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2023 Advancing Research on Care and Outcome Measurements (ARCOM)

Using Mobile Technology to Inform Driving Decision-Making in Dementia

Could state-of-the-art technology recognize the driving habits of individuals with cognitive decline?

Mark Rapoport, M.D.
Sunnybrook Research Institute
Toronto, Canada



Background

Driving safety is a particular concern for older adults at risk of developing Alzheimer’s and their caregivers. Although many older adults are able to drive with little to no impairment, they are at a higher risk of being involved in an accident than middle-aged adults. Many caregivers face a difficult challenge in recognizing when an older adult’s driving has become dangerous.

Previous research has shown that age, genetic, and simple driving data (GPS and accelerations) used together can help identify preclinical Alzheimer’s better than genetic tests alone. To better understand this, Dr. Mark Rapoport and colleagues have developed a state-of-the-art driving monitoring system that can track additional driving details such as brake response times, merges, and lane changes. This system mounts below the rearview mirror and is equipped with sensors and cameras that capture activity both inside and outside of the car.

Research Plan

Dr. Rapoport plans to test the ability of their monitoring system to distinguish older drivers with different levels of cognitive impairment, and whether the system is useful to inform driving decision-making among older adults. The researchers will enroll 60 older adults in their study: 20 healthy older adults, 20 with mild cognitive impairment (a condition that often precedes Alzheimer’s), and 20 with mild dementia. All individuals will have their driving data continuously collected for eight weeks using the driving monitoring system. Additionally, individuals will complete clinical and cognitive screening tests at the start of the study and provide feedback about their experience at the end of the study using three standardized surveys.

Dr. Rapoport will use high-level machine learning to analyze the driving data and identify the most relevant and informative features associated with cognitive impairment. They  will also look for associations between cognitive impairment level and survey results to understand the system’s usability and acceptability.

Impact

This work could identify driving habit details that may be relevant in Alzheimer’s. The findings could lay a foundation for additional studies designed to understand the impact of cognitive decline on driving habits, and how close monitoring of these habits might support identification of the earliest stages of mild cognitive impairment or Alzheimer’s.

The ARCOM Grant Program was developed jointly with Leveraging an Interdisciplinary Consortium to Improve Care and Outcomes for Persons Living With Alzheimer’s and Dementia (LINC-AD). The funding partners for this initiative are the Brain Canada Foundation through the Canada Brain Research Fund, an innovative partnership between the government of Canada (through Health Canada) and Brain Canada and the Alzheimer’s Association.

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