Publications
Healthy City Lab / Publications
Healthy City Lab / Publications
Cognitive and brain reserve predict decline in adverse driving behaviors among cognitively normal older adults
Samantha A Murphy, Ling Chen, Jason M Doherty, Prerana Acharyya, Noah Riley, Ann M Johnson, Alexis Walker, Hailee Domash, Maren Jorgensen, Sayeh Bayat, David B Carr, Beau M Ances, Ganesh M Babulal
Frontiers in Psychology 2022
Daily driving is a multi-faceted, real-world, behavioural measure of cognitive functioning requiring multiple cognitive domains working synergistically to complete this instrumental activity of daily living. This study examined whether cognitive reserve and brain reserve predicted changes in adverse driving behaviours in cognitively normal older adults.
Driving assessment in preclinical Alzheimer’s disease: progress to date and the path forward
Sayeh Bayat, Catherine M Roe
Alzheimer's Research & Therapy 2022
Changes in driving behaviour may start at the preclinical stage of Alzheimer’s disease (AD), where the underlying AD biological process has begun in the presence of cognitive normality. Here, we summarize the emerging evidence suggesting that preclinical AD may impact everyday driving behaviour.
Adverse driving behaviors increase over time as a function of preclinical Alzheimer's disease biomarkers
Jason M Doherty, Samantha A Murphy, Sayeh Bayat, Julie K Wisch, Ann M Johnson, Alexis Walker, Suzanne E Schindler, Beau M Ances, John C Morris, Ganesh M Babulal
Alzheimer's & Dementia 2022
We investigated the relationship between preclinical Alzheimer's disease (AD) biomarkers and adverse driving behaviours in a longitudinal analysis of naturalistic driving data and showed that abnormal amyloid beta (Aβ42/Aβ40) ratio was associated with an increase in adverse driving behaviours over time compared to ratios in the normal/lower range.
Neuropsychological correlates of changes in driving behavior among clinically healthy older adults
Andrew J Aschenbrenner, Samantha A Murphy, Jason M Doherty, Ann M Johnson, Sayeh Bayat, Alexis Walker, Yasmin Peña, Jason Hassenstab, John C Morris, Ganesh M Babulal
The Journals of Gerontology: Series B 2022
In this work, we study the extent to which the cognitive domain scores moderate change in driving behaviour in cognitively healthy older adults using naturalistic (Global Positioning System-based) driving outcomes and compare them against self-reported outcomes using an established driving questionnaire.
An event-based model and a map visualization approach for spatiotemporal association relations discovery of diseases diffusion
Roya Habibi, Ali Asghar Alesheikh, Sayeh Bayat
Sustainable Cities and Society 2022
Here, we propose a novel, event-based spatiotemporal model, to mine associated areas in space and time simultaneously. This model was applied to a dataset of COVID-19 in New York City. The method simplified the spatiotemporal complexities of infectious disease diffusion, and the map visualization method reveals the spatiotemporal structure of the outbreak.
Driving, Social Distancing, Protective, and Coping Behaviors of Older Adults Before and During COVID-19
Catherine M. Roe, Sayeh Bayat, Jamie Hicks, Ann M Johnson, Samantha Murphy, Jason M. Doherty, Ganesh M. Babulal
Journal of Applied Gerontology 2022
Here, we explore the impact of the COVID-19 pandemic on driving, social distancing, protective, and coping behaviours of older adults by reporting data on participants above 65 whose driving behaviours are being monitored using GPS devices.
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
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.
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.
Gerontology 2021
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.
Gerontology 2021
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.