ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2025
A Preliminary Usability Evaluation of an Artificial Intelligence-Based, Motion-Detecting Wearable Device: The Geriatric Functional Assessment System.
John A Batsis, Rishank Singh, Jennifer Poole, Paige Bramblett, Danae Gross, Meredith Gilliam, Chaterlee Pamintuan, Beckham Nora, David H Lynch, Xiaohui Liang
Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
10 authors.
John A BatsisDivision of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.ORCID 0000-0002-0845-4416
Rishank SinghDepartment of Computer Science, University of Massachusetts Boston, Boston, Massachusetts, USA.
Jennifer PooleDivision of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
Paige BramblettDivision of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
Danae GrossDepartment of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Meredith GilliamDivision of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
Chaterlee PamintuanDivision of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
Beckham NoraDivision of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
David H LynchDivision of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.ORCID 0000-0002-2512-9367
Xiaohui LiangDepartment of Computer Science, University of Massachusetts Boston, Boston, Massachusetts, USA.
Funding
Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
North Carolina Translational and Clinical Sciences Institute (NC TraCS)UM1TR004406 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI NICHOLAS J SHAHEEN · 2023 to 2026
$37.5M
Validating novel sleep sensors and devices in older adults with Alzheimer's diseaseP30AG073107 · NIA · UNIVERSITY OF MASSACHUSETTS AMHERST · PI Sudeshna Das · 2021 to 2026
$32.0M
UNIV OF NORTH CAROLINA CLINICAL NUTRITION RESEARCH UNITP30DK056350 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Ian Michael Carroll · 1999 to 2026
$31.6M
Utilizing Technology and AI Approaches to Facilitate Independence andResilience in Older AdultsP30AG073104 · NIA · JOHNS HOPKINS UNIVERSITY · PI Peter M. Abadir, Alexis Battle · 2021 to 2026
$31.2M
Technology Identification and Training CoreP30AG073105 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DEMIRIS, GEORGE, KARLAWISH, JASON H · 2021 to 2025
$21.2M
Johns Hopkins University P30AG073107NCATS NIH HHS UL1 TR002489NCATS NIH HHS UM1 TR004406NIA NIH HHS P30 AG073104NIA NIH HHS P30 AG073105NIA NIH HHS P30 AG073107NIDDK NIH HHS P30 DK056350NIH HHSNIH HHS P30AG073104North CarolinaTranslational and Clinical Sciences UM1TR004406University of Massachusetts Amherst P30AG073105University of North Carolina Nutrition Obesity Research Center P30DK056350-23University of Pennsylvania
6 · The paper itself
Abstract
backgroundPhysical function is a key determinant of independence among older adults. Yet, there are barriers to assessing physical function in clinic. We developed a wearable geriatric functional assessment system (GFAS) that quickly and effortlessly evaluates physical function.
methodsA single-arm, nonrandomized, mixed-methods, usability study evaluated the design, ergonomics, and usability of the GFAS. Participants aged >65 years with multiple chronic conditions were recruited and wore the GFAS about the clinic for 15 min. We assessed walking speed, 30-s sit-to-stand, and evaluated postural balance using a Footscan pressure plate system. In addition to transcribed exit-interviews and a Willingness to Pay questionnaire, the USE, Technology Acceptance, and System Usability Scales were evaluated.
resultsOf the 37 participants screened, 21 were recruited, enrolled, and consented, whose mean age was 76.6 ± 5.45 years (52.4% female), with 28.6% non-White, 19% were on Medicaid, and 52.4% were classified as having a robust Fried frailty status. Participants favored the prototype and its existing functionality (7.14 ± 2.35) and would wear it if recommended by their clinician (7.62 ± 2.50, median 8.0). All felt it was easy to use, 74% of comments outlined they would use it again, and 81% noted it was comfortable. System Usability score was 78.2 ± 14.5, USE was 5.83 ± 3.59, and Technology Acceptance demonstrated satisfaction of 7.05 ± 2.18 in using the device.
conclusionsThe GFAS prototype shows considerable promise in evaluating physical function in older adults and that additional steps are needed to maximize usability.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
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