist in collecting, processing, and analyzing 3D motion data 2) process MRI, CT images, and/or US data using image processing tools; 3) develop finite element skeletal models at regions of interest; and/or 4) assess model fidelity. 

Modeling information transfer through dynamical systems: A brain-based approach

Faculty Mentor: Chris Mizelle, PhD, Associate Professor, Department of Kinesiology

Right-handed individuals activate networks in the left side of the brain while performing motor acts with their right hand. It has been assumed that left-handed individuals would show brain activations that “mirror” this; However, new research has raised doubts. To understand the motor neurophysiology in left-handed individuals, and how these mechanisms differ from right-handed individuals, direct study of neural activations is needed. Traditional measures of brain activations, acquired using electroencephalography (EEG), focus on evaluation of time-voltage and time-frequency analyses of sensor-level data. Recent computational developments, however, provide researchers with advanced techniques to study brain activation localizations and information flow dynamics. Past REU students demonstrated feasibility. Extending previous work, this project will use EEG to image neural activations and develop a neural networks model to describe the information flow in left- and right-handed individuals. To accomplish this purpose, the student will: 1) collect EEG data; 2) implement information flow measures in MATLAB; 3) validate the neural network model by evaluating information flow measures in different behavioral domains; and 4) compare information flow dynamics and source localization results between left- and right-handed individuals.

Role of miRNAs in transgenerational mechanisms that contribute to familial obesity predisposition using drosophila as a model system

Faculty Mentor: Alexander Murashov, PhD, Professor, Department of Physiology, Brody School of Medicine

Many noncommunicable diseases (NCDs) exhibit strong family clustering, including obesity, metabolic disorders, heart diseases, and cancer. However, study of long-term generational effects under controlled conditions is nearly impossible in humans. Drosophila has been proven to be an effective model system for generational studies that can be used to gain information about epigenetic regulation of the predisposition to NCDs. This project aims to uncover role of miRNAs in transgenerational mechanisms that contribute to familial obesity predisposition.  In this project, we will characterize the offspring metabolic phenotype and feeding behavior after ancestral Western diet. We will also knockdown or overexpress miRNAs to assess their contribution into transgenerational phenotype. The results may uncover new markers and therapeutic targets of predisposition to obesity. The results of the study may lead to the identification of new markers and therapeutic targets for obesity predisposition. 

Visual Motor Control as Indicator of Neurological Function

Faculty Mentor: Nicholas Murray, PhD, Professor, Department of Kinesiology

The oculomotor system can be an indicator of the neurological status of an individual.  For example, individuals with traumatic brain injury (TBI) and mild traumatic brain injury (mTBI) suffer from a number of vision and visual processing dysfunctions, including visual field defects, vision motion sensitivity, and oculomotor deficits. Eye movement assessment and brain imaging techniques including fNIR/EEG provide biological markers for specific pathology and indicate cortical and subcortical brain areas that influence motor performance.  While there is considerable evidence for motor dysfunction following neurological impairment, the purpose of this project is to model visual scan patterns of individual’s neurological impairment using an eye tracking enabled Virtual Reality (VR) system.  Specifically, the student will: 1) use MATLAB or similar program to develop analytical measures for brain injury within an eye tracking enabled VR system; 2) analyze visual control parameters that are most predictive of neurological impairment; and 3) develop models using visual control variables to distinguish long term effects of neurological impairment. 

Neural Basis of Design Fixation

Faculty Mentor: Brian Sylcott, PhD, Associate Professor, Department of Engineering

Design fixation refers to blind adherence to a set of ideas, which can limit the output of conceptual design. Engineering designers tend to fixate on features of pre-existing solutions and consequently generate designs with similar features. The lack of variety resulting from this behavior can inhibit design innovation. As such, researchers have sought to better understand the mechanisms behind design fixation in order to develop strategies to mitigate its effects. While traditional attempts to study design fixation have focused on behavioral observations, advances in neuroimaging have opened new avenues for research. This project will employ a novel neuroimaging technology, functional near-infrared spectroscopy (fNIRS), to study the brain activity of engineering designers during conceptual design in order to understand how design fixation is reflected in a person’s brain when solving design problems. Preliminary functional magnetic resonance imaging (fMRI) results show increased activation in areas associated with visuospatial processing when comparing ideation activities completed using a fixation source to those without one. Activation was found in the right inferior temporal gyrus, left middle occipital gyrus, and right superior parietal lobule regions. The left lingual and superior frontal gyri were found to be less active in the example condition; these gyri are close in proximity to the prefrontal cortex, associated with creative output. The spatial patterns of activation provide evidence that a shift in mental resources can occur when a designer becomes fixated. These results will be explored further in this work. Specifically, students will: 1) collect neurophysiological data from healthy adults completing conceptual design tasks; 2) process fNIRS and behavioral data; and 3) correlate data with experimental conditions.

Stability Fluctuations during Locomotion

Faculty Mentor: Ryan Wedge, PT, PhD, Assistant Professor, Department of Physical Therapy

People may optimize gait stability when they walk with preferred patterns. It is unclear how gait stability is modulated when doing different gait tasks, such as traversing uneven terrain. Also, it is unknown if people can further lower the amount of necessary stability when walking with preferred speed on unthreatening terrain. The end goal of this project is to develop interventions that may improve stability in people with pathology, such as lower limb amputation or stroke. The aim of the current step in this project is to develop a real-time stability feedback system that can be used in the lab environment. To accomplish this aim and in collaboration with the research team, the student will: 1) Collect and analyze motion capture data necessary for the stability calculation using Qualisys, V3D, MATLAB and LabVIEW, 2) Create a program for multiple stability metrics in real-time, and 3) test the program with unthreatened and threatened walking.

Brain, language, and real-time processing correspondence in healthy individuals and individuals with impaired language

Faculty Mentor: Matthew Walenski, PhD, Associate Professor, Department of Communication Sciences and Disorders

Language is a unique human capacity. When language can be impaired, whether due to brain injury or disease, psychiatric disorder, or atypical development, there are often profound consequences for an individual and their quality of life. Understanding and ameliorating impaired language depends on our knowledge of the structure of language, the processes by which it is produced and comprehended in real time, and the structure and function of the brain regions that subserve these processes. The goal of this research project is to use electroencephalography (EEG) and event-related potential (ERP) techniques to examine these correspondences between brain, language, and real-time processing in healthy individuals and individuals with impaired language. Students will: 1) complete training for human subjects’ research and project specific tasks; 2) contribute to the development of new paradigms to elicit clinically relevant ERPs reflecting language and cognitive function; 3) help with data collection and processing; and 4) develop clear and compelling data visualization techniques.