Community Mobility as a Predictor of Cognitive Performance in Stroke Recovery
Session Number
Project ID: MEDH 01
Advisor(s)
Dr. Shira Cohen-Zimerman; Cognitive Neuroscience Laboratory, Shirley Ryan Ability Lab
Dr. Jordan Grafman; Cognitive Neuroscience Laboratory, Shirley Ryan Ability Lab
Discipline
Medical and Health Sciences
Start Date
22-4-2020 10:05 AM
End Date
22-4-2020 10:20 AM
Abstract
Community mobility is an instrumental activity of daily living that measures the ability of an individual to independently travel and navigate his or her neighborhood and community. This study investigated community mobility, specifically in the differences in the types of locations an individual travels to, as a predictor of cognitive performance using GPS after stroke. Using the Configurable Integrated Monitoring Service (CIMON) smartphone application, the mobility of 20 participants were tracked for 90 days, followed by an intensive battery of standardized cognitive testing. We identified coordinate clusters using Google Maps and developed a location categorization model based on the North American Industry Classification System (NAICS) that can be used in future studies. Our results yielded a few significant correlations between location and cognitive variables; however, more testing is needed before any definitive conclusions can be affirmed
Community Mobility as a Predictor of Cognitive Performance in Stroke Recovery
Community mobility is an instrumental activity of daily living that measures the ability of an individual to independently travel and navigate his or her neighborhood and community. This study investigated community mobility, specifically in the differences in the types of locations an individual travels to, as a predictor of cognitive performance using GPS after stroke. Using the Configurable Integrated Monitoring Service (CIMON) smartphone application, the mobility of 20 participants were tracked for 90 days, followed by an intensive battery of standardized cognitive testing. We identified coordinate clusters using Google Maps and developed a location categorization model based on the North American Industry Classification System (NAICS) that can be used in future studies. Our results yielded a few significant correlations between location and cognitive variables; however, more testing is needed before any definitive conclusions can be affirmed