2024 Alzheimer's Association Research Grant to Promote Diversity (AARG-D)
Remote Sensing for ADRD-Specific Activities Identification in Older Adults
Can in-home sensors be used to monitor behavioral changes associated with early Alzheimer’s?
Knoo Lee, Ph.D.
The Curators of the University of Missouri
Columbia, MO - United States
Background
Individuals with Alzheimer's and other dementias often need the services of hospitals and other long-term care facilities, especially as the disease progresses. Studies have found that many older adults and individuals living with Alzheimer’s often prefer to “age in place” or live independently in one’s own home and community. This can foster a sense of belonging and improve overall quality of life. However, there is a need to develop new approaches that can monitor disease progression while preserving independence in older adults who are at risk of developing Alzheimer’s.
Behavioral changes in routine tasks such as household chores, personal care, and eating habits can often be early signs of Alzheimer’s. Dr. Knoo Lee and colleagues propose a study that would test whether an advanced computer science technique called machine learning could be used to detect the behavioral changes associated with early Alzheimer’s in older adults aging in place.
Research Plan
For their project, Dr. Lee and the team will use remote motion sensor systems that can monitor daily activities and movement. They will recruit 16 individuals to participate in their study, including both cognitively unimpaired older adults and individuals living with early Alzheimer’s, as well as their caregivers. Sensors will be installed in the homes of these participants and movement data will be collected over four weeks. The researchers will then analyze their findings and test whether machine learning can identify the behavioral changes associated with early Alzheimer’s.
Impact
The findings from this study may improve our understanding of the behavioral changes associated with early Alzheimer’s. The results may also lead to the development of cost-effective, noninvasive methods to help older at-risk adults age in place.