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2015 Grants - Seelye
Routine Everyday Activities of Life (REAL) Cognitive Assessment
Adriana Seelye, Ph.D.
Oregon Health & Science University
2015 New Investigator Research Grant
Can a technique for monitoring everyday activities be used to detect early declines in brain function among older people at risk for Alzheimer’s disease?
Alzheimer’s disease is a progressive disorder that begins decades before clinical symptoms appear. As such, researchers are looking for ways to identify the earliest changes in cognition (or brain function) that may indicate increased risk for developing Alzheimer’s. As older people begin to develop mild cognitive impairment (MCI), a condition that often precedes Alzheimer’s, their ability to carry out daily tasks declines in subtle ways. By detecting and monitoring these subtle functional changes, clinicians might identify which individuals are at greatest risk for developing Alzheimer’s disease. Because they are administered too infrequently and do not assess people’s activities within their home environment, the available standard cognitive tests do not currently provide this type of assessment.
For their current grant, Adriana Seelye, Ph.D., and colleagues will begin to develop a home-based assessment tool for monitoring changes in everyday task performance — changes that can reveal early forms of cognitive decline. They will remotely monitor two routine activities; home computer use and telephone use in two groups, older healthy adults or those with MCI. They will then use this information to develop “objective activity measures,” or measurements of task performance, that can discriminate between healthy participants and participants with MCI. The researchers will also determine whether the objective activity measures can be used to track changes in cognitive function over time that may predict the onset of MCI or Alzheimer’s disease.
If successful, the results of this study could lead to the development of a home-based tool for assessing early changes in cognitive function. Such a tool would provide a cost-effective, non-invasive method for identifying older adults at greatest risk for Alzheimer’s disease — and at a stage of cognitive decline when Alzheimer’s prevention strategies could be most effective.