Smart Driving Technology for Non-Invasive Detection of Age-Related Cognitive Decline

Overview

Journal Sensors (Basel)

Publisher MDPI

Specialty Biotechnology

Date 2025 Jan 8

PMID 39771798

Authors

Peter Serhan

Shaun Victor

Oscar Osorio Perez

Kevin Abi Karam

Anthony Elghoul

Madison Ransdell

Firas Al-Hindawi

Yonas Geda

Geetika Chahal

Danielle Eagan

Teresa Wu

Francis Tsow

Erica Forzani

Affiliations

Soon will be listed here.

Abstract

Alzheimer's disease (AD) and Alzheimer's Related Dementias (ADRD) are projected to affect 50 million people globally in the coming decades. Clinical research suggests that Mild Cognitive Impairment (MCI), a precursor to dementia, offers a critical window of opportunity for lifestyle interventions to delay or prevent the progression of AD/ADRD. Previous research indicates that lifestyle changes, including increased physical exercise, reduced caloric intake, and mentally stimulating activities, can reduce the risk of MCI. Early detection of MCI is challenging due to subtle and often unnoticed cognitive decline and is traditionally monitored through infrequent clinical tests. In this research, the Smart Driving System, a novel, unobtrusive, and economical technology to detect early stages of neurodegenerative diseases, is presented. The system comprises a multi-modal biosensing array (MMS) and AI algorithms, including driving performance and driver's biometrics, offering insights into a driver's cognitive function. This publication is the first work reported towards the ultimate goal of developing the Smart Driving Device and App, integrating it into vehicles, and validating its effectiveness in detecting MCI through comprehensive pilot studies.

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