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A Preliminary Usability Evaluation of an Artificial Intelligence-Based, Motion-Detecting Wearable Device: The
John A Batsis1,2, Rishank Singh3, Jennifer Poole1
1Division of Geriatric Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
Background:
Physical 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.
Methods:
A 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.
Results:
Of 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.
Conclusions:
The GFAS prototype shows considerable promise in evaluating physical function in older adults and that additional steps are needed to maximize usability.
