In Journal of medical Internet research ; h5-index 88.0
BACKGROUND : The use of digital therapeutic solutions for rehabilitation of conditions such as osteoarthritis provides scalable access to rehabilitation. Few validated technological solutions exist to ensure supervision of users while they exercise at home. Motion Coach (Kaia Health GmbH) provides audiovisual feedback on exercise execution in real time on conventional smartphones.
OBJECTIVE : We hypothesized that the interrater agreement between physiotherapists and Motion Coach would be noninferior to physiotherapists' interrater agreement for exercise evaluations in a cohort with osteoarthritis.
METHODS : Patients diagnosed with osteoarthritis of the knee or hip were recruited at a university hospital to perform a set of 6 exercises. Agreement between Motion Coach and 2 physiotherapists' corrections for segments of the exercises were compared using Cohen κ and percent agreement.
RESULTS : Participants (n=24) were enrolled and evaluated. There were no significant differences between interrater agreements (Motion Coach app vs physiotherapists: percent agreement 0.828; physiotherapist 1 vs physiotherapist 2: percent agreement 0.833; P<.001). Age (70 years or under, older than 70 years), gender (male, female), or BMI (30 kg/m2 or under, greater than 30 kg/m2) subgroup analysis revealed no detectable difference in interrater agreement. There was no detectable difference in levels of interrater agreement between Motion Coach vs physiotherapists and between physiotherapists in any of the 6 exercises.
CONCLUSIONS : The results demonstrated that Motion Coach is noninferior to physiotherapist evaluations. Interrater agreement did not differ between 2 physiotherapists or between physiotherapists and the Motion Coach app. This finding was valid for all investigated exercises and subgroups. These results confirm the ability of Motion Coach to detect user form during exercise and provide valid feedback to users with musculoskeletal disorders.
Biebl Johanna Theresia, Rykala Marzena, Strobel Maximilian, Kaur Bollinger Pawandeep, Ulm Bernhard, Kraft Eduard, Huber Stephan, Lorenz Andreas
digital health, digital rehabilitation, exercise therapy, mHealth, machine learning, osteoarthritis, smartphone