Division of Neuroergonomics

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.  

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. 

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.  

Driving with Obstructive Sleep Apnea Syndrome

Matthew Rizzo M.D., , John Lee Ph.D., Jeffrey Dawson Sc.D., Jon Tippin M.D.

The primary purposes of this research are 1) determine to what extent drivers with OSAS are aware of their decreased arousal, based on a comparison between physiologic indices of sleep and report of sleepiness on a standard sleep questionnaire; 2) assess to what extent drivers with OSAS are aware of cognitive impairment, based on comparison between standardized cognitive tests and an awareness of acquired impairment inventory; 3) investigate which drivers with OSAS are aware of falling asleep at the wheel based on physiologic indices of sleep during driving, self-assessment of driving performance, and awareness of impairments; 4) assess to what extent treatment of OSAS with continuous positive airway pressure (CPAP) leads to improvement in cognitive function, driving performance, and awareness of impairments; 5) identify potential screening, identifying, and warning drivers with OSAS who are at risk for impaired driving due to drowsiness and lack of insight into their impairment. 

Enhancing Mobility in the Elderly

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

Cognitive training technique transfers to improvement in cognitive abilities measured on neuropsychological tests and improvement in instrumentes 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.  

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.  

Prediction of Driver Safety in Advancing Age

Matthew Rizzo M.D., 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. 

Prediction of Driver Safety in Parkinson's disease

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

Safe and Unsafe Driving in Alzheimer's disease and Stroke

Matthew Rizzo M.D., 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 Alzhemier'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. 

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. Thomas Pietras is currently coordinating this work.