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Current Research


Adaptive Warning Systems

Participants Needed

PI: Matthew Rizzo M.D. Investigators: Nazan Aksan Ph.D., Steve Anderson Ph.D., Jeffrey Dawson Sc.D., Sarah Hacker B.A., Ben Lester Ph.D., Shaun Vecera Ph.D.
Funding: Toyota, Nissan

Drivers over the age of 60 encounter some of the highest crash rates per mile, topped only by those caused by risky and much less experienced drivers under the age of 25. The causal pathway often involves a number of factors, some of which can be prevented or controlled. For instance, age-related declines in cognitive, perceptual, and motor abilities decrease driver abilities to cope with increasing complexity associated with new technology.

This research project aims to implement a specific plan for measuring use and impact of in-vehicle technologies by older drivers who are at increased risk for driving performance and safety errors due to effects of attentional decline. The study will examine young and aging populations and assess their levels of functioning using a battery of neuropsychological tests, an on road drive in NIRVANA around Iowa City, as well as a series of drives in the SIREN driving simulator.


Driving with Obstructive Sleep Apnea Syndrome

Participants Needed

PI: Matthew Rizzo M.D. Investigators: Nazan Aksan Ph.D., Steve Anderson Ph.D., Jeffrey Dawson Sc.D., Mark Dyken M.D., John Lee Ph.D., Jon Tippin M.D.
Funding: National Institutes of Health

Obstructive sleep apnea (OSA) is a chronic disorder associated with repeated episodes of complete or partial collapse of the upper airway during sleep. These episodes lead to fragmented sleep and intermittent oxygen desaturation, which results in excessive daytime sleepiness (EDS) and increased cardiovascular morbidity and mortality. Results of epidemiologic studies show that individuals with OSA, as a group, are at greatly increased risk for a motor vehicle crash compared to drivers without the disorder.

Positive airway pressure (PAP) is considered the treatment of choice in the management of patients with clinically significant OSA. PAP reverses the upper airway collapse in OSA patients by delivering pressurized air through either a nasal or oral-nasal mask sufficient to "splint" open the airway. By providing a patent airway, PAP is able to prevent obstructive respiratory events, thereby improving cognition in many patients.

We are conducting a study with individuals with OSA who are legally licensed and actively driving to further investigate the relationship between OSA and PAP treatment. The broad goals of this research project are to quantify real-world driving behavior in OSA and to determine the amount of PAP usage needed to produce meaningful improvements in driver safety.

The results of this study will provide unique, community-based data samples on performance outcomes from unprecedented exposure data on driving in OSA and normal comparison subjects. Also, this project will help determine the factors that predict residual impairments in real-world driving performance in drivers with OSA after adjusting for levels of PAP use.


Attentional Disengagement

Participants Needed

PI: Matthew Rizzo M.D. Investigators: Ben Lester Ph.D., Shaun Vecera Ph.D.
Funding: Toyota, Nissan

Licensed drivers ages 60 years old and above have among the highest crash rates per mile of all age groups, approaching the rate of the risky and much less experienced cohort of drivers less than 25 years old (NHTSA, 2008). The increased crash risk for the older driver is probably due to medical factors (e.g., visual, neurological) that accompany aging, rather than just age itself. To identify ways to enhance older driver safety and mobility, it is necessary to obtain accurate and objective measures of older driver behavior and safety errors and to develop means to mitigate these errors.

The goal of this project is to collect a preliminary dataset consisting of both neurocognitive attention related tasks and on-road driving performance of elderly drivers and to analyze the relationship between them in order to provide base theory for an onboard cognitive diagnosis algorithm.


Predicting Driver Safety: Real World Recorders

Participants Needed

PI: Matthew Rizzo M.D. Investigators: Nazan Aksan Ph.D., Steve Anderson Ph.D., Jeff Dawson Sc.D.
Funding: National Institutes of Health

The broad goal of this longitudinal research project is to improve predictions of driver safety in advancing age. Data will be recorded utilizing a comprehensive, multidisciplinary approach in older drivers without impairment, as well as those with mild cognitive impairments to mild dementia.

This project will utilize a camera to observe day-to-day driving exposure in the real world in conjunction with continuous monitoring of electronic outputs from state-of-the-art black box recorders. The study seeks to inform us on how real-world driving performance declines and how driving exposure and self-awareness affect older driver safety. Resulting data can inform policies for driver licensure (e.g., graded restriction) and future safety interventions (e.g., educational) that seek to prevent injury while preserving mobility and quality of life in advancing age.


Countermeasures

PI: Matthew Rizzo M.D. Investigators: Steve Anderson Ph.D., Jeff Dawson Sc.D., John Lee Ph.D., Monica Lees Ph.D., Michelle Rusch Ph.D., Shaun Vecera Ph.D.
Funding: National Institutes of Health

The broad goals of this research project are to identify patterns of driving performance and safety errors resulting from age-related impairments in the useful field of view (UFOV), and to develop in-vehicle countermeasures that decrease crash risk and increase safety and mobility.

Over the course of this study we intend to determine optimal signal parameters for a driver alerting and collision warning device. As an outcome of the study we intend to be able to make recommendations on promising collision warning devices for at-risk drivers with UFOV loss, develop basic information on real-world driving strategies in people at risk for collisions, understand the efficacy of basic warning signal parameters and how they differ in cognitively impaired and normal drivers, and develop tools for possible clinical trials in drivers who have a variety of medical impairments. The result may be used to design safer automobiles that use new strategies and technologies for collision warning, perceptual augmentation, and attention management.


Driving Safety in Diabetes

PI: Matthew Rizzo M.D. Investigators: Jeff Dawson Sc.D., Joseph Dillon M.D., Gregory Doelle M.D., Satoshi Kitazaki Ph.D., William Sivitz M.D.
Funding: National Institutes of Health

This pilot project aims to prove the feasibility and utility of a system and procedures capable of quantifying real-world driving behavior and determining the level and patterns of glucose control needed to produce meaningful improvements in driver safety in type 1 diabetes mellitus (T1DM).

Individuals with DM, as a group, are at significantly increased risk for a motor vehicle crash compared to drivers without the disorder. Hypoglycemia is a key factor in this increased risk, particularly in type 1 DM. Hypoglycemia impairs alertness, judgment, and the decision-making abilities needed to safely drive a motor vehicle, causing behavior and performance impairments that increase the risk of driver errors that may lead to a crash. Further, some drivers with DM are unaware of their hypoglycemic status and are particularly liable to drive while impaired.

This project seeks to determine real-work driving performance in drivers with T1DM, determine the relationship between glucose control and driver safety, and evaluate the relationship between hypoglycemic unawareness and real-world driving safety in T1DM.


Traumatic Brain Injury: Sensors to track quality of life

PI: Matthew Rizzo M.D. Investigators: Nazan Aksan Ph.D., Steve Anderson Ph.D., Jeff Dawson Sc.D.
Funding: National Institutes of Health

The study will be designed to collect preliminary data to test whether a sensor system can track everyday activities such as having a meal, taking a walk, engaging in moderately intense exercise, and social conversation. The sensor system is composed of a cell phone and wrist-worn accelerometer. Data will be collected on both structured and unstructured activities and then reviewed with the intent of establishing unique signatures for activities of interest.


Augmented Reality Cues and Driver Hazard Perception

PI: Matthew Rizzo M.D. Investigators: John Lee Ph.D., Michelle Rusch Ph.D., Shaun Vecera Ph.D.

On-board driver assist applications may improve the ability to perceive and react to roadway hazards in drivers with age related visual information processing impairments. By directing a driver's attention to where it is needed, these systems may produce safety benefits such as reduced response times (RTs) to hazardous situations, reduced collision involvement, and increased headway time.

One type of driver assist technology currently being investigated is augmented reality (AR). AR refers to the combining of real and artificial stimuli, with the aim to improve human performance. This typically involves overlaying computer-generated graphics so that these virtual objects appear to be embedded in the real world. The augmentation may highlight important objects or regions, superimpose informative annotations, or supplement a real environment.

We are investigating if AR cues can really help motor vehicle drivers, especially older drivers, to drive safely and to avoid road hazards. This line of research examines alerting effectiveness through the use of our high-fidelity driving simulator SIREN.


Diagnostic Tools for Identifying Sleepy Drivers

PI: Matthew Rizzo M.D. Investigators: Steven Anderson Ph.D., Jeffrey Dawson Sc.D., Jon Tippin M.D.
Funding: Iowa Department of Transportation

The purpose of this research study is to identify and evaluate a set of tools that can assist Iowa Motor Vehicle Enforcement Officers on duty in identifying drivers who are practicing sleep impaired driving.


Effects of Drugs on Cognition and Driving

Many drivers use prescription drugs (e.g. antiepileptics, antihistimines). Others use recreational drugs of abuse such as alcohol, marijuana, and the "party drug" Ecstasy (MDMA). We are studying the effects of such drugs on perception, cognition (e.g. decision making), driver performance, and safety errors.


Safe and Unsafe Driving in Alzheimer's disease and Stroke

PI: Matthew Rizzo M.D. Investigators: Steven Anderson Ph.D., Jeffrey Dawson Sc.D.

The study aims to identify valid and pragmatic off-road measures of cognitive and visuospatial abilities that can be used to predict safe and unsafe driving abilities in elderly drivers at risk for impaired driving. We are using a comprehensive approach to evaluating automobile driving in at-risk drivers, through the study of neuropsychological test performances, State driving records, and driving performance in the instrumented vehicle ARGOS and the driving simulator, SIREN. We are studying community dwelling older adults who are legally licensed and still actively driving. This includes drivers with cognitive deficits due to Alzheimer's disease and stroke, and older drivers without neurological disease. By analyzing the performance of these drivers in ARGOS, SIREN, and on a battery of cognitive and visuoperceptual tests, and with respect to actual State driving records, we will objectively determine which performance factors best discriminate between safe and unsafe drivers. One of the ultimate goals of this line of research is to develop fair and accurate criteria to predict driving ability in elderly populations at risk for cognitive disability.


Memory Disorders Registry

Volunteers Invited - Memory Disorders Registry

This is a registry for research involving memory disorders and other cognitive changes that often occur with aging. The purpose is to establish a registry of older persons who may be willing to participate in studies designed to learn more about memory disorders associated with aging. The information collected in the registry will enable the investigators to learn more about the risk factors that may be associated with these cognitive changes.


Driving Studies Registry

Volunteers Invited - Driving Studies Registry

This is a registry for persons interested in participating in our real world driving studies or research using the SIREN driving simulator. The purpose is to establish a registry of drivers who may be willing to participate in studies to learn more about factors that may influence driving (e.g. hazard perception ability, cognitive ability). The information collected in the registry will enable the investigators to learn more about different driver populations, their crash risk, and/or the effectiveness of different crash countermeasures (e.g. collision warning technology).


Completed Research


Abstract Virtual Environments

We are investigating the utility of surreal simulated environments in assessing abilities that are critical to real world tasks. We are developing the simulator tools to perform these assessments in close collaboration with Digital Artefacts. Current projects include Go No-Go and "Mudsplash" scenarios.


Enhancing Mobility in the Elderly

PI: Matthew Rizzo M.D. Investigators: Steven Anderson Ph.D., Karlene Ball Ph.D., Jeffrey Dawson Sc.D.

Cognitive training technique transfers to improvement in cognitive abilities measured on neuropsychological tests and improvement in instrumented activities of daily living, specifically, safely driving a motor vehicle. Participants are legally licensed elderly drivers who are at risk for unsafe driving due to age-related impairments of visual processing speed, and attention (divided, selective) leading to a decrease in the useful field of view. Driving measures depend on testing in ARGOS and in a driving simulator located at UAB. The cognitive intervention uses speed of processing training. A control condition uses an internet training protocol.


Eye Movements and Cognition

Eye movements provide a window on visual search and cognition. For example, during driving a driver's fixations are directed toward the focus of expansion of optical flow that defines the direction of forward travel. Eye movements are also directed to salient signals from the bottom-up (e.g., to irrelevant "mudsplashes") and based on top-down search strategies.


Prediction of Driver Safety in Parkinson's disease

PI: Matthew Rizzo M.D. Investigators: Steven W. Anderson Ph.D., Jeff Dawson Sc.D., Ergun Uc M.D.

Parkinson's Disease (PD) is a progressive neurogenerative disorder that causes motor, cognitive, and sleep disturbances, all of which can contribute to unsafe driving. The disease starts in mid- or late-life and generally progresses over 15-20 years, but patients often try to maintain their professional activities and social responsibilities, especially during the first decade of the illness. Automobile driving is a crucial factor in maintaining this independence, yet automobile crashes pose a serious public health problem, inflicting great suffering upon individuals and severe costs to society. The diagnosis of PD alone, however, is not a reliable criterion for determining fitness to drive. We need criteria that are objective, have been derived empirically and can be applied to each driver's performance on standardized tests that assess specific motor and cognitive deficits known to occur in PD and likely to impair driving. In the mean time, there is little agreement on how to advise individuals with PD, their families, and licensing authorities about whether an individual with PD can drive safely, or even be tested safely on the road.

We are conducting a controlled-longitudinal study with individuals with PD who are legally licensed and still actively driving. The design of this study has been aided by a pilot study which was funded by the CPH/COM New Investigator Research Award to Dr. Uc. Each subject's driving ability is evaluated using a driving simulator (SIREN), an instrumented vehicle (ARGOS), and State driving records. We use a comprehensive battery of "off-road" tests to measure motor function in PD, cognition, and daytime arousal and determine the extent of each factor's contribution to specific driving errors and crashes. These data will enable us to develop a predictive model of driving with specific off-road measures that can be used to predict an individual driver's performance, safety errors and crashes. With annual follow-up studies in subjects with PD, we will assess the stability of on- and off-road driving measures and the occurrence of crashes, the extent to which decline in motor and cognitive abilities results in further decline in driving performance, and the validity of the predictive model.


Prediction of Driver Safety in Parkinson's disease: Intervention

PI: Matthew Rizzo M.D. Investigators: Steven W. Anderson Ph.D., Jeff Dawson Sc.D., Ergun Uc M.D.

Based on our own and other researchers' empirical findings on the types and circumstances of common safety errors and poor driving performance, as well as upon the underlying causes and mechanisms of driving problems in Parkinson's Disease (PD), we have devised a new intervention for at-risk drivers with PD. The intervention consists of a systematic review of each subject's own road drive in an instrumented vehicle using verbal, video, and written feedback, followed by simulator training sessions for collision avoidance and interaction with traffic. We will compare the effects of this new intervention on driving safety measures against a standard older driver intervention (AARP-Driver Safety Program).

Understanding of crash risk and the development of fair and accurate performance criteria to predict driving ability in PD, as well as development of effective rehabilitation programs for impaired drivers with PD, will reduce the risk of motor vehicle crashes and help protect and preserve the rights and mobility of these patients by avoiding undue revocation of driving freedoms.


Traffic Entry Judgments

Ongoing studies are assessing traffic entry judgments by drivers with differing visual and cognitive abilities. These studies make use of our instrumented vehicle, ARGOS, and a LIDAR (light detection and ranging) system to measure speed and distance of oncoming vehicles.



Immobilization

Simple mobility impairments may be highly deleterious to driving. Recent investigations with Neurosurgery and Orthopedic Surgery have addressed effects of cervical immobility and limb immobility.


Attention Studies

Attention comprises a set of mechanisms that improve our abilities to perceive, conceive, and perform on all manners of tasks. For example, automobile driving performance depends highly on visual attention. We are studying basic attention mechanisms in normal and neurologically impaired subjects (e.g. with stroke, Alzheimer's disease, head injury, herpes simplex encephalitis) using a broad range of psychophysical and cognitive assessment tools. This includes studies of the "attentional blink", "change blindness" and hazard perception.


Prediction of Driver Safety in Advancing Age

PI: Matthew Rizzo M.D. Investigators: Steven Anderson Ph.D., Jeffrey Dawson Sc.D., John Lee Ph.D.

The specific aims of this study are as follows: 1) comprehensively assess driving abilities in older individuals who are legally licensed and still actively driving. Driving is evaluated using SIREN, ARGOS and State driving records; 2) Analyze the performance of every driver on a battery of "off-road" cognitive tests aimed at measuring several aspects of visual, perceptual and visuomotor abilities, attention, memory, and executive functions; determine which cognitive impairments contribute most importantly to specific driving errors and crashes based on driver performance using the measures described above; 3)Develop a predictive model of driving whereby specific off-road measures can be used to predict an individual driver's performance, safety errors and crashes; 4) Follow up with the drivers to assess (a) stability of off-road measures and occurrence of crashes, (b) extent to which decline in cognitive abilities results in further decline in driving performance, and (c) validity of the predictive model.