Persons living with dementia (PWD) often require assistance with routine activities and daily tasks. Workloads placed on caregivers often results in high levels of physical and emotional stress, and depression, and higher overall morbidity and mortality rates. Focus group of caregivers for individuals with mild to moderate dementia, identified dressing the PWD as the most pressing and stressful daily concern. We have developed a prototype computerized Dressing Assistant (DA), designed to reduce caregiver burden and independence. The system, employing advanced smart home technologies embedded within a set of dresser drawers, uniquely tailors assistance to the cognitive and affective states and abilities of PWD, using prompts and feedback. Our interdisciplinary team which combines human-computer interaction, gerontological nursing and dementia, will conduct translational research, bringing DA from laboratory to home settings.
AIM 1 : Optimize the Dressing Assistant installation procedures for PWD home settings. To understand how effectively the DA system can be installed in a home, we will consider: 1) the initial system installation, including length of installation visit, number of component adjustments, and caregiver and PWD training time required; and 2) opportunities for system optimization and durability through ongoing DA system monitoring, alert notices generated by the performance log, and caregiver feedback to the study team.
AIM 2 : Assess Dressing Assistant system reliability and accuracy in PWD home settings. We will use an adaptive support model, performance log, error rate, and caregiver feedback, to determine how accurately the DA system functions in a home setting. Data includes: 1) system switches and sensor logs (i.e. which drawers were opened, when, for how long, and in what sequence), and doorway motion sensor; 2) validated Pearlin?s Caregiver Mastery and Mahoney?s Caregiver Vigilance scales will determine trend effects; and 3) mobile device caregiver feedback.
AIM 3 : Maximize utility through identification of barriers and facilitators, usage, acceptability, effectiveness, and perceptions and refining system accordingly. We will identify barriers and facilitators that enable/impede frequent, long-term Dressing Assistant system use and compare performance log usage frequency data and accuracy measures (AIM 2) to consider how DA system accuracy affects usage. The DA system-generated data, and qualitative open-ended structured caregivers and PWD interviews will be used to determine acceptability. We will consider whether the PWD/caregiver dyad effectively uses the technology, frequency and duration of use based on the performance logs, and user interviews to identify reasons for using/not using the DA system. Interviews will identify barriers and facilitators influencing usage and obtain information about how positive and negative perceptions of the interaction experience affect use. Key Words: Alzheimer's, caregiver, dementia, smart home, assistive technology, Activities of Daily Living.

Public Health Relevance

Significance): The number of people living with Alzheimer's Disease (AD), the leading cause of dementia, is expected to triple in the next 35 years, with the potential to significantly increase the burden on caregivers. As a result, morbidity and mortality rates for caregivers stands to increase. Our translational research and comercialization efforts seeks to optimize the translation of a Dressing Assistant (DA), developed under a successful R21 award, from laboratory to home settings, to engage and empower the PWD and to decrease the burden on caregivers--having the potential to reduce caregiver morbidity and mortality and increase quality of life.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Small Business Technology Transfer (STTR) Grants - Phase I (R41)
Project #
3R41AG062082-02S1
Application #
9856368
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Atienza, Audie A
Project Start
2018-09-30
Project End
2020-05-31
Budget Start
2019-06-15
Budget End
2020-05-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Inventors' Workshops, Inc.
Department
Type
DUNS #
080263066
City
New York
State
NY
Country
United States
Zip Code
10010