Injury Science REU Research Projects

The Center for Injury Research and Prevention (CIRP) at Children's Hospital of Philadelphia (CHOP)'s Injury Science Research Experiences for Undergraduates (REU) Program offers projects in three areas of research:

CIRP is a leading multidisciplinary center engaged in collaborative cross-discipline research implementing real-world applications, and the Injury Science REU Program includes mentoring from a well-established team of highly trained pediatric researchers as well as peer mentors.

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Clinical Research Associate Jalaj Maheshwari, MS collaborating with Injury Science REU alum Sophie Tushak on an Engineering Core project.

Engineering Core

All Engineering Core REU students will learn the design and conduct of laboratory-based and real-world engineering studies and the analysis and interpretation of the data collected. They may have opportunities to submit and present their work at conferences (e.g., The Ohio State University Impact Biomechanics Symposium and the Annual Meeting of the Human Factors and Ergonomics Society) with support from their mentors and to participate in the preparation of publications. They will be encouraged to work independently with appropriate mentorship and to generate enthusiasm and future career interest in engineering research that incorporates medicine and behavior for injury prevention.

The following projects will be conducted with the REU Class of 2023 students: 

Engineering Research Projects

Project 1: Biomechanical Responses during Pre-Crash Maneuvers and Autonomous Driving Scenarios

Mentor: Valentina Graci, PhD

Research Description

Motor vehicle crashes remain a leading cause of death for children, youth, and young adults. Historically, automotive safety research and advancements have focused on the mitigation of injuries once the crash has occurred. However, more recently automotive safety research is shifting its focus to studying events prior to the crash. Previous research has shown that more than 60% of crashes involve some form of pre-crash maneuver (braking, swerving, skidding) prior to the crash. This number is likely to increase with the advent of early warning systems and autonomous vehicles. At the Center for Injury Research and Prevention, we are interested in understanding how pre-crash maneuvers affect child occupant position and motion prior to a crash. We are developing warning systems that could decrease reaction time and body motion outside the optimal position within a seat belt. We are also developing new technology and analytic methods to test seating configuration and automatic emergency braking in critical autonomous scenarios.

REU Project Description

The REU student will become a member of the Engineering Research Core at the Center for Injury Research and Prevention and will receive mentorship from several of the lead investigators of the Core. Depending on the stages of projects, the student will be involved in various aspects of the research process, including designing and machining experimental fixture, data collection on human volunteers, post-processing, data analysis, and interpretation of the results. The student will develop skills with data analysis of a diverse set of data types that could potentially be: motion capture and EMG data collection and/or analysis of children and young adults. Previous experience using MATLAB is critical. The student will have the opportunity to increase skills in this area. The student will also gain experience in problem-solving, analyzing data, interpreting findings, and developing new research ideas. There may also be potential opportunities to submit and present the student's work at conferences and to participate in the preparation of journal publications. This project work is in person to allow the student to also participate in potential data collection or fixture modifications, besides data analysis.

Project 2: Understanding Eye-Glance Behaviors Among Young Drivers

Mentor: Thomas Seacrist, MS

Research Description

Despite continued advances in young driving safety, motor vehicle crashes remain a leading cause of death for young drivers (16-24 years). While inexperience contributes to this elevated crash risk, other developmental factors, such executive function, also influence crash risk in young drivers. Our previous research has shown that drivers who are slower to develop their executive functioning skills are more likely to be involved in motor vehicle crashes. Additionally, drivers with poorer executive functioning are less likely to detect road hazards. Our team is currently collecting eye-tracking data among novice drivers using a novel simulated driving assessment. We are interested in understanding how eye-glance behaviors vary with executive function and other development factors.

Additionally, we are also interested in understanding how eye-glance behaviors vary among young drivers during their typical day-to-day driving. Recently, the US Department of Transportation funded a large-scale US naturalistic driving study – the Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study – which tracked day-to-day driving among 3,000 drivers over a three-year period. This large dataset offers a unique opportunity to study eye-glance behavior during real-world driving. We are interested in understanding how eye-glance behavior varies with driver age, road types, environmental factors, etc.

REU Project Description

The REU student will become a member of the Neuroscience of Driving Team at the Center for Injury Research and Prevention and will receive mentorship from several of the lead investigators. The REU student will be involved in the review and analysis of eye-tracking data collected from young drivers during simulated driving assessment (i.e. a virtual drive consisting of common crash scenarios) and/or during real-world driving (i.e. eye-tracking data collected from in-vehicle cameras that tracked drivers during day-to-day driving). The student will hone his/her skills with video coding, eye-tracking metrics, data analysis, and team-based data review. The student will also gain experience in problem-solving, interpreting findings, and identifying new research questions. There will also be opportunities to submit and present at conferences and to participate in the preparation of journal publications.

To this end, we are seeking a highly motivated applicant with a strong interest in eye-tracking, traffic safety, and/or human factors, ranging from conceptualization of research projects to publication. Students majoring/concentrating in Engineering, Data Science, Human Factors, Behavioral Science, or a related major are encouraged to apply. Previous experience using MATLAB, Python, R, or other programming language is required, and the student will have the opportunity to develop skills in this area. Prior experience with video coding or eye-tracking is preferred. Scientific writing experience and an interest in co-authoring publications is also preferred.

Project 3: Analysis of Pediatric Occupant Kinematics and Kinetics in Motor Vehicle Crashes (In-Person or Remote)

Mentor: Jalaj Maheshwari, MSE

Research Description

Motor vehicle crashes and incidents are a leading cause of injury for children, youth, and young adults worldwide. The Engineering team at the Center for Injury Research and Prevention strives to prevent these motor vehicle injuries through a variety of pediatric research projects using computational modeling and/or sled testing. Human body models and anthropomorphic test devices (ATDs), also known as crash test dummies, are a great tool to assess the kinematic and kinetic responses of an occupant under different crash conditions. We are analyzing the responses of pediatric occupants in different crash conditions, vehicle restraint parameters, and child restraints. The occupant kinematics, kinetics, and injury metric data will be analyzed over the crash conditions to better guide passive safety systems (seat belts, airbags) and child restraint system development.

REU Project Description

The REU student will become a member of the Engineering Research Core at the Center for Injury Research and Prevention and will receive mentorship from several of the lead investigators of the Core. The student will be involved in various aspects of the research process including data extraction, data pre-processing, data analysis, and interpretation of the results. The student will be analyzing kinematic, kinetic, and injury data.

Previous experience using MATLAB and/or Python is required. Additional experience with finite element (FE) modeling is desirable but not required. The student will have the opportunity to increase skills in these areas. The student will also gain experience in problem-solving, data analysis, interpreting findings, and developing new research ideas. There will also be opportunities to submit and present the student's work at conferences and to participate in the preparation of journal publications.

Project 4: Social Equity and Spatial Effects on Safe Mobility

Mentor: Megan S. Ryerson, PhD

Research Description

The field of transportation recognizes that the “after-the-fact” crash-based model of safety is biased, but presently does not have a clear mechanism to test safety in an a priori manner. Earlier attempts to collect such proactive data have been challenging and prohibitively expensive, or, at worst, unsafe. However, a new individual-level data set of virtual driving assessment scores, merged with real driving test results and traffic infringement and crash records obtained from administrative sources, affords a unique opportunity to begin proactively planning for safe mobility.

At the Center for Safe Mobility at the University of Pennsylvania we are particularly interested in working with these data to measure the social and spatial predictors of safe mobility. In this study we operationalize safe mobility through virtual driving assessment results, live driving test results, and observed driving behavior. We will then measure the effect of socioeconomic and demographic predictors on these indicators using measures such as: the individual’s socioeconomic and demographic background, roadway typologies around the individual’s residence, intersection characteristics at the location of low-test performance or an observed crash, and more. The Center for Safety Mobility features a diverse and interdisciplinary research team from fields that include engineering, city planning, spatial science, and more.

REU Project Description

The REU student will be a member of the research team at the Center for Safe Mobility and will receive direct mentorship from Dr. Ryerson and lead members of her research team. The student will engage in a diverse array of research tasks including, but not limited to: data analysis, data visualization, writing and oral presentation, and spatial analysis. The Center for Safe Mobility conducts almost all analyses using the open-source statistical software R. Previous experience using R is thus desirable. Regardless of knowledge of R, the student will have ample opportunity to increase skills in this platform, given the wide range of uses for which it is currently employed in the Center’s research.

The student will also be an active intellectual partner and contribute in regular meetings with the research team, actively contribute to project development, and help generate new research questions. There will be possible opportunities to present the student's work at conferences and to be co-author on journal publications.

Project 5: Developing 3D-Printed Anthropomorphic Models to Improve Clinical Training

Mentor: Michael Hast, PhD and Elizabeth Silvestro, MSE

Research Description

Knee injuries are a common complaint among children presenting to emergency rooms and primary care centers. A common sign of knee injury is effusion, a collection of fluid that can be encapsulated or burst. Current diagnosis begins with a physical exam, which relies on a subjective interpretation of manual examinations.  Medical training programs provide minimal guidance with respect to accurately diagnosing pediatric knee effusions. At the same time, a misdiagnosis or delay in identifying knee effusions can impart longstanding complications to the joint, including growth disruption and loss of range of motion.

Because of this, MRI and ultrasound are currently used to provide clarity to the diagnosis, but this represents a significant increase in time spent in the clinic and includes a significant economic burden. Therefore, there is a need for a scalable solution to adequately prepare clinicians for manual pediatric knee evaluation. Hands-on trainers revolutionized training in cardiopulmonary resuscitation and offer an effective framework for improving manual diagnosis of pediatric knee effusions. The goal of this project is to design and develop 3-D printed models of physiologic and pathologic pediatric knees for the purpose of training medical professionals.

REU Project Description

The REU student will become a member of the Additive Manufacturing for Pediatrics 3D Lab at CHOP and the McKay Orthopaedic Research Lab at the University of Pennsylvania. The student will be involved in various aspects of the research process, including data collection, data analysis, and interpretation of the results. The student will gain first-hand experience segmenting and analyzing MR images, creating biofidelic models with 3D printing techniques, and performing mechanical testing with universal test frames.

The student must be enrolled in either a Bioengineering or Mechanical Engineering program. Previous experience with CAD programs and coding with MATLAB and/or Python is desired but not required. The student will have the opportunity to increase skills in these areas and will also gain experience in problem-solving, data analysis, interpreting findings, and developing new research ideas. There will also be opportunities to submit and present the student's work at conferences and to participate in the preparation of journal publications.

Behavioral Science Core

All Behavioral Science Core REU students will be exposed to core behavioral science research methods – quantitative and qualitative – and will apply them in settings involving human subjects. They may have opportunities to submit and present their work at conferences (e.g., the International Study for Traumatic Stress Society Annual Conference, the CHOP LEND Research Day) with support from their mentors and to participate in the preparation of journal publications. They will be encouraged to work independently with appropriate mentorship and to generate enthusiasm and future career interest in behavioral science research that links behavior to medicine and engineering for injury prevention and prevention of traumatic stress among injured children.

The following project will be conducted with the REU Class of 2023 students:

Behavioral Science Research Project

Project 6: Examining Learning to Drive, Risky Driving Behavior, and Crashes in Young Drivers

Mentor: Elizabeth A. Walshe, PhD

Research Description

Compared to adults, young novice drivers are three times more likely to be involved in a motor vehicle collision, which remains a leading cause of death and injury among adolescents. We are currently conducting a number of studies examining the relationship between driving skills, motor vehicle crashes, and the development of the neural and cognitive processes necessary for safe driving in adolescents and young drivers. 

REU Project Description

The REU student will join an interdisciplinary research team that combines cognitive neuroscience, developmental psychology, data science, and epidemiology approaches to understand risky driving behavior and increased crash risk among young novice drivers. This team conducts clinical human subjects research, as well as population-level studies of young drivers. As part of this quantitative research team, the student will work with the clinical human subjects research team and gain exposure to a wide range of research activities, including: participant recruitment, supporting data collection/study visits, data collation and analysis, literature reviews, and presentation/dissemination. The student will also be exposed to many measurement tools and their data, including cognitive neuropsychological tests of brain function, virtual driving assessment, eye-tracking, personality scales, participant survey data, and more. 

The student may also have an opportunity to develop a number of valuable skills for a career in research by joining research team meetings and scientific discussions and assisting with a number of stages of the scientific research process (planning/lit reviews, testing, data collection, dissemination). We are looking for a student who is interested in quantitative research and is motivated and excited to work on this team’s projects examining the brain and behavior of young drivers. We encourage diverse majors to apply, including (but not limited to): Psychology, Neuroscience, Public Health, Health Sciences, Engineering, Biomedical Engineering, or any other related major.

Epidemiology Core

All Epidemiology Core REU students will be exposed to survey design and administration and data analysis and interpretation. They will have opportunities to submit and present their work at conferences (e.g., the American Public Health Association’s Annual Conference) with support from their mentors and participate in the preparation of publications. Students will be encouraged to work independently with appropriate mentorship, to generate enthusiasm and future career interest in epidemiology, statistics, demography, and ethnography research that links the fields of medicine and behavior to injury prevention. Students will be encouraged to work independently with appropriate mentorship and to generate enthusiasm and future career interest in epidemiology, statistics, demography, and ethnography research that links the fields of medicine and behavior to injury prevention.

The following projects will be conducted with the REU Class of 2023 students:

Epidemiology Research Projects

Project 7: Human Subject Study with Parents and Teens to Study Effectiveness of Driver Safety App 

Mentors: Morgan O’Donald, MPH; Emma Sartin, PhD

Research Description

Teen drivers are responsible for a disproportionate number of fatal crashes every year, many of which are because of distracted driving. Researchers at the Center for Injury Research and Prevention (CIRP) are conducting a research study with our business partner Minnesota Health Solutions (MHS) to address this issue. Our study includes a prospective randomized trial with teens and parents to assess the effectiveness of a novel teen driver app technology.

REU Project Description

This student will participate in many aspects of a scientific research study and will have the opportunity to gain experience in applying various skills valuable to a future career in public health, health sciences, policy, or scientific research. The student may be involved in and responsible for tasks related to: literature reviews; database creation; data collection and management; and research participant phone calls and other interactions. In addition, the student will be able to participate in research meetings, scientific discussions, and CIRP-wide research meetings. The student should be motivated, enthusiastic, dependable, and detail-oriented. Prior coursework in Public Health, Psychology, Social Work, Health Policy, Behavioral Health, Nursing, or Health Sciences and experience working with scientific data or in a scientific research setting is preferred, but not required. 

Project 8: Optimizing Concussion Care for Children and Adolescents

Mentor: Olivia Podolak, MD

Research Description

The Minds Matter Concussion Research Program informs our leading concussion care at Children’s Hospital of Philadelphia. With a diverse patient population, we rapidly translate cutting-edge research into clinical care that advances target interventions, improves diagnostics, optimizes concussion treatment, and supports better long-term outcomes for pediatric patients. We have several ongoing projects that have supported our concussion care initiatives and a new project starting that will help us understand diverse patient needs more broadly. Through collaborations with community healthcare providers, school staff, coaches, and industry partners we will investigate barriers to accessing specialized concussion care from different community locations. We hope to test alternative approaches to this care that may reduce disparities and improve outcomes to impact the lives of children more broadly.

REU Project Description

The REU student will work collaboratively with members of the CHOP Minds Matter Concussion team and gain exposure to both quantitative and qualitative research methods. Activities may include conducting semi-structured interviews; transcription, coding; entering, managing, and analyzing data from quantitative and qualitative data sources; developing a database; attending training activities and project team meetings; and presenting preliminary findings to internal and external partners. This work may be completed on-site or in the community. Competitive candidates for this position will have a demonstrated interest in public health, healthcare, and child/adolescent health issues. Prior coursework in Public Health, Psychology, Social Work, Health Policy, Behavioral Health, Nursing, or Health Sciences is required and at least one course in Research Methods is preferred.

This project is reserved for applicants from HBCUs and other Minority Serving Institutions. Find out if your school is eligible. For more information about Minority Serving Institutions, click here.

Project 9: Cognitive and Circuit Impairments Induced by Mild Traumatic Brain Injury

Mentor: Akiva Cohen, PhD

Research Description

Traumatic brain injury (TBI) is the leading cause of death and disability in children and young adults. A TBI occurs on average every 21 seconds and afflicts approximately two million people annually in the United States. No effective therapy currently exists to treat TBI.  A profound obstacle to the diagnosis and treatment of TBI is the absence of an objective, quantitative test for TBI. The difficulty in diagnosing TBI is due in large part to the overlap in symptoms between TBI and other conditions (e.g. stroke, migraine, PTSD, depression and non-convulsive seizures), as well as variability in the initial injury and clinical presentation. Therefore, we are determining the nature of a brain circuitry functional biomarker in mice that have received a mild TBI.

REU Project Description

The REU student will become a member of the Cohen Lab at the Children’s Hospital of Philadelphia Research Institute. The student will receive mentorship from the lead investigator, as well as from members of his laboratory. The student will learn various behavioral paradigms and immunohistochemistry, as well as cell counting and biochemistry. The student will also gain experience in problem-solving, data analysis, interpreting findings, and developing new research ideas. There will also be opportunities to submit and present the student's work at conferences and to participate in the preparation of journal publications.