Dataset Information

EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers.

ABSTRACT: The number of older drivers is steadily increasing, and advancing age is associated with a high rate of automobile crashes and fatalities. This can be attributed to a combination of factors including decline in sensory, motor, and cognitive functions due to natural aging or neurodegenerative diseases such as HIV-Associated Neurocognitive Disorder (HAND). Current clinical assessment methods only modestly predict impaired driving. Thus, there is a need for inexpensive and scalable tools to predict on-road driving performance. In this study EEG was acquired from 39 HIV+ patients and 63 healthy participants (HP) during: 3-Choice-Vigilance Task (3CVT), a 30-min driving simulator session, and a 12-mile on-road driving evaluation. Based on driving performance, a designation of Good/Poor (simulator) and Safe/Unsafe (on-road drive) was assigned to each participant. Event-related potentials (ERPs) obtained during 3CVT showed increased amplitude of the P200 component was associated with bad driving performance both during the on-road and simulated drive. This P200 effect was consistent across the HP and HIV+ groups, particularly over the left frontal-central region. Decreased amplitude of the late positive potential (LPP) during 3CVT, particularly over the left frontal regions, was associated with bad driving performance in the simulator. These EEG ERP metrics were shown to be associated with driving performance across participants independent of HIV status. During the on-road evaluation, Unsafe drivers exhibited higher EEG alpha power compared to Safe drivers. The results of this study are 2-fold. First, they demonstrate that high-quality EEG can be inexpensively and easily acquired during simulated and on-road driving assessments. Secondly, EEG metrics acquired during a sustained attention task (3CVT) are associated with driving performance, and these metrics could potentially be used to assess whether an individual has the cognitive skills necessary for safe driving.

SUBMITTER: Rupp G

PROVIDER: S-EPMC6341028 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers.

Rupp Greg G Berka Chris C Meghdadi Amir H AH Karić Marija Stevanović MS Casillas Marc M Smith Stephanie S Rosenthal Theodore T McShea Kevin K Sones Emily E Marcotte Thomas D TD

Frontiers in human neuroscience 20190115

The number of older drivers is steadily increasing, and advancing age is associated with a high rate of automobile crashes and fatalities. This can be attributed to a combination of factors including decline in sensory, motor, and cognitive functions due to natural aging or neurodegenerative diseases such as HIV-Associated Neurocognitive Disorder (HAND). Current clinical assessment methods only modestly predict impaired driving. Thus, there is a need for inexpensive and scalable tools to predict ...[more]

PMID: 30697156

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Project description:BACKGROUND: In many countries, primary care physicians determine whether or not older drivers are fit to drive. Little, however, is known regarding the effects of cognitive decline on driving performance and the means to detect it. This study explores to what extent the trail making test (TMT) can provide indications to clinicians about their older patients' on-road driving performance in the context of cognitive decline. METHODS: This translational study was nested within a cohort study and an exploratory psychophysics study. The target population of interest was constituted of older drivers in the absence of important cognitive or physical disorders. We therefore recruited and tested 404 home-dwelling drivers, aged 70 years or more and in possession of valid drivers' licenses, who volunteered to participate in a driving refresher course. Forty-five drivers also agreed to undergo further testing at our lab. On-road driving performance was evaluated by instructors during a 45 minute validated open-road circuit. Drivers were classified as either being excellent, good, moderate, or poor depending on their score on a standardized evaluation of on-road driving performance. RESULTS: The area under the receiver operator curve for detecting poorly performing drivers was 0.668 (CI95% 0.558 to 0.778) for the TMT-A, and 0.662 (CI95% 0.542 to 0.783) for the TMT-B. TMT was related to contrast sensitivity, motion direction, orientation discrimination, working memory, verbal fluency, and literacy. Older patients with a TMT-A???54 seconds or a TMT-B???150 seconds have a threefold (CI95% 1.3 to 7.0) increased risk of performing poorly during the on-road evaluation. TMT had a sensitivity of 63.6%, a specificity of 64.9%, a positive predictive value of 9.5%, and a negative predictive value of 96.9%. CONCLUSION: In screening settings, the TMT would have clinicians uselessly consider driving cessation in nine drivers out of ten. Given the important negative impact this could have on older drivers, this study confirms the TMT not to be specific enough for clinicians to justify driving cessation without complementary investigations on driving behaviors.

Project description:BACKGROUND:Distracted driving attributable to the performance of secondary tasks is a major cause of motor vehicle crashes both among teenagers who are novice drivers and among adults who are experienced drivers. METHODS:We conducted two studies on the relationship between the performance of secondary tasks, including cell-phone use, and the risk of crashes and near-crashes. To facilitate objective assessment, accelerometers, cameras, global positioning systems, and other sensors were installed in the vehicles of 42 newly licensed drivers (16.3 to 17.0 years of age) and 109 adults with more driving experience. RESULTS:During the study periods, 167 crashes and near-crashes among novice drivers and 518 crashes and near-crashes among experienced drivers were identified. The risk of a crash or near-crash among novice drivers increased significantly if they were dialing a cell phone (odds ratio, 8.32; 95% confidence interval [CI], 2.83 to 24.42), reaching for a cell phone (odds ratio, 7.05; 95% CI, 2.64 to 18.83), sending or receiving text messages (odds ratio, 3.87; 95% CI, 1.62 to 9.25), reaching for an object other than a cell phone (odds ratio, 8.00; 95% CI, 3.67 to 17.50), looking at a roadside object (odds ratio, 3.90; 95% CI, 1.72 to 8.81), or eating (odds ratio, 2.99; 95% CI, 1.30 to 6.91). Among experienced drivers, dialing a cell phone was associated with a significantly increased risk of a crash or near-crash (odds ratio, 2.49; 95% CI, 1.38 to 4.54); the risk associated with texting or accessing the Internet was not assessed in this population. The prevalence of high-risk attention to secondary tasks increased over time among novice drivers but not among experienced drivers. CONCLUSIONS:The risk of a crash or near-crash among novice drivers increased with the performance of many secondary tasks, including texting and dialing cell phones. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Highway Traffic Safety Administration.).

Project description:ObjectiveDaily cannabis users develop tolerance to some drug effects, but the extent to which this diminishes driving impairment is uncertain. This study compared the impact of acute cannabis use on driving performance in occasional and daily cannabis users using a driving simulator.MethodsWe used a within-subjects design to observe driving performance in adults age 25 to 45 years with different cannabis use histories. Eighty-five participants (43 males, 42 females) were included in the final analysis: 24 occasional users (1 to 2 times per week), 31 daily users and 30 non-users. A car-based driving simulator (MiniSim™, National Advanced Driving Simulator) was used to obtain two measures of driving performance, standard deviation of lateral placement (SDLP) and speed relative to posted speed limit, in simulated urban driving scenarios at baseline and 30 min after a 15 min ad libitum cannabis smoking period. Participants smoked self-supplied cannabis flower product (15% to 30% tetrahydrocannabinol (THC). Blood samples were collected before and after smoking (30 min after the start of smoking). Non-users performed the same driving scenarios before and after an equivalent rest interval. Changes in driving performance were analyzed by repeated measures general linear models.ResultsMean whole blood THC cannabinoids concentrations post smoking were use THC = 6.4 ± 5.6 ng/ml, THC-COOH = 10.9 ± 8.79 ng/mL for occasional users and THC = 36.4 ± 37.4 ng/mL, THC-COOH = 98.1 ± 90.6 ng/mL for daily users. On a scale of 0 to 100, the mean post-use score of subjective high was similar in occasional users and daily users (52.4 and 47.2, respectively). In covariate-adjusted analysis, occasional users had a significant increase in SDLP in the straight road segment from pre to post compared to non-users; non-users decreased by a mean of 1.1 cm (25.5 cm to 24.4 cm) while occasional users increased by a mean of 1.9 cm (21.7 cm to 23.6 cm; p = 0.02). Daily users also increased adjusted SDLP in straight road segments from baseline to post-use (23.2 cm to 25.0 cm), but the change relative to non-users was not statistically significant (p = 0.08). The standardized mean difference in unadjusted SDLP from baseline to post-use in the straight road segments comparing occasional users to non-users was 0.64 (95% CI 0.09 - 1.19), a statistically significant moderate increase. When occasional users were contrasted with daily users, the baseline to post changes in SDLP were not statistically significant. Daily users exhibited a mean decrease in baseline to post-use adjusted speed in straight road segments of 1.16 mph; a significant change compared to slight speed increases in the non-users and occasional users (p = 0.02 and p = 0.01, respectively).ConclusionWe observed a decrement in driving performance assessed by SDLP after acute cannabis smoking that was statistically significant only in the occasional users in comparison to the nonusers. Direct contrasts between the occasional users and daily users in SDLP were not statistically significant. Daily users drove slower after cannabis use as compared to the occasional use group and non-users. The study results do not conclusively establish that occasional users exhibit more driving impairment than daily users when both smoke cannabis ad libitum.

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Dataset Information

EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers.

Publications

EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers.

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