Automated Sensing for Daily Activity in Older Adults
This study is looking at how well sensing technologies, like smartwatches, computer vision, and eye tracking, can recognize and score daily activities (Instrumental Activities of Daily Living or IADLs) in older women. IADLs are complex tasks like cooking or cleaning that are important for living independently. Researchers want to see if these technologies can accurately measure how efficiently you perform these tasks, compared to ratings from occupational therapists. This could help doctors detect early changes in daily activity that might signal a need for more support. The study is recruiting 20 women, aged 75 and older, who live in the community and can perform cooking and light cleaning tasks independently. You would also need to be part of the University of Pittsburgh Pepper Center research registry and have normal cognition or mild cognitive impairment.
- Study design
- This is an observational study with 20 participants. It is not specified if it is randomized or blinded.
- What's involved
- You would have a 15-minute telephone screening and a 90-minute in-person assessment. During the in-person assessment, you would perform structured cooking and cleaning tasks in a standardized kitchen while being monitored by sensing technologies.
- Compensation
- Not stated in the trial record.
- Follow-up
- Your efficiency of IADL performance will be measured at the 15-minute telephone screening and the 90-minute in-person assessment.
AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.
Automated IADL Sensing to Refine Measurement of Older Adult Daily Activity
At a glance
Conditions
NCT07585864
Where you'd take part
This study runs at 1 site. They're the same protocol — you choose where, and that choice sets who your contact draft is addressed to.
University of Pittsburgh
Pittsburgh, Pennsylvaniastudy coordinator listed
Recruiting
Sites open and close at different times, so the status above is per site — it can differ from the study's overall status.
Study leadership
- Andrea L Rosso, PhD · PRINCIPAL_INVESTIGATOR · University of Pittsburgh
Who to contact
Opens a ready-to-send draft in your own email app — review before sending.
What this trial measures
- Efficiency of IADL Performance15-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.