This paper is in the following e-collection/theme issue:

Mobile Health (mhealth) (2974) Innovations in Exercise Rehabilitation (215) mHealth for Wellness, Behavior Change and Prevention (2912) Technology in Physiotherapy (136) mHealth for Rehabilitation (267) Portable and Mobile Technologies for Rehabilitation (156)

Published on in Vol 23, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26658, first published .
App-Based Feedback for Rehabilitation Exercise Correction in Patients With Knee or Hip Osteoarthritis: Prospective Cohort Study

App-Based Feedback for Rehabilitation Exercise Correction in Patients With Knee or Hip Osteoarthritis: Prospective Cohort Study

App-Based Feedback for Rehabilitation Exercise Correction in Patients With Knee or Hip Osteoarthritis: Prospective Cohort Study

Authors of this article:

Johanna Theresia Biebl1 Author Orcid Image ;   Marzena Rykala1 Author Orcid Image ;   Maximilian Strobel2 Author Orcid Image ;   Pawandeep Kaur Bollinger2 Author Orcid Image ;   Bernhard Ulm3 Author Orcid Image ;   Eduard Kraft1 Author Orcid Image ;   Stephan Huber2 Author Orcid Image ;   Andreas Lorenz1 Author Orcid Image
Article Authors Cited by (14) Tweetations (10) Metrics

Journals

  1. Luna A, Denham M. AI provides congruent and prescriptive feedback for squat form: qualitative assessment of coaching provided by AI and physical therapist. Journal of Comparative Effectiveness Research 2022;11(14):1071 View
  2. Hribernik M, Umek A, Tomažič S, Kos A. Review of Real-Time Biomechanical Feedback Systems in Sport and Rehabilitation. Sensors 2022;22(8):3006 View
  3. Giravi H, Biskupiak Z, Tyler L, Bulaj G. Adjunct Digital Interventions Improve Opioid-Based Pain Management: Impact of Virtual Reality and Mobile Applications on Patient-Centered Pharmacy Care. Frontiers in Digital Health 2022;4 View
  4. Merolli M, Gray K, Choo D, Lawford B, Hinman R. Use, and acceptability, of digital health technologies in musculoskeletal physical therapy: A survey of physical therapists and patients. Musculoskeletal Care 2022;20(3):641 View
  5. Mennella C, Maniscalco U, De Pietro G, Esposito M. The Role of Artificial Intelligence in Future Rehabilitation Services: A Systematic Literature Review. IEEE Access 2023;11:11024 View
  6. Ibrahimov E, Horodynskyi S, Teleki Y, Olinyk O, Honcharuk L. Modern Views on Physical Rehabilitation of Patients with Osteoarthritis of the Knee Joint. Ukraïnsʹkij žurnal medicini, bìologìï ta sportu 2022;7(2):209 View
  7. Phan P, Mitragotri S, Zhao Z. Digital therapeutics in the clinic. Bioengineering & Translational Medicine 2023;8(4) View
  8. Chen T, Or C. Perceptions of a machine learning-based lower-limb exercise training system among older adults with knee pain. DIGITAL HEALTH 2023;9 View
  9. Marks R. Artificial Intelligence and Its Potential Application in Advancing Hip Osteoarthritis Care. Journal of Orthopaedic Science and Research 2023:1 View
  10. Han S, Kong S. A Pilot Study on the Efficacy of an App-Based Rehabilitation Counselling Program after Total Knee Arthroplasty. Healthcare 2024;12(13):1329 View
  11. Shi J, Sit R. Impact of 25 Years of Mobile Health Tools for Pain Management in Patients With Chronic Musculoskeletal Pain: Systematic Review. Journal of Medical Internet Research 2024;26:e59358 View
  12. Cornella-Barba G, Farrens A, Johnson C, Garcia-Fernandez L, Chan V, Reinkensmeyer D. Using a Webcam to Assess Upper Extremity Proprioception: Experimental Validation and Application to Persons Post Stroke. Sensors 2024;24(23):7434 View
  13. Kang D, Park J, Yoon C, Choi C, Lee S, Park T, Chang S, Jang S. Multidisciplinary Digital Therapeutics for Chronic Low Back Pain Versus In-Person Therapeutic Exercise with Education: A Randomized Controlled Pilot Study. Journal of Clinical Medicine 2024;13(23):7377 View