Title: Wearable Sensor and AI to Recognize and Evaluate IADLs
Funded by the National Institute on Aging (R21AG077404) PI: Cole
Mild cognitive impairment (MCI) reportedly affects up to 24% of older adults and involves an associated decline in functional mobility. Individuals with MCI experience decreased balance, decreased gait speed, altered gait parameters, and even a greater risk of falling. Currently, clinical measures of balance and mobility only moderately predict dysfunction associated with MCI. The objective of this project is to combine the expertise of physical and occupational therapy and engineering to use advancing wearable technology and advanced deep learning algorithms to develop a framework for recognizing and determining the ability to perform naturalistic movements in a structured grocery shopping task. Our long-term goal is to develop a naturalistic and highly reliable method that may provide early identification of cognitive and movement dysfunction so as to initiate treatment before the onset of dementia, as well as to provide a functional test to measure potential longitudinal functional changes.
