As drivers steering our way through each day, we make hundreds of tiny navigational decisions. When do we turn and in which direction? What are the best roads to take to get to where we're going most directly and effectively?
For most of us, these decisions are made subconsciously.
But research shows that, in the very earliest stages of Alzheimer's disease, years before symptoms such as decline in memory surface, people may start navigating differently on the roads without realizing it.
Building on this knowledge, the University of Calgary's Healthy City Lab in the Schulich School of Engineering has developed a "route complexity metric" to measure these subtle navigational changes. This new metric is derived through real-world sensor data collected from older adults as they go about their daily driving routines. Using this data, the research team can create a "digital fingerprint" of an individual's navigational style as they drive through their daily environment.
The route-complexity metric was introduced in a recently published study in the IEEE Journal of Translational Engineering in Health and Medicine.
"Driving is interesting because, even though we rarely think about it this way, it's actually a very complex activity," says Dr. Sayeh Bayat, PhD, assistant professor of biomedical and geomatics engineering, director of the Healthy City Lab, and a Schulich Research Chair. "When you're driving, you're constantly making decisions. Where to turn, how to respond to traffic, how to get where you're going. All that draws on different parts of the brain and some routes are more demanding than others. If there are lots of turns, or if you're taking a route that's different from what you're used to, it requires more planning, attention, and spatial awareness.
"Analyzing these patterns can tell us a lot. Changes in how someone navigates can give us early insight into cognitive health, long before more obvious symptoms appear."
The research was led by Kelly Long, a UCalgary graduate student in biomedical engineering, and co-authored with Bayat and Dr. Ganesh Babulal, OTD, PhD, an associate professor of neurology at the Washington University School of Medicine.
The study used passive sensor monitoring technology installed in cars to collect driving data from 111 adults between the ages of 65-85, some of whom had biomarker-confirmed preclinical Alzheimer's disease, in which changes in the brain are present, even though symptoms have yet to arise. Their driving patterns were compared with participants without preclinical Alzheimer's.
"We discovered that people with preclinical Alzheimer's shifted towards simpler, more direct routes as they got older, whereas cognitively healthy adults did not make this shift," says Long, BSc (Eng)'21, MSc'25. "This change is important because it suggests that even before memory decline sets in, early Alzheimer's may influence how people plan or execute everyday navigation."
Subtle driving changes that often go unnoticed by families reveal themselves in the continuous real-world data collected by the sensors.
"Alzheimer's disease is difficult to detect early, and current diagnostic tools rely heavily on imaging tests like PET scans and invasive procedures such as spinal taps," says Bayat. "What we're looking at instead is everyday behaviour. Something as familiar as how a person drives or the routes they choose can reflect changes in cognitive function. Our route-complexity metric lets us measure those changes without asking people to do anything extra."
From a cognitive health standpoint, the potential of the driving metric and the digital fingerprint it provides could make a huge impact. "This type of digital biomarker could one day complement traditional clinical tests to help flag cognitive changes before the symptoms of Alzheimer's arise," says Bayat. "It can support more informed clinical decisions, enable earlier and more personalized interventions, and track changes over time."
The research also has important implications for mobility and independence because it provides a clearer insight into the changing driving capabilities of those facing deteriorating cognitive health. Bayat notes that dementia is a progressive process, and that many people in its early stages are able to continue driving safely. When driving is limited too early, the resulting loss of independence and social connection can negatively impact quality of life.
In partnership with researchers across Canada and Australia, the Healthy City Lab was recently rewarded a $1 million CCNA Phase III Team Grant from the Canadian Institutes of Health Research to advance its work on driving and dementia. The project is jointly led by Bayat, along with Toronto researchers Dr. Gary Naglie, MD, of Baycrest Health Sciences, and Dr. Mark Rapoport, MD, of Sunnybrook Health Sciences Centre.
"This national, multi-site project will build on our earlier research using in-vehicle technologies to assess driving behaviours in people with cognitive impairment," says Bayat. "Ultimately, we're working toward a fair, accessible, and data-driven framework for driving assessment which supports individuals, families, and clinicians in making confident, informed decisions."
January is Alzheimer's Awareness Month. In light of this, on Saturday, Jan. 31, the Healthy City Lab team will be at the Alzheimer's Calgary Talking About Dementia education sessions sharing their ongoing efforts in dementia research. The sessions will be held from 10 a.m. to 12 p.m. at the DoubleTree by Hilton Calgary. Register at alzheimercalgary.ca
Sayeh Bayat is an assistant professor in the departments of Biomedical Engineering and Geomatics Engineering at the Schulich School of Engineering. She is also a member of the Hotchkiss Brain Institute and the O'Brien Institute for Public Health at the Cumming School of Medicine.
