Towards the Monitoring of Functional Status in a Free-Living Environment for People with Hip or Knee Osteoarthritis: Design and Evaluation of the JOLO Blended Care App

• Published in: Sensors (Basel, Switzerland) Vol. 20; no. 23; p. 6967
• Main Authors: Emmerzaal, Jill, De Brabandere, Arne, Vanrompay, Yves, Vranken, Julie, Storms, Valerie, De Baets, Liesbet, Corten, Kristoff, Davis, Jesse, Jonkers, Ilse, Vanwanseele, Benedicte, Timmermans, Annick
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 05-12-2020; MDPI
• Subjects: Accelerometers; Activity recognition; app development; Arthritis; Biomechanical engineering; Biomechanics; Biomedical materials; blended care; Datasets; Design analysis; Exercise; Feedback; Functional Status; Goal setting; Humans; interaction design; Joints (anatomy); Machine learning; Mobile Applications; Older people; Osteoarthritis; Osteoarthritis, Hip - diagnosis; Osteoarthritis, Knee - diagnosis; Patients; Personal information; Physical fitness; Portable computers; Rehabilitation; Sensors; Smartphones; Surveys and Questionnaires; Therapy; usability; app development; usability; interaction design; osteoarthritis; blended care
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s20236967

(1) Background: Joint loading is an important parameter in patients with osteoarthritis (OA). However, calculating joint loading relies on the performance of an extensive biomechanical analysis, which is not possible to do in a free-living situation. We propose the concept and design of a novel blended-care app called JOLO (Joint Load) that combines free-living information on activity with lab-based measures of joint loading in order to estimate a subject's functional status. (2) Method: We used an iterative design process to evaluate the usability of the JOLO app through questionnaires. The user interfaces that resulted from the iterations are described and provide a concept for feedback on functional status. (3) Results: In total, 44 people (20 people with OA and 24 health-care providers) participated in the testing of the JOLO app. OA patients rated the latest version of the JOLO app as moderately useful. Therapists were predominantly positive; however, their intention to use JOLO was low due to technological issues. (4) Conclusion: We can conclude that JOLO is promising, but further technological improvements concerning activity recognition, the development of personalized joint loading predictions and a more comfortable means to carry the device are needed to facilitate its integration as a blended-care program.