PhD Candidate, University of Toronto
Engineer | Researcher | Educator
I’m a PhD candidate in Biomedical Engineering at the University of Toronto in the Intelligent Assistive Technology and Systems Lab, advised by Dr. Alex Mihailidis. I am also working with the Roe Lab in the Knight Alzheimer’s Disease Research Center, Department of Neurology, at Washington University School of Medicine.
My research interests involve using wearable technologies to monitor health in the context of everyday environments. I believe how people interact with their environment reveals significant information about their health and well-being. Through my work, I aim to examine these interactions by using methods from spatial analysis, data mining and artificial intelligence.
In my PhD thesis, I am investigating whether GPS mobility can be used to explain, influence, and/or predict dementia. The two primary projects that I am working on are:
(1) Analyzing mobility patterns of people with dementia using multi-sensor datasets including GPS and accelerometry
(2) Investigating in-road driving performance of people with preclinical Alzheimer's disease using GPS driving data
Before my PhD, I graduated with a bachelor's degree in Engineering Science (Aerospace Major) at the University of Toronto in 2016.
Our paper "GPS Driving: A Digital Biomarker for Preclinical Alzheimer Disease" has been accepted for publication in Alzheimer's Research & Therapy. For more information, check here.
Our abstract "Evaluating predictability in outdoor mobility: A potential pathway to personalized assistance for people with dementia" has been accepted for presentation at the AAIC, happening on July 26 - 30th.
GPS Driving: A Digital Biomarker for Preclinical Alzheimer Disease
Sayeh Bayat, Ganesh M. Babulal, Suzanne E. Schindler, Anne M. Fagan, John C. Morris, Alex Mihailidis, Catherine M. Roe
Alzheimer's Research & Therapy 2021 - In Press
We applied machine learning methods to a large dataset of GPS driving trajectories from a cohort of cognitively intact older drivers with and without preclinical AD. Our findings suggest that driving may serve as an effective and accurate digital biomarker for identifying preclinical AD among older adults.
Paper (to be posted)
Outdoor Life in Dementia: How predictable are people with dementia in their mobility?
Sayeh Bayat and Alex Mihailidis.
Alzheimer's & Dementia: DADM 2021
Aiming to better capture the essence of mobility of people with dementia, we analyze the randomness and predictability manifested in their GPS trajectories. We find that relying on both spatial and temporal patterns, a 4-week record of mobility patterns of people with dementia displays 95% potential predictability.
A GPS-based Framework for Understanding Outdoor Mobility Patterns of Older Adults with Dementia: An Exploratory Study
Sayeh Bayat, Gary Naglie, Mark Rapoport, Elaine Stasiulis, Michael J Widener and Alex Mihailidis.
We develop a comprehensive framework for comparing outdoor mobility patterns of cognitively intact older adults and older adults with dementia using passively collected GPS data.
Bringing the ‘Place’ to Life Space in Gerontology Research
Sayeh Bayat, Michael J Widener and Alex Mihailidis.
We discuss new directions for extending the life-space framework in environmental gerontology by drawing on the advancements in the activity space framework in travel behaviour and health geography literature.
Inferring Destinations and Activity Types of Older Adults From GPS Data: Algorithm Development and Validation
Sayeh Bayat, Gary Naglie, Mark Rapoport, Elaine Stasiulis, Belkacem Chikhaoui and Alex Mihailidis.
JMIR AGING 2020
We develop and validate a framework that relies solely on GPS data to capture older adults’ travel destinations (ie, stop points) and activity types. We show that GPS technology can be used to extend the traditional life-space assessments by accurately determining semantic dimensions of outdoor mobility.
A High-Performance Millirobot for Swarm-Behaviour Studies: Swarm-Topology Estimation
Justin Y Kim, Zendai Kashino, Laura Marcela Pineros, Sayeh Bayat, Tyler Colaco, Goldie Nejat, Beno Benhabib
We present a novel high-performance millirobot ( milli- robot- Toronto), designed to allow for the testing of complex swarm-behaviours, including human–swarm interaction. As complementary software to this hardware development, we also present a new global swarm-topology estimation algorithm.
MIE1624: Introduction to Data Science and Analytics
Tutorial Teaching Assistant, Mechanical & Industrial Engineering Department, graduate course, (~100 students)
MIE1622: Computational Finance & Risk Management
Tutorial Teaching Assistant, Mechanical & Industrial Engineering Department, graduate course, (~70 students)
MAT188: Linear Algebra & MATLAB
Head Teaching Assistant, Core Course, First-year Engineering, (~800 students)
APS106: Foundations of Computer Programming (Python)
Computer Lab Teaching Assistant, Core Course, First-year Engineering, (~800 students)
CSC108: Introduction to Computer Programming (Python)
Office Hour & Marking Teaching Assistant, Computer Science Department, (~1000 students)
Organizer, 4th Workshop AI for Aging, Rehabilitation and Intelligent Assisted Living (ARIAL), Date: August 21-26, 2021
TRI - KITE Research Institute
550 University Ave, Toronto, ON M5G 2A2
Tel: 416-597-3422 x 7345