Description
Alzheimer's disease (AD) and Alzheimer's Related Dementias (ADRD) is 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 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 exercises, can reduce the risk of MCI. Early detection of MCI is challenging due to subtle and often unnoticed cognitive decline, traditionally monitored through infrequent clinical tests. As part of this research, the Smart Driving System was proposed, a novel, unobtrusive, and economical technology to detect early stages of neurodegenerative diseases. This system, leveraging a multi-modal biosensing array (MMS) and AI algorithms, assesses daily driving behavior, offering insights into a driver's cognitive function. The ultimate goal is to develop the Smart Driving Device and App, integrating it into vehicles, and validating its effectiveness in detecting MCI through comprehensive pilot studies. The Smart Driving System represents a breakthrough in AD/ADRD management, promising significant improvements in early detection and offering a scalable, cost-effective solution for monitoring cognitive health in real-world settings.
Details
Title
- Smart Driving Technology for Non-Invasive Detection of Age-Related Cognitive Decline
Contributors
- Serhan, Peter (Author)
- Forzani, Erica (Thesis advisor)
- Wu, Teresa (Committee member)
- Hihath, Joshua (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2024
Subjects
Resource Type
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Note
- Partial requirement for: M.S., Arizona State University, 2024
- Field of study: Electrical Engineering