UNMC_Acronym_Vert_sm_4c
University of Nebraska Medical Center

Selected Completed Research


  • Mapping Visual Field Defects for Distance and Determination of Compensatory Mechanisms
    PI: Deepta Ghate MD  Investigators: David Anderson MS, Sachin Kedar MD, Matthew Rizzo MD, David Warren PhD
    Funding: Great Plains IDeA-CTR
    Glaucoma is a common eye disease in older adults that impairs the visual perceptual abilities needed for safe driving in rapidly changing, complex driving environments.  Consequently, drivers with glaucoma are 3 times more likely to be involved in a traffic accident compared to the general driver population.  We have developed an innovative approach to map a glaucoma patient's visual fields in an immersive, high-fidelity simulated driving environment.  By comparing clinical visual fields with visual fields from simulated environments, we can determine how a driver's attentional load interacts with visual perceptual abilities and driving performance.  The results from this study may help to improve patient self-awareness of visual disability, the study of visual perception in glaucoma patients, and development of ADAS systems for patients with visual impairments.
  • Driving Safety and Real-Time Glucose Monitoring in Insulin-Dependent Diabetes
    PI:
     Matthew Rizzo MD  Investigators:  Cyrus Desouza MBBS, Andjela Drincic MD, Jennifer Merickel PhD, Kendra Schmid PhD
    Funding: Toyota Collaborative Safety Research Center
    This project addressed the need for in-vehicle driver-state detection using wearable and in-vehicle measurements of driver physiology and health.  We deployed a multidisciplinary approach to quantify the relationship between driver physiology and on-road safety behavior in drivers with insulin-dependent diabetes mellitus (DM).  Using this approach, we successfully demonstrated the feasibility and utility of procedures capable of quantifying real-world driving behavior to determine the level and patterns of glucose control needed to produce meaningful improvements in driver safety in drivers with DM.

    Our experimental platform included detailed, continuous measurements of naturalistic driving, glucose levels, and activity patterns in driver, with an without DM, from in-vehicle Black Box sensor instrumentation, continuous glucose monitors (CGMs), and wearable activity sensors.  This project demonstrates a new experimental platform and data relevant to improving safety and mobility in drivers with DM using a variety of in-vehicle and physiologic sensors to record real-world driver behavior.

  • Predicting Driver Safety in Parkinson's Disease
    PI:
     Ergun Uc MD  Investigator: Matthew Rizzo MD
    Funding: National Institutes of Health
    In this project, we tested subjects with Parkinson's Disease and controls on driving (using a driving simulator and an instrumented vehicle); their motor, cognitive, and visual function; and we obtained their state crash and license records longitudinally to determine predictors of driver safety in Parkinson's Disease.

  • PAP Adherence and Real-World Driving Safety in OSA
    PI: 
    Matthew Rizzo MD  Investigators: Jon Tippin MD, Steven Anderson PhD, Jeffrey Dawson ScD, Nazan Aksan PhD, Mark Dyken MD, John Lee PhD
    Funding: National Institutes of Health (Heart, Lung, and Blood)
    The broad goal of this research project was to quantify real-world driving behavior in obstructive sleep apnea (OSA) and to determine the amount of positive airway pressure (PAP) usage needed to produce meaningful improvements in real-world driver safety.  To address our specific aims, a multidisciplinary team with expertise in sleep disorders, cognitive neuroscience, driver performance assessment, human factors engineering, biostatistics and pubic policy comprehensively investigated 1) cognitive functions; 2) physiologic indices of sleep (from laboratory-based sleep studies); 3) extended measurements of real-world PAP therapy adherence, sleep patterns, and self-ratings of sleepiness and quality of life in the drivers' own homes; and 4) real-world driver strategies and tactics from Black Box recorders installed in the drivers' own cars.  The patterns of performance and behavior observed in real-world OSA drivers can be used to help formulate new experimental hypotheses and treatment strategies for other sleep disorders, as well as the broader issue of insufficient sleep in the general population.
  • Measuring Use & Impact of In-Vehicle Technologies on Older Driver Safety
    PI: 
    Matthew Rizzo MD  Investigators: Nazan Aksan PhD, Steven Anderson PhD, Jeffrey Dawson ScD, Sarah D Hacker MA, Benjamin Lester PhD, Lauren Sager MS, Shaun Vecera PhD
    Funding: Toyota Collaborative Safety Research Center
    This study evaluated the relative effectiveness of in-vehicle technologies for older and middle-aged drivers.  These technologies included three distinct Adaptive Driver Assist Systems (ADAS): Lane Deviation Warning (LDW), Forward Collision Warning (FCW), and Lane Change Merge Warning (LCMW).  This protocol included several simulated drive layouts that participants drove with and without ADAS warnings.  Electronic drive data were sampled in synch with eye tracker data.  Video analysts reviewed video for safety relevant behaviors.  A certified driver instructor evaluated safety errors on a standardized on-road drive in an instrumented vehicle.  Participants also completed a battery of tests of visual motor function and cognitive function.  Key findings concern warning system effectiveness, role of age and cognitive functioning on systems effects, and real-world validity of the findings.
  • Predictions of Driver Safety in Advancing Age: Real-World Recorders
    PI: 
    Matthew Rizzo MD  Investigators: Steven Anderson PhD, Jeffrey Dawson ScD, Jennifer Merickel PhD
    Funding: 
    National Institutes of Health (Aging)
    Drivers over the age of 60 have more crashes per mile than almost any other age group in the United States.  The goal of this controlled, longitudinal study is to improve driving safety in aging drivers and develop evidence-based criteria to develop interventions capable of improving driver awareness, safety, mobility, and quality of life.  We've equipped participants' own vehicles with advanced, in-vehicle instrumentation systems to provide direct, detailed information about each driver's behaviors and safety while navigating "the real world".  By tackling cognitive and behavioral research in real-world settings, this study provides unique data on driver exposure and safety errors and advances the NIH priority of performing translational research in the neurosciences.
  • Simulated Barrier Warnings in Military Entry Facilities
    PI: 
    Laurence Rilett PhD  Investigators: Jennifer Merickel PhD, Matthew Rizzo MD
    Funding: Department of Defense
    The purpose of this collaborative study is to improve the design of safe military entry facilities.  To do so, we are studying how military individuals respond to warning signals that alert the driver to a threat.  We are combining sophisticated graphical design to precisely simulate the visual and environmental characteristics of military entry facilities with advanced measures of driver behavior and visual attention.  The results of this study will inform design of future military entry facilities to improve driver safety and effective threat response.
  • Electrophysiological Biomarkers of Chemotherapy-Related Cognitive Impairment
    PI: 
    Vijaya Bhatt MD  Investigators: David Anderson MS, Sachin Kedar MD, Matthew Rizzo MD, Kendra Schmid MD
    Funding: UNMC Research Support Fund
    Chemotherapy-related cognitive impairment ("chemobrain") is influenced by a variety of factors, including cancer stage, treatment toxicity, and psychosocial factors.  This project aims to quantify how each of these factors affects cognitive impairment from chemotherapy, while also determining the feasibility of developing biomarkers that can detect cognitive impairments from chemotherapy.  To meet this goal, we are assessing chemotherapy-related attention impairments in patients with myelodysplastic syndrome using driving simulation and EEG.  The findings may impact the knowledge, treatment, control, and prevention of chemotherapy-related cognitive impairment in cancer survivors, while preserving their independence and quality of life.
  • Driving and Mobility Performance After Right-Sided Total Knee Arthroplasty Surgery
    PI: 
    Matthew Rizzo MD  Investigators: Kevin Garvin MD, Jennifer Merickel PhD, Bobby Muelleman BA
    Funding: UNMC
    The goal of this pilot project is to determine the evidence-based guidelines for safe driving in patients who have undergone right-sided knee replacement (TKA).  TKA impairs a driver's rapid and precise operation of vehicle controls, increasing risk of crash and injury.  Using high-fidelity driving simulation, we are quantifying safety-critical mobility inside and outside of the vehicle in TKA patients (pre- and post-surgery) compared with drivers without joint injury.  The results and design of this pilot project may be used to inform guidelines for clinical care and patient education after TKA surgery and to guide further studies in mobility recovery post-joint replacement and injury
  • Mind Share Studies: Real-World Cognitive Testing and Behavior Tracking of Individuals with Alzheimer's Disease
    PI: 
    Matthew Rizzo MD and Joan Severson MS
    Funding: Digital Artefacts LLC and UNMC
    Alzheimer's disease is a progressive neurodegenerative disorder that slowly impairs memory and thinking skills and, eventually, the ability of individuals to carry out the simplest tasks.  Most people who suffer from Alzheimer's Disease begin experiencing symptoms in their mid-60s.  Earliest symptoms include memory problems, which lead to cognitive impairment.  Mind Share Studies is a real-world study that uses the iPhone's ResearchKit and Digital Artefacts' BrainBaseline platform to reach anyone with an iPhone in the United States.  The study gathers data on cognition, behavior, and medication adherence to look at how behavior and lifestyle affect Alzheimer's disease.