Cognitive Ability General, Functional Abilities
Conditions
Keywords
Occupational therapy, machine learning, accelerometry, computer vision
Brief summary
The instrumental activities of daily living (IADL) refer to complex daily activities required for adult independence, such as preparing a meal or taking medications. This study will assess the efficacy of sensing technologies (smartwatch, computer vision, eye tracking) for recognizing IADL activities in naturalistic settings and score performance relative to ratings from occupational therapists. If successful in assessing the efficiency of IADL, the sensing technologies will be a valuable addition to geriatric assessment.
Detailed description
With declines in motor and cognitive function, even older adults living independently may be less efficient in performing daily activities, such as cooking and light housekeeping, which may signal an impending need for caregiver support and healthcare services. Clinicians currently lack automated tools for detecting early declines in daily activity. This research will assess the utility of motion sensors and computer vision assessment in detecting early deficits in the instrumental activities of daily living (IADL), in this case structured cooking and cleaning tasks performed in a standardized kitchen. Older adults with normal cognitive status and those with mild cognitive impairment will be recruited from a research registry to assess differences in performance.
Interventions
None listed
Sponsors
University of Pittsburgh
National Institute on Aging (NIA)
Study design
Observational model
CASE_CONTROL
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
FEMALE
Age
75 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
1. Participant in University of Pittsburgh Pepper Center research registry 2. Age 75+ 3. Female 4. Residing in community 5. Meets criteria for normal cognition or mild cognitive impairment on telephone screening (Memory Impairment Screen \>= 5) 6. Daily, independent performance of cooking and light cleaning tasks
Exclusion criteria
1. Inability to provide informed consent 2. Meets criteria for possible dementia (Memory Impairment Screen \<= 4) 3. Reports difficulty with activities of daily living (dressing, feeding oneself, using toilet, bathing) 4. Uses mobility assistance device for indoor ambulation 5. Medical conditions that may interfere with participation (e.g., severe untreated psychiatric disorders, unstable cardiovascular conditions, Parkinson's disease) 6. Current participation in other interventional studies or clinical trials.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Efficiency of IADL Performance | 15-minute telephone screening, 90-minute in-person assessment | Machine learning composite based on candidate sensing metrics, such as time to complete each element of kitchen task, pacing of activity, corrections, repetition of movement, adjustments of posture, and need to review directions. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Concordance with Occupational Therapist Rating | One 90-min in-person assessment | Agreement between machine-learning sensor categorization and occupational therapist assessment of standardized kitchen tasks. |
Countries
United States
Contacts
CONTACTAndrea L Rosso, PhD
PRINCIPAL_INVESTIGATORAndrea L Rosso, PhD
University of Pittsburgh
Outcome results
None listed