Driving Simulator Performance After Acquired Brain Injury: A Comparative Study of Neuropsychological Predictors

Acquired brain injury (ABI) often results in cognitive and motor impairments that can compromise driving ability, an essential aspect of independence and social participation. This study utilized a custom-designed driving simulator to compare driving performance between individuals with ABI and controls, and to examine the relationship between cognitive performance and driving behavior within the control group. All participants completed a series of standardized driving simulation tasks of varying complexity. The control group also completed a neuropsychological battery that assessed attention, processing speed, executive function, and visuospatial abilities. Simulator data were analyzed using generalized linear mixed models to evaluate group differences and, for the control group, cognitive predictors of performance. Results showed that individuals with ABI performed comparably to controls in basic operational tasks but demonstrated reduced performance in cognitively demanding scenarios requiring sustained attention, visuospatial monitoring, and adaptive control, such as rural driving, vehicle following, and parking. In the control group, strong associations were found between simulator outcomes and measures of attention, processing speed, and spatial orientation. The findings support the use of simulator-based assessment as an objective tool sensitive to post-injury impairments and highlight its links to cognitive domains relevant to driving.

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Publication Details

Journal
Big Data and Cognitive Computing
Published
2026-01-06
DOI
https://doi.org/10.3390/bdcc10010020
Primary Topic
Older Adults Driving Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Driving Simulator Performance After Acquired Brain Injury: A Comparative Study of Neuropsychological Predictors

Jan Hejda, Patrik Kutílek, Jiří Remr, Lýdie Leová et al.
Big Data and Cognitive Computing
Older Adults Driving Studies
article

Driving Simulator Performance After Acquired Brain Injury: A Comparative Study of Neuropsychological Predictors

Jan Hejda, Patrik Kutílek, Jiří Remr, Lýdie Leová, Marek Sokol, Petr Volf
article en

Abstract

Acquired brain injury (ABI) often results in cognitive and motor impairments that can compromise driving ability, an essential aspect of independence and social participation. This study utilized a custom-designed driving simulator to compare driving performance between individuals with ABI and controls, and to examine the relationship between cognitive performance and driving behavior within the control group. All participants completed a series of standardized driving simulation tasks of varying complexity. The control group also completed a neuropsychological battery that assessed attention, processing speed, executive function, and visuospatial abilities. Simulator data were analyzed using generalized linear mixed models to evaluate group differences and, for the control group, cognitive predictors of performance. Results showed that individuals with ABI performed comparably to controls in basic operational tasks but demonstrated reduced performance in cognitively demanding scenarios requiring sustained attention, visuospatial monitoring, and adaptive control, such as rural driving, vehicle following, and parking. In the control group, strong associations were found between simulator outcomes and measures of attention, processing speed, and spatial orientation. The findings support the use of simulator-based assessment as an objective tool sensitive to post-injury impairments and highlight its links to cognitive domains relevant to driving.

Big Data and Cognitive ComputingVol. 10(1)
Institute for Evaluation and Social Analyses (CZ), Czech Technical University in Prague (CZ)
Reduced inequalities
Openalex Percentile: Top 97%
Older Adults Driving Studies
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Driving Simulator Performance After Acquired Brain Injury: A Comparative Study of Neuropsychological Predictors — Jan Hejda, Patrik Kutílek, et al. · Big Data and Cognitive Computing (2026) | TGRS Research Map | TGRS