Automated IADL Sensing to Refine Measurement of Older Adult Daily Activity

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.

Study Overview

• Status: Not yet recruiting
• Conditions: Cognitive Ability General; Functional Abilities

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.

• Study Type: Observational
• Enrollment (Estimated): 20

Contacts and Locations

• Study Contact: Name: Steven M. Albert, PhD; Phone Number: 412-383-8693; Email: smalbert@pitt.edu
• Study Contact Backup: Name: Andrea L Rosso, PhD; Phone Number: 412-624-3060; Email: ALR143@pitt.edu

Study Locations

• United States
  • Pennsylvania
    • Pittsburgh, Pennsylvania, United States, 15261
      • University of Pittsburgh
      • Contact: Steven M Albert, PhD; Phone Number: 4123838693; Email: smalbert@pitt.edu
      • Contact: Email: smalbert@pitt.edu
      • Principal Investigator: Steven M. Albert, PhD
      • Principal Investigator: Andrea L Rosso, PhD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Eligible participants from the Community Research Connection registry of the University of Pittsburgh Claude D. Pepper Older Americans Independence Center.

Description

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.

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Older adults with normal cognition; Memory Impairment Screen >= 5 and MOCA >= 26
Older adults with mild cognitive impairment; Memory Impairment Screen >= 5 and MOCA < 26

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Efficiency of IADL Performance	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.	15-minute telephone screening, 90-minute in-person assessment

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Concordance with Occupational Therapist Rating	Agreement between machine-learning sensor categorization and occupational therapist assessment of standardized kitchen tasks.	One 90-min in-person assessment

Collaborators and Investigators

• Sponsor: University of Pittsburgh
• Collaborators: National Institute on Aging (NIA)
• Investigators: Principal Investigator: Steven M. Albert, PhD, University of Pittsburgh

Study record dates

Study Major Dates

• Study Start (Estimated): June 1, 2026
• Primary Completion (Estimated): December 1, 2026
• Study Completion (Estimated): June 1, 2027

Study Registration Dates

• First Submitted: May 6, 2026
• First Submitted That Met QC Criteria: May 6, 2026
• First Posted (Actual): May 14, 2026

Study Record Updates

• Last Update Posted (Actual): May 15, 2026
• Last Update Submitted That Met QC Criteria: May 13, 2026
• Last Verified: May 1, 2026

More Information

Terms related to this study

• Keywords: machine learning; Occupational therapy; computer vision; accelerometry
• Other Study ID Numbers: STUDY25120169; P30AG024827 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: De-identified data may be shared for future research with the appropriate sharing agreements in place. IPD includes demograhy, cognitive, sensor measures, and occupational therapist ratings.
• IPD Sharing Time Frame: June 1, 2027-May 31, 2028
• IPD Sharing Access Criteria: Qualified investigators can contact the PIs to request data. Deidentified data will be provided via password protected data exchange.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; ICF; ANALYTIC_CODE

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No