Driving as a Diagnostic Tool: Scenario-based Cognitive Assessment in Older Drivers From Driving Video
Journal:
arXiv
Published Date:
Jul 7, 2025
Abstract
We introduce scenario-based cognitive status identification in older drivers
from Naturalistic driving videos and large vision models. In recent times,
cognitive decline, including Alzheimer's disease (AD) and mild cognitive
impairment (MCI), is often underdiagnosed due to the time-consuming and costly
nature of current diagnostic methods. By analyzing real-world driving behavior
captured through in-vehicle systems, this research aims to extract "digital
fingerprints" that correlate with functional decline and clinical features of
MCI and AD. Moreover, modern large vision models can draw meaningful insights
from everyday driving patterns of older patients to early detect cognitive
decline. We propose a framework that uses large vision models and naturalistic
driving videos to analyze driver behavior, classify cognitive status and
predict disease progression. We leverage the strong relationship between
real-world driving behavior as an observation of the current cognitive status
of the drivers where the vehicle can be utilized as a "diagnostic tool". Our
method identifies early warning signs of functional impairment, contributing to
proactive intervention strategies. This work enhances early detection and
supports the development of scalable, non-invasive monitoring systems to
mitigate the growing societal and economic burden of cognitive decline in the
aging population.
