Automated System for Detecting and Reporting Lapses in Performance of Activities of Daily Living for Independent and Cohabitating Persons with Alzheimer's Disease and Related Dementias

NIH RePORTER · NIH · R43 · $499,758 · view on reporter.nih.gov ↗

Abstract

Project Abstract In this SBIR Phase I project, ASTER Labs will significantly enhance an innovative system able to accurately detect Activities of Daily Living (ADL) performed by persons with Alzheimer’s disease and related dementias with new capabilities to determine specific compliance or non-compliance during their daily lives. This new solution addresses a current unmet need to significantly streamline ongoing evaluations of persons’ abilities to complete these important activities, and will equip care providers with reliable, automated, and on-demand information to assist with assessing patients’ functional independence and making informed decisions on interventions and level of care based on disease progression. In 2023, an estimated 6.7 million Americans live with Alzheimer’s dementia. Nearly a third live alone and are more likely to suffer poorer health outcomes than those cohabitating. Clinical research shows the importance of ongoing ADL assessment to establish diagnoses of dementia and its progression. Current and proposed ways to automate this assessment (e.g. cameras, beacon-based tracking systems) have been limited and criticized based on potential privacy concerns, reduced accuracy and coverage, and need for significant infrastructure additions. Ubiquitous commercial products primarily focus on fitness activities versus ADL, and further, inadequately address dementia patients’ unique sensitivity to non-discreet, unfamiliar wearable devices. ASTER Labs’ work on two related systems leveraging a discreet electronic shoe insole specifically designed for dementia patient care has identified a strong need to complement clinical interventions (e.g. compensatory memory techniques, memory notebooks) to help prevent or delay dementia onset and preserve functional independence. As those with cognitive impairment risk inaccurate recollection of ADL performed throughout the day, ASTER Labs’ system is able to automatically and accurately detect and identify ADL. However, an unmet need exists to enhance the ability of dementia care providers to receive verifiable notifications of ADL compliance, based on whether automatically-detected activities were performed as expected, and according to specific constraints on frequency of occurrence. Therefore ASTER Labs’ proposed ActivVerify system will leverage its technology using intelligent processing of WiFi, GPS, inertial, and audio sensor data from a small hardware suite concealed in a shoe insole and unnoticeable to the wearer, combined with new data analysis software capabilities that use constraint scheduling and matching to determine and verify ADL compliance. In Phase I, the prototype system will be assembled, with feasibility demonstrated by functional evaluation in a focus group study with caregivers, physicians, and cognitive rehabilitation therapists of patients with dementia. The system’s ADL compliance accuracy will be determined in timed experiments by ASTER Labs’ engineers wearing the prot...

Key facts

NIH application ID
10819978
Project number
1R43AG085709-01
Recipient
ASTER LABS, INC.
Principal Investigator
Suneel Ismail Sheikh
Activity code
R43
Funding institute
NIH
Fiscal year
2024
Award amount
$499,758
Award type
1
Project period
2024-09-25 → 2026-08-31