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BME-SIM REU

Applications are currently being accepted.  
Starting February 5, 2018, applications will be reviewed on a rolling basis until all positions are filled.

Program dates for 2018 are May 27 to August 4.

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The Departments of Engineering, Kinesiology and Physical Therapy at East Carolina University will conduct a 10 week summer research program funded by the National Science Foundation (NSF) for 10 undergraduate students. The goal of the BME-SIM REU is to provide a quality research experience to undergraduate students in order to increase awareness of and application to graduate school. At the end of the program students will have a better understanding of how to conduct research, an increased awareness of graduate school, clarification and reinforcement of a STEM career path, and greater identification as an engineer/scientist. Through the REU program students will be exposed to cutting edge research utilizing advanced computational models with applications in biomedical engineering.

We are seeking rising juniors and seniors from accredited undergraduate institutions who are U.S. citizens or permanent residents to work on a research protocol with senior faculty members. Applicants should have a strong academic record in engineering, basic sciences, math, computer science, or other related disciplines. Underrepresented groups are strongly encouraged to apply, as well as those from academic institutions with limited research opportunities. Applications from community college students who are transitioning to four-year institutions or within a semester from transferring are also encouraged to apply. Each selected participant will receive a $5000 stipend, an on-campus housing, dining plan, access to the student recreation center, and travel to a conference. Funds to travel to the REU site are available as needed.


If you have any questions, please contact Dr. Stephanie George georges@ecu.edu or Dr. Zachary Domire domirez@ecu.edu.


The BME-SIM REU program has some fantastic faculty mentors from diverse backgrounds. Please click on a faculty member's name below to see a biographical sketch and a link to a profile page.

Profile

Dr. George is an Assistant Professor in the Department of Engineering. Her research interests include computational modeling of the cardiovaascular system using MRI, pulmonary hypertension with sickle cell disease, and heart failure patient monitoring. She currently serves as a faculty mentor to the Society of Women Engineers chapter and Biomedical Engineering Society chapter. She has presented research to regional high school students at ECU's Engineering and Technology Day and conducted demonstrations for middle school girls at our STEM2 Girls Day Out Program. As part of her involvement in the American Society of Mechanical Engineers Bioengineering Division, she has reviewed abstracts and judged poster presentations for the undergraduate research competition at the summer bioengineering conference (2012-2013) and has also reviewed undergraduate papers for the Proceedings of the National Conferences on Undergraduate Research (2012).

Profile

Dr. Domire is an Associate Professor in the Department of Kinesiology. He serves as the Director of the Biomechanics graduate program. He also is a mentor for the American Society of Biomechanics Mentor Program, grant reviewer for United States Department of Defense, Israel Science Foundation, and Natural Sciences and Engineering Research Council of Canada, peer reviewer for 21 scientific journals, member of the International Program Committee of icSPORTS 2013 “International Congress on Sports Science Research and Technology Support”, and presented a tutorial on Magnetic Resonance Elastography as a tool to study skeletal muscle at the 2008 North American Congress on Biomechanics.

Dr. Sylcott is an Assistant Professor in the Department of Engineering. His research interests include facilitating engineering design using neuroimaging, effectiveness of design prototypes and representation, and user preference modeling. He currently serves as a faculty mentor for ECU's National Society of Black Engineers chapter. As a member of the American Society for Engineering Education, he has reviewed undergraduate research abstracts submitted for presentation at the annual conference. In 2016, he served as an organizer and instructor for the inaugural Engineering and Technology Summer Academy, a week-long camp designed to expose young women to careers in STEM fields.

Profile

Dr. Kulas is a Professor in the Department of Health Education and promotion. His research interests include how trunk biomechanics influence lower extremity biomechanics during dynamic tasks, material properties of muscle and how they relate to lower extremity injury, and how mechanical factors are related to lower extremity injury. He has reviewed manuscripts and proposals for 4 different organizations including the Journal of Applied Biomechanics and is an active member of several professional societies including ASB, ACSM, and NATA.

Profile  

Dr. Zhen Zhu's research areas include unmanned systems; sensor integration; computer vision, laser, GPS, radio and inertial navigation systems. He was a senior research engineer and a principal investigator with Northrop Grumman Corporation, where he lead several major research programs sponsored by the Defense Advanced Research Projects Agency (DARPA) and the Air Force Research Laboratory (AFRL). Prior to that he worked on research projects funded by the Federal Aviation Administration (FAA), NASA and the Air Force Office and Scientific Research (AFOSR) at Ohio University. He has developed various systems and algorithms for automatic navigation and guidance of manned and unmanned aircraft. He plans to bring his experiences in electrical and aerospace engineering into teaching and research at ECU.

Profile

Dr. Meardon is an Assistant Professor in the Department of Physical Therapy. As a junior faculty member at the University of Wisconsin of La Crosse, she guided 8 doctor of physical therapy students every year in the process of research (hypothesis testing, data collection, data analysis, data interpretation) resulting in 8 local, 5 state and 6 national conference abstract submissions and presentations. She also served as a reviewer for undergraduate research celebrations on a yearly basis as well as for the National Conference of Undergraduate Research in 2013.

Dr. Ryan's broad research interests include acoustics, complex systems, and engineering education. Her current projects include the study of nearly periodic arrays of resonators for several applications including ultrasensitive mass detection and modification of system resonant responses when the array is used as an attachment (energy sink) on a primary resonant structure. In addition, she is modeling acoustic propagation in complex scenes such as littoral or surf-zone environment.

Profile  

Dr. Muller-Borer is an Associate Professor in the Department of Engineering. Her research interests include cardiac electrophysiology, cell-to-cell communication, stem-cell based therapies, and computational biology. She has served as the Vice Chair of the North Carolina Biotechnology Center Intellectual Exchange Group for Laser Capture Microdissection (Laser TAG), executive committee member of the North Carolina Tissue Engineering and Regenerative Medicine Society, a preceptor for ECU Brody School of Medicine High School Medical Honors Program, and as an executive committee member and presenter of Go Science Greenville.

Dr. Mizelle is an Assistant Professor with the Department of Kinesiology. His research interests are based in multimodal neuroimaging and behavioral neuroscience, and are focused on understanding brain function when observing and performing complex action, and also in sensory-motor and sensory-sensory integration. He is also interested in identifying the effects of natural aging and neurological disease on motor- and sensory-related processes. To achieve these research goals, he is currently using EEG and structural MRI to model brain activation. He also has experience working with undergraduate and graduate students at ECU, as well as the Georgia Institute of Technology.

Profile 

Dr. Howard is an Associate Professor in the Department of Engineering. His research interests include design analysis and manufacturing of advanced composite structures, engineering design processes (including modern design tools such as solid modeling, rapid prototyping, finite element analysis, and motion analysis), and engineering education and high school outreach activities. He also has experience working with undergraduates on a NSF REU program for Solid Freeform Fabrication at Milwaukee School of Engineering.

Profile

Dr. Yao is an Associate Professor in the Department of Engineering. His research interests fall in the areas of wireless/wearable medical sensors, sensor networks for home environments, telemedicine, and industrial process monitoring and control. His educational research interests are laboratory/project-driven learning, integration of research into undergraduate education, and development of electronic learning-tools for future engineering education. He has performed manuscript reviews for 12 different organizations, participated in the Summer Ventures program for high school students, and is an active member in four professional societies.

Profile  

Dr. Abdel-Salam is a Professor in the Department of Engineering. His research interests include solar energy, solar assisted heat pumps, wind energy, alternative fuels, supersonic mixing and combustion, atomization, sprays and fuel injection, thermal-fluids systems, Web-based laboratories, distance education, and educational effectiveness in engineering education. He has reviewed manuscripts and proposals for 15 different organizations including the Journal of Energy and is an active member of 5 professional societies including ASHRAE, SAE, ASME, and ASEE.

Profile

Dr. DeVita is a Professor in the Department of Kinesiology. He has been a funded researcher (both P.I. and co-investigator) on six external grants investigating knee joint forces and locomotion biomechanics in people with knee osteoarthritis, knee ACL injury, and healthy and injured runners. He is an active member of the NIH Musculoskeletal Rehabilitation Sciences study section and an American Society of Biomechanics faculty mentor to doctoral students since 2010. He has directly recruited and trained over 100 undergraduate students to work in the ECU Biomechanics Laboratory and mentored seven Undergraduate research grant winners at ECU.

Dr. Perry is a licensed speech language pathologist and speech scientist. She is an associate professor at East Carolina University where she conducts research using magnetic resonance imaging and 3D computer technology to study the anatomy, speech, and surgical approaches used to treat cleft palate. Her research is funded through the National Institute of Health. Her current collaborative work aims to examine the how variations in presurgical anatomy effect postsurgical speech outcomes in children born with cleft palate. Dr. Perry serves on the cleft palate craniofacial team at New Hanover Regional Medical Center in Wilmington, NC. She is the director of the Speech Imaging and Visualization Laboratory at East Carolina University. Dr. Perry serves as the coordinator for the resonance disorders clinic where she provides speech evaluations and therapy to individuals with errors related to cleft palate and resonance disorders. Dr. Perry also provides support and training through surgical mission trips to third world countries.

Research within Visual Motor Lab (VML) involves projects that examine visual attention, arousal, mental workload, and visual processing through neuroimaging. The goal of our research program is to understand how vision and cognition control and modulate motor behavior. This research is based on the use of eye movement recordings, biometrics, and psychophysiological recordings including EMG, EEG, and ECG as well as other measures to examine cognitive function in information rich environments. The lab is designed to measure human motor behavior in dynamic situations through in-field assessment, virtual simulations or in more static, self-paced laboratory tasks. Our secondary focus includes research to determine how visual search behavior influences motor dysfunction such as Mild Traumatic Brain Injury (mTBI) and freezing of gait in Parkinson's disease. At the core of this research is to investigate the links between the perceptual (processing) and motor systems (output). To accomplish this goal, we examine the antecedents and consequences of an individual's ability to function in dynamic situations based on physiological changes that can either facilitate or debilitate performance.


Each faculty mentor will be directing a different project that will be available for students to work on during the program. Potential students should review each project and determine if it would be a good fit for their personal research interests. All projects are related to biomedical engineering, modeling and simulations.

2017

Faculty Mentor: Dr. Stephanie George, Department of Engineering

Computational Fluid Dynamics (CFD) models, combined with imaging, allow for the development of subject, or phantom specific hemodynamic models. These models may be used to diagnose, understand underlying mechanisms of disease, evaluate treatment success, evaluate and test surgical procedures, or predict clinical events or outcomes. Previous REU students have developed CFD models in the pulmonary artery and image processing codes to improve disease diagnosis. The clinical context for this project is coronary artery bypass graft (CABG) flow. Many CFD studies have examined the geometry of the anastomoses and its effect on competitive flow, however few have considered the downstream effects of perfusion and collateral flow. Competitive flow is defined as the influence of the parent coronary artery on the flow in the artery graft, which is not measureable at surgery. This project will utilize a phantom model of the coronary circulation including an adjustable stenosis, peristaltic pump and novel optical imaging method, iCertainty™. The goal of this REU project is to determine the effect of collateral flow on competitive flow in a CABG CFD model at varying levels of stenosis. To accomplish these purposes, the student will: 1) create geometries and computational meshes for CABG models with 50%, 75% and 90% stenosis using ANSYS Workbench; 2) develop the CFD cases (ANSYS FLUENT) for the three geometries with appropriate boundary conditions from iCertainty™; 3) Incorporate downstream collateral flow into the models and run the CFD cases; 4) compare the results using TECPLOT; and 5) determine the impact of collateral flow on CABG flow.

Faculty Mentor: Dr. Zachary Domire, Department of Kinesiology

Most biomechanical models assume that muscle fibers shorten by a factor equal to the overall change in muscle length multiplied by the cosine of the muscle pennation angle. However, there is considerable evidence that muscle fibers shorten by significantly less than this. This is likely because some muscle fibers operate in series rather than in parallel. There are important implications for this assumption in both the force-length and force-velocity relationships of the muscle. The purpose of this project will be to use ultrasound imaging to measure muscle moment arms to predict whole muscle change in length and measure muscle fascicle length changes to develop a better way to represent this in future muscle models. It is hypothesized that this discrepancy can be simply incorporated into a muscle and that doing so can improve model accuracy. The model will be validated by comparing output to experimental measured strength curves. For this project, the student will: 1) collect ultrasound data from the Aixplorer ultrasound system on the lower extremity musculature; 2) calculate muscle moment arms and fascicle lengths; 3) measure isometric strength throughout the range of motion; 4) input parameters into a muscle model developed in MATLAB; and 5) compare model results with experimentally measured strength with various representations of fascicle length changes.

 

Faculty Mentor: Stacey A. Meardon, Assistant Professor, Department of Physical Therapy

Movement variability is proposed to be necessary for adaptation [26] and stress distribution across tissues during active tasks [27]. Low movement variability has the potential to produce areas of concentrated tissue stress which may contribute to micro damage accumulation and injury [27]. However, this has not been empirically examined. In order to adequately capture stress volume, a 3D finite element model fully representing the structure of the tissue of interest is needed. Subject-specific imaging and subsequent processing are needed for input to such models [28,29]. The aim of this study is to examine the influence of coordinative variability of key lower extremity segments on bone stress volume of the tibia using a subject-specific finite element model. The working hypothesis is that reduced coordinative variability of the lower extremity will result in elevated tibial stress measures increasing the likelihood of micro damage accumulation. To accomplish this purpose using a database of MRI images of tibiae, the student will: 1) identify key coordinative and bone stress variables from the literature to guide analysis; 2) process images from existing database using image processing tools in MATLAB; 3) implement a protocol for finite element analysis of tibiae in collaboration with research team; and 4) perform statistical analysis, with guidance of research team to identify the relationship between movement variability and bone stress.

 

Faculty Mentor: Zhen Zhu, PhD, Assistant Professor, Department of Engineering

Various types of sensors and imaging devices have been developed for visualization, clinical analysis and noninvasive diagnosis. For example, CT, MRI and ultrasound can all be used to produce 2D or 3D scans. Infrared cameras have been used to detect light and heat images, which could also be used in 3D modeling. However, imagery of biomedical systems often suffers from noise, interference, blurriness or unwanted motion/vibration caused by the environment, the patient/target, or the user. Image processing techniques have to be customized and reconfigured for this type of imagery [46,47]. Preliminary results from previous REU student research projects have shown that real-time image processing and 3D modeling is indeed feasible by using open-source software libraries. Imagery data can be combined with input from additional sensors, such as motion and displacement, to create more accurate 2D or 3D models. The goal of this REU project is to identify and evaluate the sensor integration algorithms that can be implemented for real-time 3D modeling. To accomplish these purposes, the student will: 1) compare existing software libraries and identify candidate algorithms and libraries; 2) optimize them for biomedical systems; 3) implement them in real-time software; and 4) compare the performance across different algorithms, libraries and computational hardware.

 

Faculty Mentor: Barbara Muller-Borer, PhD, Department of Engineering

Stem cell transplantation is proposed as a therapeutic approach to repair or augment the function of impaired heart tissue. Understanding the mechanisms that safely and efficiently induce differentiation of an adult-derived stem cell into a cardiac myocyte is important for integrating stem cells from variable sources which enhances their use in cell therapy. This project focuses on 1) tissue scaffold design and modeling the cellular microenvironment (continuation of current REU project) [32] and 2) the use of  a two dimensional (2D) cell culture model to evaluate electrical, mechanical and ionic signals, between a modeled cardiac myocytes and adult-derived stem cells (new project). The structural and cellular models will be useful in studying the cardiac microenvironment, the relationship of cellular coupling, and factors determining molecular pathways for the regulation of transcription factors expressed in cardiac myocytes and upregulated in differentiating stem cells. REU students will be introduced to scaffold design and electrospinning techniques, cell culture techniques, confocal fluorescence imaging and time-lapse studies of live cell cultures, and the use of Virtual Cell Modeling and Analysis Software [33] and MATLAB. Specifically, the student will: 1) Use confocal or SEM images of biological scaffolds (results provided from current REU project) to create an analytical model to evaluate mechanical and fluid flow properties of the microenvironment; 2) simulate the spatial and temporal characteristics of the cycling cardiac cytosolic calcium signal and corresponding calcium signal in an adjacent stem cell; 3) predict/analyze the role of calcium diffusion through gap junction mediated cell-to-cell communication and other membrane channels; and 4) assess GJ mediated intercellular communication as the permeability and conductance of myocardial GJ channels are metabolically altered.

 

Faculty Mentor: Anthony Kulas, PhD, Associate Professor, Dept. of Health Education & Promotion

While musculoskeletal models are commonly used to better understand mechanisms of human movement, current musculoskeletal models do not accurately predict quadriceps isometric moments through a full range of motion. Developing subject-specific models that accurately predict muscle strength among healthy individuals is a critical first step towards ultimately understanding mechanisms responsible for both strength gains (performance enhancement) and strength loss (disease states). The purpose of this project will be to develop subject-specific models to predict isometric quadriceps torque profiles reflective of a healthy and young population. Specifically the models will: 1) incorporate the relationship between vastus lateralis fascicle lengthening to whole muscle lengthening and 2) be reflective of in-vivo patellofemoral motion. Comparison to experimental isometric quadriceps torque curves will serve as the criterion for model validation. Specifically, the student will: 1) determine the relationship between vastus lateralis (a surrogate of quadriceps function) fascicle lengthening to muscle lengthening, 2) adapt the model patellofemoral motion to reflect in-vivo motion, and 3) compare model predicted quadriceps torque profiles to experimentally measured quadriceps torques.

 

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

Left-handed individuals are often overlooked in the motor control literature for various reasons. It is well known that right-handed individuals activate networks in the left side of the brain while performing motor acts with their dominant right hand. Traditionally, it has been assumed that left-handed individuals would show brain activations in the right hemisphere that “mirrored” their right-handed counterparts [30]. However, new research has caused some doubt in this assumption [31]. To better understand the motor neurophysiology in left-handed individuals, and how these mechanisms differ from right-handed individuals, direct study of neural activations is needed in left-handed individuals. Electroencephalography (EEG) will be used to image neural activations and a neural networks model will be developed to describe the information flow from one sensor to other sensors in response to a particular task or stimulus. A past BME-SIM REU student conducted a feasibility study, which has shown that information flow measures are sensitive to different motor control conditions, and the purpose of this project is to extend this work using EEG and measures of information flow to determine the cortical networks active in left and right handed individual in different motor and cognitive-motor tasks. To accomplish this purpose, the student will: 1) become familiar with MATLAB for implementation of information flow measures; 2) become proficient at EEG data acquisition; 3) validate the neural network model by evaluating information flow measures in different behavioral domains; and 4) compare estimated information flow dynamics between left- and right-handed individuals.

 

Faculty Mentor: Teresa Ryan, PhD, Assistant Professor, Department of Engineering

The student will contribute to ongoing work in the use of coupled arrays of resonant structures [34-39] for a variety of applications. This topic has roots in a simple single degree of freedom dynamic vibration absorber, which pulls energy at a certain single frequency away from a primary resonator. Work has expanded to include attachment of a set of resonant structures, termed a subordinate oscillator array.  Such complex vibratory systems have possible applications as mechanical filters or absorbers of vibration energy (safety and injury prevention), energy harvesting (such as battery charging based on gait), or ultrasensitive mass detection (breathalyzer for new analytes) [35-38]. The dynamic response of any resonant system can be manipulated by attaching a subordinate oscillator array with a prescribed distribution of properties. Rapid prototyping technology can be used for quick production of design iterations, but the anisotropic nature of the resulting structures requires careful evaluation. Ultimately, variation of mass and stiffness dictate behavior of the vibrating system which has been shown to be highly sensitive to minute variation in those property distributions. The student will design and build a set of resonator arrays designed to trap energy in a chosen frequency range. Specifically, the student will 1) use different rapid prototyping technologies and/or build parameters to fabricate the arrays; 2) Use the dynamic material property measurements of the prototypes in a MATLAB based numerical model of the multi-degree of freedom resonant system; and 3) Use the model to determine the sensitivity of array performance to the different build parameters. 

 

 

Faculty Mentor: Richard Willy, Assistant Professor, Department of Physical Therapy

Soldier mobility and performance is often impaired due to lower extremity injury resulting from high peak and cumulative load demands [40]. In soldiers, the knee is highly susceptible to injury, particularly while marching with body-borne loads [41]. Therefore, algorithms to predict knee loads in soldiers, both with and without body-borne loads, are highly sought. While various screening tools have attempted to predict lower extremity loads and subsequent injury risk in soldiers, these assessments have proven to either lack precision or are not feasible for wholesale adoption in the United States Military. As such, this proposed project aims to develop field-ready algorithms that can accurately predict knee joint loads in soldiers while marching with and without body-borne loads. To accomplish these purposes, the student will: 1) will estimate tibiofemoral and patellofemoral contact forces during marching with and without 50 pounds of body-borne load in a cohort of university-based, Army Reserve Officer Training Corps Cadets via a previously described musculoskeletal model [42]; 2) measure various clinical assessments of lower extremity strength and flexibility as well as aerobic fitness; 3) develop a regression equation to estimate tibiofemoral and patellofemoral contact forces using measurements obtained from the clinical assessments.

 

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

When evaluating products consumers take a variety of factors into consideration. In addition to aesthetics and functionality, how a product makes consumers feel is an increasingly important concern. As of late, there has been a fair amount of work exploring the role of emotions in product design. However, much of this work has been more qualitative in nature than quantitative. As such, there are open questions about how to quantify emotional response to products and how the data can be used to design products that are more emotionally appealing. Neural imaging provides one approach to quantifying this data. Participants in this study will make product judgements while being monitored by electroencephalography (EEG). The goal is to uncover any insights from the neurological activity data collected during product elections that can be used to improve the performance of the emotion based utility models. Specifically, students will: 1) collect neurophysiological data (EEG) from healthy young as they evaluate consumer products; 2) process EEG data in the time and frequency domains; 3) calculate event-related potentials and event-related synchronization and desynchronization; and 4) estimate underlying neuroanatomical generators of the EEG waveforms;

 

 

2016

Faculty Mentor: Dr. Stacey Meardon, Department of Physical Therapy

Tissue specific loads experienced by the human body during physical activity can be obtained through a combination of experimental data collection and musculoskeletal modeling. Current models of bone stress apply external loads experienced during activity to computer simulations of bone. Measures of bone geometry are key inputs to such models. However, subject specific measures of bone geometry can be costly and involve participant exposure to radiation. In order to improve the validity and utility of musculoskeletal models, a cost-effective method to estimate bone geometry with minimal radiation exposure is needed.

Tibial stress injuries are common in military and running populations. The ability estimate subject specific tibial stresses will provide a basis for understanding loads experienced by the tibia during physical activity and has the potential to influence rehabilitative and preventative efforts.

Ongoing work aims to identify the key demographic, anthropometric, and surrogate measures that best predict tibial bone geometries needed for computer simulations. The next steps in this process are to determine an algorithm to asymmetrically scale geometry of the tibia based on key predictors. Bone stress results during running and walking will be compared to those obtained from a subject-specific model using MRI. The results of this work will be used to scale future models of the tibia and are expected to enhance the validity and utility of such models. Key to the success of this project is the utilization of students to assist in processing and scaling MR images using image processing tools in MATLAB. Students will be guided through the study from collection to interpretation (hypothesis, data collection and analysis, data interpretation). Students will be expected to disseminate the outcomes in a public forum.

Faculty Mentor: Dr. Jason Yao, Department of Engineering

Peripheral edema is a swelling as the result of the heart's incapability to circulate fluid. Assessing edema can often provide insight about a patient’s heart condition. Currently, there is an edema ranking system in place that the medical personnel use in skin pressing test. They observe the rate at which the skin bounces back after a press, and then subjectively rank the edema score. This method of measurement by medical professionals is subjective and often inconsistent.

We hypothesize that using pressurized air and image-processing software can analytically evaluate skin edema more objectively and consistently, which will more accurately reflect the patient’s heart status.

The purpose of this project is to test the above hypothesis. Anticipated research work will include: blow a “burst” of air flow to a subject’s leg skin using well-controlled pressurized air (air pressure, distance, angle of blowing. Etc.); capture the skin depression and rebounding with a high speed camera; and analyze skin reaction using MATLAB image process functions such as edge detection. Normalized skin reaction parameters will be calculated from these image-processing data and create a new edema scoring system.

If proven successfully, the proposed approach will provide objective and consistent edema scoring data for more reliable assessment of heart patients. This will further reduce the number of readmission of heart patients who have been released in less than 30 days; cost generated by these patient readmissions are not reimbursed by many insurance companies. Hospitals will significantly save care cost as a result.

Faculty Mentor: Dr. Zhen Zhu, Department of Engineering

This project is focused on the application of medical image processing algorithms and software. One example of such application is image-based pulmonary hypertension monitoring. Pulmonary hypertension leads to right ventricle failure. Thus it is important to monitor the right ventricle for early changes in morphology and function. Image processing techniques will be developed to track the motion of the right ventricle wall to investigate radial strain and strain rate in the vessel wall. Additional features to be investigated include septal bowing and synchronous contraction. It will involve algorithm development for image pre-processing, segmentation, feature extraction and tracking. These techniques will be implemented in real time software, by using any applicable libraries or by developing custom software.

Faculty Mentor: Dr. Stephanie George, Department of Engineering

The clinical context for this project is the pulmonary artery (PA). High pressure in the PA is known as pulmonary hypertension which is associated with high mortality. The gold standard diagnostic technique is right heart catheterization (RHC) which is a very invasive and costly procedure. This same procedure is utilized for monitoring PH with repeat RHC every 3-6 months. This invasive monitoring plan is difficult for patients to adhere to and also continuously exposes them to the risks of RHC. Therefore a non-invasive diagnostic and monitoring technique will improve patient care. Wall Shear Stress may serve as an important metric in diagnosing and monitoring pulmonary hypertension. The student would be responsible for developing an imaging analysis Matlab code to process phase-encoded MR data from the pulmonary artery and branches and estimate the wall shear stress. Imaging metrics will be compared to clinical metrics and outcomes based on echocardiography and right heart catheterization.

Faculty Mentor: Dr. Barbara Muller-Borer, Department of Engineering

Projects in the Cell Based Therapy & Tissue Engineering laboratory are focused on the development and evaluation of 3D cardiac microenvironments to study stem cell differentiation and behavior to advance strategies for safer, more efficient, cell-based and tissue engineered regenerative therapy. Multiple technologies using electrospinning techniques, bioreactor systems, advanced imaging systems and microelectrode arrays are applied to study role of the simulated microenvironments on cell engraftment, differentiation and function.

For this project, the research student will: 1) review current stem cell and cardiac cell models, 2) apply cellular modeling techniques using Virtual Cell and MATLAB 3) create a multi compartment, cellular model to simulate cell-cell dynamics, 4) test and evaluate the cell model’s response to perturbations in the microenvironment 5) analyze and present the results of the study.

Faculty Mentor: Dr. Zachary Domire, Department of Kinesiology

Most biomechanical models assume that muscle fibers shorten equally throughout a muscle and shorten by the same amount as the overall muscle. However, there is considerable evidence that this is not true. There are important implications for this assumption in both the force-length and force-velocity relationships of the muscle. The purpose of this project will be to use ultrasound imaging to measure muscle moment arms to predict whole muscle change in length and measure muscle fascicle length changes to develop a better way to represent this in future muscle models.

Specifically students will: 1) collect ultrasound data from the Aixplorer ultrasound system on the lower extremity musculature; 2) calculate muscle moment arms and fascicle lengths; 3) measure isometric strength throughout the range of motion; 4) input parameters into a muscle model developed in MATLAB; and 5) compare model results with experimentally measured strength with various representations of fascicle length changes.

Faculty Mentor: Dr. Anthony Kulas, Department of Health Education and Promotion

Scaling generic musculoskeletal models according to anthropometric measurements is a common means to ensure that the “subject-specific” model produces strength profiles representative of their actual abilities. While scaling is common, quadriceps torques produced by scaled models have only a modest agreement with experimental data from the same subjects. Developing subject-specific models that accurately predict muscle strength among healthy individuals is a critical first step towards ultimately understanding mechanisms responsible for both strength gains (performance enhancement) and strength loss (disease states). The purpose of this project will be to develop subject-specific models, based on measured fascicle behavior, to predict isometric quadriceps torque profiles reflective a healthy and young population. Comparison to experimental isometric quadriceps torque curves will serve as the criterion for model validation.

Specifically students will: 1) develop subject-specific musculoskeletal models derived from ultrasound-based fascicle behavior measured under passive and active states, 2) investigate the sensitivity of model performance to perturbations in optimal fiber length and 3) compare model predicted quadriceps torque profiles to experimentally measured quadriceps torques.

Faculty Mentor: Dr. Chris Mizelle

Effects of Natural Aging on Cognitive Motor Control General changes in brain structure and function have been well documented in healthy older adults. However, these alterations have yet to be fully characterized in processes related to daily activities, such as tool use. It is unclear whether age-related performance deficits might arise from neuroanatomical alterations, or from more subtle changes in the functional properties of regions and networks for (normally) routine processing tasks. It is also unclear whether contextual or mechanical action-related processes are more affected by natural aging. This research seeks to address these questions by using electroencephalography (EEG) to evaluate the effects of natural aging on brain activity that supports cognitive motor processes in healthy young and older adults and, further, to develop a model of motor-relevant functional connectivity in healthy young and older adults. Specifically students will: 1) collect neurophysiological data (EEG) from healthy young and older adults as they view tool-related actions; 2) process EEG data in the time and frequency domains; 3) calculate event-related potentials and event-related synchronization and desynchronization; 4) estimate underlying neuroanatomical generators of the EEG waveforms; and 5) develop a model of intra- and inter-hemispheric functional connectivity using imaginary cortico-cortical coherence.

2015

Faculty Mentor: Dr. Stephanie George, Department of Engineering

Computational Fluid Dynamics (CFD) models combined with imaging allow for the development of subject specific hemodynamic models. These models may be used to diagnose, understand underlying mechanisms of disease, evaluate treatment success, evaluate and test surgical procedures, or predict clinical events or outcomes. In order to decrease processing time, assumptions about the geometry and flow may be made. The clinical context for this project is the pulmonary artery (PA). High pressure in the PA is known as pulmonary hypertension which is associated with high mortality. The gold standard diagnostic technique is right heart catheterization (RHC) which is a very invasive and costly procedure. This same procedure is utilized for monitoring PH with repeat RHC every 3-6 months. This invasive monitoring plan is difficult for patients to adhere to and also continuously exposes them to the risks of RHC. Therefore a non-invasive diagnostic and monitoring technique will improve patient care. One non- invasive approach is the combined use of magnetic resonance (MR) imaging and CFD. The goal of this REU project is to determine the effect of geometry on the hemodynamics in the PA in both normotensive and hypertensive subjects to improve the clinical utility of CFD models.

To accomplish these purposes, the student will: 1) conduct a literature review on CFD in the PA; 2) create computational meshes for the PA at using MR data from three points in the cardiac cycle; 3) develop the CFD cases for the three geometries with appropriate boundary conditions from MR; 4) compare the results using TECPLOT; and 5) recommend a CFD protocol for generating CFD models in the PA that optimizes processing time.

Faculty Mentor: Dr. Zachary Domire, Department of Kinesiology

Landing from a jump is a common mechanism for ACL injury, particularly when landing with extended knees. The amount of knee flexion when landing varies substantially across individuals, with no clear reason that some individuals choose the dangerous strategy of landing with little flexion. The control of landing strategies is not completely understood. Developing a computer simulation model of landing would be an ideal approach to determine possible control mechanisms and ultimately determine the driving factors that choose some individuals to adopt risky landing strategies.

The current project will be a step towards the development of a subject specific model of landing. Specifically students will: 1) collect ultrasound data from the Aixplorer ultrasound system on the lower extremity musculature; 2) calculate geometric parameters; 3) measure isometric strength throughout the range of motion and take a variety of anthropometric measures; 4) input parameters into a muscle model developed in MATLAB; 5) examine possible objective functions that could possibly be used to control a simulation of landing; and 6) compare results with experimentally measured kinematics and kinetics of the same subjects landing from a jump.

Faculty Mentor: Dr. Paul DeVita, Department of Kinesiology

Musculoskeletal modeling is a current and important area in Biomechanics. Presently there exist a number of biomechanical-neuromuscular models to predict knee muscle and knee joint contact forces during locomotion. Many of these models predict similar results strengthening the confidence researchers have in these models (1, 2, 3). The Biomechanics Laboratory in the Department of Kinesiology at East Carolina University developed and uses a biomechanical model to predict muscle and joint loads in and around the ankle and knee joints in locomotion (4, 5). We have successfully applied the model to both healthy and clinical populations during walking and running gaits.

The NSF-mentored research experience will explore biomechanical-musculoskeletal modeling through a variety of research experiences. These include: 1) learning the basic data capture and processing techniques used in biomechanical modeling; 2) learning the basics of biomechanical modeling through a study of the literature and the current lab model; 3) collecting biomechanical gait data from a variety of movements and using the Lab model to predict forces in the ankle and knee muscles and joints; 4) comparing our predicted muscle and joint forces with those in the literature; 5) performing a sensitivity analysis to determine to degree to which predicted ankle and knee joint forces are sensitive to changes in parameter values; 6) presenting the results of this work to the Biomechanics Lab group; and 7) having fun doing biomechanics science with other fun people.

This project is directly related to Dr. DeVita’s current, NIH funded research investigating treatment options for people with knee osteoarthritis and will lead to both future publications and grant applications.

1. Lin YC, Walter JP, Banks SA, Pandy MG, Fregly BJ. Simultaneous prediction of muscle and contact forces in the knee during gait. Journal of Biomechanics, 2010; 43(5):945-952.

2. Kim HJ, Fernandez JW, Akbarshahi M, Walter JP, Fregly BJ, Pandy MG. Evaluation of predicted knee-joint muscle forces during gait using an instrumented knee implant. Journal of Orthopedic Research, 2009; 27(10):1326-1331.

3. Messier S, Legault C, Loeser R, Van Arsdale S, Davis C, Ettinger W, DeVita, P. (2011). Does high weight loss in older adults with knee osteoarthritis affect bone-on-bone joint loads and muscle forces during walking? Osteoarthritis and Cartilage, 19, 272-280.

4. DeVita, P. & Hortobagyi, T. (2001). Functional knee brace alters predicted knee muscle and joint forces in persons with ACL reconstruction during walking. Journal of Applied Biomechanics, 17, 297-311.

5. Messier, S., Mihalko, S, Legault, C., Miller, G., Nicklas, B., DeVita, P., Beavers, D., Hunter, D., Lyles, M., Eckstein, F., Williamson, D., Carr, J., Guermazi, A. & Loeser, R. (2013). Effects of intensive diet and exercise on knee joint loads, inflammation, and clinical outcomes among overweight and obese adults with knee osteoarthritis. The IDEA randomized clinical trial. Journal of the American Medical Association, 310, 1263-1273

Faculty Mentor: Dr. Jason Yao, Department of Engineering

PIn vivo and in vitro monitoring of cell behavior, such as cell growth, movement, and proliferation, is important for both diagnostic and therapeutic purposes. On the diagnosis end, for example, diseased cells may demonstrate different movement patterns than healthy ones. Capturing these pattern differences early might help detect and prevent certain diseases. On the therapy end, treated cells need to engraft or integrate with native tissue. Continuous monitoring of these dynamics provides significant insights for the healing process.

Multiple MATLAB toolboxes include software tools that can perform image processing and computer vision analysis. This NSF-REU project hypothesizes that effectiveness of medical treatments can be measured using image-based cell monitoring approaches. The REU student will develop MATLAB algorithms that track cell movements and cell size to measure the cells’ response to certain treatment. In order to achieve the goal within the REU timeframe, the image processing procedures (background subtraction, foreground masking, object recognition, etc.) needed in this effort may be created by modifying those from an ongoing research project that develops image-based algorithms to identify and count moving objects.

Faculty Mentor: Dr. Tony Kulas, Department of Health Education and Promotion

Musculoskeletal models, which are commonly derived from scaling generic models to individual subjects, enable the scientific community to investigate how humans perform various movement tasks. To better understand the biomechanical adaptations resulting from an intervention, such as muscle strengthening exercises commonly prescribed in rehabilitation, musculoskeletal models are required to incorporate parameters that are likely to change following the intervention. The current project aims to 1) develop musculoskeletal models that incorporate subject-specific muscle architecture and strength, and 2) investigate the effects of hamstring muscle alterations, simulated based on known adaptations from strengthening programs, on anterior cruciate ligament (ACL) forces during common activities of daily living. Students will: 1) visualize muscle architecture using real-time ultrasound imaging, 2) measure knee muscle strength on an isokinetic dynamometer, and 3) utilize the muscle architecture and strength to create subject-specific musculoskeletal models. Students will then apply the subject-specific models to squatting and landing movements to estimate hamstring muscle and anterior cruciate ligament forces. Finally, students will simulate how a hamstring muscle strengthening intervention would affect hamstring muscle and ACL forces during these movements by altering the hamstring muscle architecture and strength.

Faculty Mentor: Dr. Zhen Zhu, Department of Engineering

When high-quality images of bio-medical systems, such as human organs, are acquired at a high frame rate, it becomes a challenge to receive and process them in real time. The processing algorithms often include various conditioning and filtering steps. We will explore the use of multi-core processors and parallel computing in PCs and embedded computers to accelerate them.

Faculty Mentor: Dr. Stacey Meardon, Department of Physical Therapy

Tissue specific loads experienced by the human body during physical activity can be obtained through a combination of experimental data collection and musculoskeletal modeling. Current models of bone stress apply external loads experienced during activity to computer simulations of bone. Measures of bone geometry are key inputs to such models. However, subject specific measures of bone geometry can be costly and involve participant exposure to radiation. In order to improve the validity and utility of musculoskeletal models, a cost-effective method to estimate bone geometry with minimal radiation exposure is needed.

Tibial stress injuries are common in military and running populations. The ability estimate subject specific tibial stresses will provide a basis for understanding loads experienced by the tibia during physical activity and has the potential to influence rehabilitative and preventative efforts. Previous work estimating tibial bone stress has used geometries obtained from a single sample CT scan acquired from a public database (Edwards et al., 2009) and known values obtained from the literature (Meardon and Derrick, 2013) to scale bone models of the tibia. More recently, pilot work by Meardon and colleagues has used x-ray to obtain 2 planar views of the tibia in order to scale an elliptical model of the tibia. In order to improve model estimates, more precise estimates of individuals’ bone geometry are necessary.

More precise measures can be directly obtained from magnetic resonance (MR) imaging (Hong et al., 2000) in a non-invasive manner. Unfortunately, MR imaging can be costly and may not be readily available to research facilities. Ongoing work aims to identify the key demographic, anthropometric, and surrogate measures that best predict tibial bone geometries needed for computer simulations. The next steps in this process are to determine an algorithm to scale geometry of the tibia for the entry into musculoskeletal model of the tibia based on key predictors and compare results to those obtained from a subject-specific model using MRI. Specifically, the effects of modifying running technique on tibial stress will be examined.

The results of this work will be used to scale future models of the tibia and are expected to enhance the validity and utility of such models. Key to the success of this project is the utilization of students to assist in processing images obtained using image processing tools in MATLAB. Students will be guided through the study from collection to interpretation (hypothesis, data collection and analysis, data interpretation). Students will be expected to disseminate the outcomes in a public forum.

References:

Edwards WB, Taylor D, Rudolphi TJ, Gillette JC, Derrick TR. Effects of Stride Length and Running Mileage on a Probabilistic Stress Fracture Model. Medicine and Science in Sports and Exercise, Vol. 41, No. 12, pp. 2177–2184, 2009.

Meardon SA, Derrick TR. Step width and tibial stresses during running. Journal of Orthopaedic & Sports Physical Therapy, Vol. 43, No. 1, pp. a54, 2013.

Hong J, Hipp JA, Mulkern RV, Jaramillo D, Snyder BD. Magnetic Resonance Imaging Measurements of Bone Density and Cross-Sectional Geometry. Calicified Tissue International, Vol 66, No. 1, pp 74-78, 2000.

Faculty Mentor: Dr. Tarek Abdel-Salam, Department of Engineering

In the human body, cells are mechanically stimulated by shear stresses induced by the flow of blood. In stem cell growth, three-dimensional (3D), porous biomaterials called scaffolds are designed to simulate the realistic extracellular matrices of human tissue. The scaffolds are cell-seeded and perfused with a bioreactor fluid in a flow chamber to stimulate growth. This is known as tissue engineering. Optimizing tissue engineering techniques allows for tighter control of tissue development, growth, and properties [1]. Since the velocity profiles and shear stresses within the flow chamber are virtually impossible to measure directly, computational fluid dynamics (CFD) will be used.  

In this study, the research student will: 1)Learn about tissue engineering, 2) Use a CAD program to create the physical models (Solid Works or Autodesk Inventor), 3) Learn numerical modeling and CFD techniques, 4) Create computational grids for the numerical analysis, 5)Use the finite volume CFD code to perform the numerical analysis, 6) Analyze and present the results of the study. 

[1] A. Lesman, Y. Blinder, and S. Levenberg, “Modeling of flow-induced shear stress applied on 3D cellular scaffolds: Implications for vascular tissue engineering,” Biotechnol. Bioeng., vol. 105, no. 3, pp. 645–654, Feb. 2010.

We are currently accepting applications.  Interested students should submit their application materials as soon as possible.  The application will remain open until all positions are filled. Starting February 5, 2018, applications will be reviewed on a rolling basis until all positions are filled.

Please read the following important information and submit all required materials before the deadline.

Qualifications

  • US citizen or permanent resident
  • Strong academic record
  • Incoming senior, or rising junior with strong academic record
  • Students from underrepresented groups (women, minorities, and persons with disabilities) and academic institutions with limited research opportunities, including community colleges, are especially welcome

Financial Incentive

  • $5,000 stipend
  • On-Campus Housing
  • Dining Plan
  • Access to Student Recreation Center
  • Travel to a conference
  • Travel reimbursement of up to $300 as needed

Required Materials

  • Completed application form (Application Form) <-- Click here for Application
  • One-page personal statement which includes your interest in the BMESIM program and research goals
  • Two recommendation letters (see below for more details)
  • An unofficial copy of academic transcript(s) from all higher education institutions attended

Submit the personal statement and unofficial copy of the transcript(s) (PDF) to BMESIM@ecu.edu with the subject line REU Application - first and last name. (ex. REU Application - Stephanie George).

The letters of recommendation should come from faculty who can speak about your academic achievements and interest in research. Letters should be submitted on official letterhead by the faculty member to BMESIM@ecu.edu with the subject line: Recommendation - first and last name. (ex. Recommendation - Stephanie George)

All materials (online application, research statement, transcript, and letters of recommendation) must be received in order for the application to be reviewed.


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Student Recreation Center and Adventure Center

The adventure center offers a rock climbing wall, kayak rentals and trips, paddle board floats and other equipment rentals.  Click here for website.

ECU Transit

The RED bus takes students to and from the medical campus.  Click here for website.

Parking

Click here for parking map.

Mendenhall Student Center

The student center offers bowling, billiards, table tennis and a gameroom (pricing).  Films are shown in the Hendrix Theatre (free with ECU OneCard), see here for schedule.

Student Health Services

Click here for website.

Greenville Guide

This document contains information about Greenville and the surrounding areas.

2015

Holly DeSmitt is a senior majoring in physics with a minor in mathematics at the State University of New York Geneseo. DeSmitt pursued the REU to gain research experience in an area that she was very interested in and passionate about. “I was especially attracted to the ECU REU because it gave me an opportunity to directly apply the physics skills that I have developed to a biomedical field in which I have had very little experience,” DeSmitt states. “My research skills strengthened as I was required to do mostly independent work. I learned a lot about graduate school and academia through close interactions with graduate students and professors.” “Some of the best memories of the summer were the weekend trips we took to the North Carolina beaches,” DeSmitt said. DeSmitt adds, “The research I did was very impactful and the faculty at ECU were personable, insightful, and willing to help me with my future plans.”

Holly

Alan Register is a junior in biomedical engineering, from East Carolina University. Register pursued the REU program in order to explore his research interest in the field of medical imaging. “Medical imaging contains many fields of science and engineering that intrigue me,” states Register. “I enjoy challenges and I felt I would gain valuable research experience and meet new people.” Register explains, “Before starting the REU, I had little to no knowledge with research”. Register’s project was focused on using a small embedded computer to perform live image processing. His favorite moment on the project was “realizing that the computer algorithm for my project actually compiled correctly and was functional after a long night of coding.” “I enjoyed meeting new people from different universities. The ECU REU program provided an excellent opportunity to actively engage in interesting, rewarding, and meaningful research with other students,” adds Register.

Faculty Mentor: Dr. Zhen Zhu

REU Project: Real time medical image processing using a small form factor computer

Alan

Alexander McGirt is a senior engineering major at UNC -Charlotte from Pembroke, NC. McGirt transferred to UNCC from UNC-Pembroke. He has an interest in research and decided to pursue participation in the REU because of his interest in biomedical engineering. “I thought the REU would be an excellent experience to gain knowledge, make connections, and even get paid.” All participants received a stipend and room and board as part of the REU program. McGirt’s favorite memory was a trip to the Outer Banks and riding jet skis one weekend. He also enjoyed staying on campus and building new friendships. “My favorite part of my time at the REU was gaining firsthand knowledge of the biomechanics side of biomedical engineering while collaborating with many individuals,” adds McGirt.

Faculty Mentor: Dr. Paul DeVita

REU Project: Predicting Lower Extremity Loads Through Bio-Mechanical Modeling

Alexander

Corey Hornbeck is a junior in biomedical engineering at Illinois Institute of Technology from North Aurora, Illinois. Hornbeck’s goal was to “be exposed to the research field of biomedical engineering and work with others to accomplish a research-oriented goal.” Hornbeck enjoyed his time in a more rural setting than the city life that he is accustomed to in Illinois. “Having a one-on-one mentor relationship with an accomplished faculty member at ECU was my favorite part of my experience,” Hornbeck adds.

Faculty Mentor: Dr. Stephanie George

REU Project: Using Phase-Contrast MRI to Calculate Wall Shear Stress in Pulmonary Hypertension

Corey

Jacob Brooks is a senior physics major at High Point University from Monkton, Maryland. Brooks elected to pursue an REU in order to “expose myself to an experience in the field of biomedical engineering to visualize that as a future career option. I wanted to be able to show graduate schools and potential employers that I have a diverse range of research abilities and make contacts that could be valuable into the future,” adds Brooks. One of Brooks’ favorite memories was playing soccer and ultimate Frisbee with other students on campus that were participants in a computer science REU being hosted at ECU. “I enjoyed being exposed to new people, new software and instruments, and making new connections including the one with my research advisor,” Brooks states. Read more about Jacob.

Faculty Mentor: Dr. Tarek Abdel-Salam

REU Project: Optimization of Square Channel Micromixer for a Variety of Reynolds Numbers with Two-Phase Liquid-Liquid Flow

Jake

LaQuanda Fredericks is a senior biology major at North Carolina Central University from St. Thomas, US Virgin Islands. Fredericks is interested in attending medical school, and thought that research “could have a significant impact on my professional growth and experience novel areas of science.” Her best memory of the program was being introduced to the DaVinci surgical robot. Fredericks also enjoyed the feeling of being part of project. “I especially loved the feeling of accomplishment I got when I coded something successfully in Matlab and saw the outputs of the code appear on the screen.”

Faculty Mentor: Dr. Stephanie George

REU Project: Retrospective Analysis of Doppler Echocardiography in Pulmonary Hypertension

LaQuanda

2014

Leticia De Jesus is a senior at The University of Texas at El Paso majoring in Kinesiology and minoring in Biology. She plans to attend graduate school to obtain a Doctorate of Physical Therapy and specialize in cardiopulmonary therapy. Leticia chose this REU program because of the financial incentives such as on campus housing, access to the student rec center, and dinning plan. It also gave her the opportunity to develop new skills and refine others, and network with students of different majors other than hers. Leticia’s hobbies include watching movies, working out, playing basketball, bow hunting, and trying new things.

Faculty Mentor: Dr. Paul DeVita

REU Project: Sensitivity Analysis of the Patellofemoral and Knee Compressive Forces to Predicted Muscle Forces

Current Status: Leticia graduated from UTEP in December 2014 and is currently applying to physical therapy programs.

Leticia

Alex Bryan graduated from East Carolina University in May 2015 with a degree in Engineering and concentrations in Biomedical & Industrial and Systems. He plans to attend graduate school to pursue a master's degree in one of his concentrations. He hopes to work in the area of medical device development in the future.

Current Status: Alex is currently attending graduate school at North Carolina State University pursuing a master's in Industrial and Systems Engineering. He is doing research in the area of animal prosthetics.

 

Alex

My name is Karleen Bartol and I am from Apex, NC. I will be a senior in the fall here at East Carolina. I am majoring in exercise physiology, and after I graduate I plan on attending PT school. I applied to this program because of the opportunity it would provide for me as an undergraduate to be involved in research in my future field of study and it involved projects that interest me. In my free time I enjoy hanging out with friends, going to the beach or lake, swimming, and reading.

Faculty Mentor: Dr. Stacey Meardon

REU Project: Scaling Bone Geometry for Musculoskeletal Modeling in Physically Active Populations

Current Status: Karleen graduated from ECU in May 2015 and is currently a student in the Physical Therapy Program at ECU.

Karleen

My name is Jason Farmer. I was born and raised in Winchester, VA and love to return to the Shenandoah Valley for hiking, camping and photography trips. I have lived in North Carolina since 2010 and I have been studying mechanical engineering at Elizabeth City State University since the fall of 2012. I am working on a project for my home university that involves the use of the brain's electrical signals to allow individuals to naturally control devices such as prosthetic implants - the BMESIM REU experience is offering various techniques and insights that will directly benefit that project. I have a wide range of hobbies: playing the guitar and didgeridoo, oil painting (usually animals or abstract scenes), biking and canoeing, role playing (it's always interesting to see how people react when "the quiet guy" REALLY gets into character and insanity ensues), playing video games, and going on adventures with my cat Shadow.

Jason

My name is Kiera Benson and I am a junior pharmaceutical science major at North Carolina Central University with a passion for the sciences and for helping people in need. I plan on going to graduate or professional school after obtaining my undergraduate degree.

Faculty Mentor: Dr. Barbara Muller-Borer

REU Project: Fluid Flow Dynamics: Modeling Media Properties During Electrospinning

Current Status: Kiera is currently a senior at North Carolina Central University.

Kiera

Jayden Stewart will be a senior at Tarleton State University in Stephenville, TX. He is studying Mechanical Engineering Technology with a minor in Mathematics. Jayden plans to attend the University of Texas at Arlington or another graduate school to pursue a master's degree in Mechanical Engineering. Jayden was once ranked 11th in the world in Game of Thrones trivia.

Faculty Mentor: Dr. Tarek Abdel-Salam

REU Project: Three-Dimensional Microfluidic Computational Study in Tissue Engineering

Current Status: Jayden graduated from Tarleton State University in May 2015 and is currently a Master’s student in Mechanical Engineering at the University of Michigan.

Jayden

James Kulii is studying Biological Engineering at North Carolina A&T State University in Greensboro, NC. He is deciding between graduate school and industry, focusing on Biological Engineering. He is interested in honing his skills in the natural processes and efficiencies of biological systems.

Faculty Mentor: Dr. Stephanie George

REU Project: Subject Specific Modeling of Blood Flow in the Pulmonary Artery

Current Status: James is currently a senior at North Carolina A&T State University.

James