Improved AD/ADRD Assessment Sensitivities Using a Novel In-Situ Sensor System

Project Summary/AbstractAccurate assessment of daily functions for individuals at risk for and with AD/ADRD, is fundamental to detection, diagnosis, and characterization of its progression and prescribed treatments. Current assessment techniques typically rely on non- continuous, discreet observations provided from a third party and covering single or limited performance domains. With significantly larger portions of American’s choosing to age in place, any assessment technology must be able to be in-situ (low-cost, ubiquitous) and operate without user interface (autonomous) to provide objective, cross-domain, and continuous daily function measurements and reporting.The primary objective of this fast track SBIR project is to demonstrate the feasibility and effectiveness of using the Birkeland Current Sovrin IoT system to continuously and accurately assess daily functions, ADLs, and IADLs, for persons experiencing cognitive decline in a home or assisted care settings. This includes direct comparison with an accepted assessment technique, ADCS-ADL/23. Machine learning and artificial intelligent techniques will be employed to identify novel subfactors for improved sensitivities from available sensor data combinations. Secondary objectives include establishing a significant data set of detailed daily actions (andlt;10 sec resolution) for 100+ individuals with AD/ADRD. Long-term goals support future intervention studies through improved assessment tools with enhanced sensitivity to early and mid-stage decline.The Birkeland Current Sovrin IoT system makes use of patented proximity-based energy monitoring and control sensors, data analytics and change detection algorithms to continuously monitor activities of individuals in a home or assisted care environment. Intelligent power-strips and battery-based sensors located throughout the home or facility, monitor real time absolute location of individuals, caregivers, and devices they interact with. Correlation of high-fidelity data allows accurate determination of activities, attribution to a specific individual, mobility measurement, and behavior assessment across traditional and novel ADL/IADL categories. Birkeland Current is teamed with Texas Aandamp;M Center for Population Health and Aging, Georgia, Tech Institute for People and Technology, Baylor Scott and White Division of Gerontology, and multiple home-care and assisted-care facilities, in the development of the study approach, implementation plan, analytics tools, and applications to aging populations and future intervention studies.Project NarrativeThe proposed research would utilize novel, ubiquitous Internet-of-Things sensors and automated analytics to demonstrate enhanced sensitivity and future utility of continuous in-situ IADL/ADL data for dementia research and its effectiveness in characterizing interventions for Alzheimer’s and related dementias of aging populations in support of NIA stated priorities.