JMIR Publications

ABSTRACT

Background:

Exercise is a main recommended treatment for knee osteoarthritis (KOA), and personalized exercise programs have been shown to have promising results in maintaining physical fitness and athleticism. Digital health applications have multiple functions and have great potential for supervising and facilitating personalized exercise rehabilitation for KOA patients.

Objective:

To assess the impact of using a computer vision-based (CV) graded exercise intervention app (after 6 weeks) on clinical outcomes in patients with KOA compared to conventional exercise rehabilitation education.

Methods:

This is a randomized controlled trial of 60 participants (aged above 60) who were recruited through community administrators from July 2023 to September 2023. The participants were randomly allocated to a graded exercise application group (n=32) and exercise education brochure group (n=28). The main outcomes were short-term effects of pain, physical function and stiffness by The Western Ontario and McMaster Universities Arthritis Index (WOMAC). Secondary outcomes were the effects of participants' affective state, self-efficacy, quality of life, and user experience.

Results:

A total of 60 older adults in the age range of 60-80 years were recruited as study participants in the previous period, containing 26 males and 34 females. A statistically significant distinction in the physical function (p=0.016) and self-efficacy (p=0.037) of the two groups after the intervention. In additional, Participants indicated a positive experience with the application.

Conclusions:

The study found that the application could improve participants' physical function and self-efficacy compared to common interventions. Future applications are expected to be replicated for KOA patients in community. Clinical Trial: ClinicalTrials.gov NCT06220565; https://clinicaltrials.gov/ct2/show/NCT06220565