Abstract TP329: ADL Speed Can Be Used As a Marker of Stroke Recovery and Health Status

Introduction: More than 50% of stroke patients experience limitations in activities of daily living (ADLs). Poor performance in ADLs has been associated with increased risk of rehospitalization after stroke and worsened quality of life. Monitoring and measuring ADLs after stroke can provide valuable insight into patients’ recovery and help identify targeted therapies to improve overall functioning. The objective of this study was to determine the feasibility of using contactless room-based sensors to capture physiological parameters and movement in patients following a stroke and whether these data can identify differences in function compared to individuals with varying ages and health status. Methods: Individuals age 18 and older were recruited to come to a study one-bedroom apartment outfitted with 16 ultrawideband contactless sensors collecting physiological data and movement following a scripted activities of daily living (ADL/IADL) protocol. A study-developed app guided patients through scripted ADLs while measuring the time to completion of each activity. Activities were grouped into simple (brush teeth, wash face, e.g.) and complex activities (food preparation, manage laundry, e.g.). Mean time to completion of all activities and activity groups were compared across 5 participant groups: students, non-student adults, healthy older adults, acute stroke survivors, and chronic stroke survivors. Results: A total of 50 participants completed at least one study visit with an average completion time of 2034 seconds (s). There were significant differences between the time to completion of the visit, ranging from 1772s to 2516s (p<0.05). Stroke survivors required the greatest amount of time (2516s), and the acute stroke survivor took the shortest amount of time to complete the tasks (1771s) followed by the students (1809s). While there was no significant difference between participant groups regarding mean total time to complete simple tasks, there was a significant difference (p<.05) in mean total time to complete complex tasks with chronic stroke survivor taking the longest (242s). Conclusions: These data demonstrate the benefits of monitoring stroke recovery and the potential challenges that long-term stroke survivors have in completing ADLs/IADL. Long term, these data show the feasibility of evaluating differences between ADL/IADL performance and the potential to utilize such data to monitor changes in health status as patients recover from stroke.