# Sensor-Detected Differences in Behaviors of Older Drivers with Pre-MCI and Mild Cognitive Impairment vs. Unimpaired Drivers

## TL;DR

Older drivers with early cognitive impairment show distinct driving patterns compared to unimpaired drivers, as detected by vehicle sensors.

## Contribution

This study identifies specific sensor-based driving behaviors that distinguish older drivers with pre-MCI/MCI from unimpaired drivers.

## Key findings

- Higher RPM, shorter trips, and greater throttle variability were linked to Pre-MCI/MCI drivers.
- Unimpaired drivers exhibited more frequent hard braking, hard turns, and steadier pedal control.
- Driving behavior patterns, not single behaviors, differentiate cognitive impairment levels.

## Abstract

What are the main findings?
Higher RPM, shorter average trips, and greater throttle variability were characteristic of drivers with Pre-MCI/MCI.More frequent hard braking, hard turns, higher mean speed, and lower average throttle (steadier pedal control) were characteristic of unimpaired drivers.

Higher RPM, shorter average trips, and greater throttle variability were characteristic of drivers with Pre-MCI/MCI.

More frequent hard braking, hard turns, higher mean speed, and lower average throttle (steadier pedal control) were characteristic of unimpaired drivers.

What are the implications of the main findings?
The results support the hypothesis that driving behaviors of individuals with early (preclinical) impairment of cognition differ from those who are unimpaired.The differences observed are based upon the patterns of driving behaviors exhibited rather than in a single behavior.

The results support the hypothesis that driving behaviors of individuals with early (preclinical) impairment of cognition differ from those who are unimpaired.

The differences observed are based upon the patterns of driving behaviors exhibited rather than in a single behavior.

Background: Research to identify changes in driving behavior that occur with the onset of Pre-MCI and MCI is an emerging area with many gaps still to be addressed. These gaps include limited use of objective, continuous measurement of driver behavior in real-life traffic conditions and comprehensive, biomarker-validated, cognitive evaluation based upon both testing and clinical ratings. Using these strategies, the questions addressed in this exploratory study are whether or not differences in driving behavior are indicative of Pre-MCI/MCI and which behaviors are most predictive of Pre-MCI/MCI. Methods: As part of a naturalistic longitudinal study, older drivers with a Montreal Cognitive Assessment score ≥ 19 had telematic sensors installed in their vehicles and underwent comprehensive cognitive assessment quarterly for three years. Thirty-six participants were classified as Unimpaired (n = 23) or Pre-MCI/MCI (n = 10/3) based upon a neuropsychological battery and diagnostic algorithm. A penalized generalized linear mixed-effects model (GLMM) with a logistic link and LASSO regularization was used to model Pre-MCI/MCI group membership vs. unimpaired as a function of ten trip-level telematic features (trip distance, hard acceleration, hard braking, hard turns, speed average, maximum speed, RPM average, fuel level, throttle average, and throttle variability) at the end of their first 12 months in the study. Results: Higher RPM, shorter average trips, and greater throttle variability predicted higher odds of Pre-MCI/MCI, while more frequent hard braking, hard turns, higher mean speed, and lower average throttle (steadier pedal control) predicted lower odds of Pre-MCI/MCI. Conclusions: The model clearly distinguished unimpaired older drivers from those with MCI or Pre-MCI, suggesting that distinct patterns of driver behavior may be related to levels of cognitive function.