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

Innovations in Exercise Rehabilitation (213) Wearable Devices and Sensors (888) mHealth for Treatment Adherence (397) Machine Learning (1465) mHealth for Rehabilitation (263) Emerging Technologies for Rehabilitation (261) Technology in Physiotherapy (134)

Published on in Vol 8, No 1 (2021): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21374, first published .
Adherence Patterns and Dose Response of Physiotherapy for Rotator Cuff Pathology: Longitudinal Cohort Study

Adherence Patterns and Dose Response of Physiotherapy for Rotator Cuff Pathology: Longitudinal Cohort Study

Adherence Patterns and Dose Response of Physiotherapy for Rotator Cuff Pathology: Longitudinal Cohort Study

Authors of this article:

David Burns1, 2 Author Orcid Image ;   Philip Boyer1 Author Orcid Image ;   Helen Razmjou1, 3, 4 Author Orcid Image ;   Robin Richards2, 5 Author Orcid Image ;   Cari Whyne1, 2 Author Orcid Image
Article Authors Cited by (19) Tweetations (16) Metrics

Journals

  1. Alfakir A, Arrowsmith C, Burns D, Razmjou H, Hardisty M, Whyne C. Detection of Low Back Physiotherapy Exercises With Inertial Sensors and Machine Learning: Algorithm Development and Validation. JMIR Rehabilitation and Assistive Technologies 2022;9(3):e38689 View
  2. Cook J, Rucinski K, Crecelius C, Stannard J. Initial Outcomes After Unicompartmental Tibiofemoral Bipolar Osteochondral and Meniscal Allograft Transplantation in the Knee Using MOPS-Preserved Fresh (Viable) Tissues. The American Journal of Sports Medicine 2023;51(3):596 View
  3. Arrowsmith C, Burns D, Mak T, Hardisty M, Whyne C. Physiotherapy Exercise Classification with Single-Camera Pose Detection and Machine Learning. Sensors 2022;23(1):363 View
  4. 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
  5. Falla D, Devecchi V, Jiménez-Grande D, Rügamer D, Liew B. Machine learning approaches applied in spinal pain research. Journal of Electromyography and Kinesiology 2021;61:102599 View
  6. Burns D, Boyer P, Arrowsmith C, Whyne C. Personalized Activity Recognition with Deep Triplet Embeddings. Sensors 2022;22(14):5222 View
  7. Fleischhacker E, Gleich J, Smolka V, Neuerburg C, Böcker W, Helfen T. The Influence of Adherence to Orthosis and Physiotherapy Protocol on Functional Outcome after Proximal Humeral Fracture in the Elderly. Journal of Clinical Medicine 2023;12(5):1762 View
  8. Boyer P, Burns D, Whyne C. Evaluation of at-home physiotherapy. Bone & Joint Research 2023;12(3):165 View
  9. Sumner J, Lim H, Chong L, Bundele A, Mukhopadhyay A, Kayambu G. Artificial intelligence in physical rehabilitation: A systematic review. Artificial Intelligence in Medicine 2023;146:102693 View
  10. Velasquez Garcia A, Hsu K, Marinakis K. Advancements in the diagnosis and management of rotator cuff tears. The role of artificial intelligence. Journal of Orthopaedics 2024;47:87 View
  11. La Touche R, Pardo-Montero J, Grande-Alonso M, Paris-Alemany A, Miñambres-Martín D, Nouvilas-Pallejà E. Psychological, Pain, and Disability Factors Influencing the Perception of Improvement/Recovery from Physiotherapy in Patients with Chronic Musculoskeletal Pain: A Cross-Sectional Study. Healthcare 2023;12(1):12 View
  12. Maenhout A, Heijenk W, Glashouwer P, Quatacker L, Praet L, Borms D. Effect of a Novel Training Program in Patients With Chronic Shoulder Pain Based on Implicit Motor Learning: Pilot and Feasibility Study.. International Journal of Sports Physical Therapy 2024;19(1) View
  13. Sassi M, Villa Corta M, Pisani M, Nicodemi G, Schena E, Pecchia L, Longo U. Advanced Home-Based Shoulder Rehabilitation: A Systematic Review of Remote Monitoring Devices and Their Therapeutic Efficacy. Sensors 2024;24(9):2936 View
  14. Pérez-Porta I, Flórez-García M, García-Pérez F, Fernández-Matías R, Pérez-Manzanero M, Araujo-Narváez A, Urraca-Gesto M, Fernández-Lagarejos C, Plaza-Manzano G, Pérez-Fernández E, Velasco-Arribas M. Effects of a web application based on multimedia animations to support therapeutic exercise for rotator cuff-related shoulder pain: protocol for an open-label randomised controlled trial. BMJ Open 2024;14(7):e085381 View
  15. Hernandez-Sanchez S, Roses-Conde J, Martinez-Llorens N, Ruiz D, Espejo-Antúnez L, Tomás-Rodríguez I, Toledo-Marhuenda J, Albornoz-Cabello M. EFisioTrack System for Monitoring Therapeutic Exercises in Patients with Shoulder Orthopedic Injuries in a Hospital Setting: A Pilot Feasibility Study. Sensors 2024;24(15):4898 View
  16. Sassi M, Carnevale A, Mancuso M, Schena E, Pecchia L, Longo U. Machine‐learning models for shoulder rehabilitation exercises classification using a wearable system. Knee Surgery, Sports Traumatology, Arthroscopy 2024 View
  17. Poulsen L, Kirk J, Raunsø N, Stamp A, Lyng K, Clausen M. Unravelling interacting barriers and facilitators to adherence and delivery of exercise-based care in the treatment of Subacromial Pain Syndrome – an exploratory qualitative study. Disability and Rehabilitation 2024:1 View

Books/Policy Documents

  1. Burns D, Abbas A, Toor J, Hardisty M. AI in Clinical Medicine. View
  2. Myers T, Mannava S. Orthopaedic Sports Medicine. View