Predicting mild cognitive impairment from simulated driving performance: A preliminary investigation
Related Experiment Video
Updated: Nov 5, 2026
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Stefan Delmas1, Anjali Tiwari1, Joy DeJong Lago2
1Department of Health and Exercise Science Colorado State University Fort Collins Colorado USA.
Introduction:
This study aimed to determine whether simulated driving performance in challenging environmental conditions can predict mild cognitive impairment (MCI).
Methods:
MCI (n = 37) and control (n = 42) participants completed a simulated driving scenario with two challenging sections involving inclement weather and navigating an unfamiliar environment. Speed and steering outcomes were assessed.
Results:
The inclement weather logistic regression model distinguished cognitive status with more than 75% accuracy. However, the route planning model was unable to significantly distinguish individuals based on cognitive status. Receiver operating characteristic (ROC) analyses revealed a significant area under the curve (AUC) for the inclement weather model, with an optimal cutoff yielding 78.4% apparent sensitivity.
Discussion:
The present findings highlight the potential value of simulated driving in challenging conditions as sensitive functional markers of early cognitive impairment. These preliminary findings provide the foundation for naturalistic and longitudinal studies to establish whether driving assessments can meaningfully capture functional changes associated with the onset of cognitive impairment.
