{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T10:38:24Z","timestamp":1792579104786,"version":"4.5.0"},"reference-count":45,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Rehabil Assist Technol"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Digital technologies have become common in postoperative orthopedic rehabilitation. The tendency toward this adoption appeared in the past decade. However, no standard method exists to classify their functional capabilities. This absence hinders practical implementation. Clinicians currently lack a structured framework to distinguish between the functional capabilities of different digital rehabilitation technologies effectively.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This scoping review aims to map digital interventions used in postsurgical orthopedic rehabilitation to a proposed Coordination, Alignment, Motivation, and Strength (CAMS) framework and to identify research trends, functional coverage, and gaps in current evidence.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n A systematic search was conducted across 5 databases: MEDLINE (via PubMed), Scopus, IEEE Xplore, Cochrane Central Register of Controlled Trials (CENTRAL), and the Physiotherapy Evidence Database (PEDro), following PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Studies were mapped to the proposed CAMS framework pillars. Multiple validated appraisal tools were applied descriptively according to study design: version 2 of the Cochrane risk-of-bias tool for randomized trials (RoB 2; n=32), the Newcastle-Ottawa Scale (NOS) for observational studies (n=2), and the Methodological Index for Non-Randomized Studies (MINORS) for nonrandomized designs (n=1).<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n A total of 35 studies met the inclusion criteria. Coordination was the most frequently addressed pillar (29\/35, 83%), followed by Motivation (26\/35, 74%). Alignment was addressed in 37% (13\/35) of studies, while Strength was the least represented pillar (12\/35, 34%). Overall, 49% (17\/35) of studies were rated \u201clow risk\u201d overall on the primary appraisal tool, 46% (16\/35) demonstrated \u201csome concerns,\u201d and 6% (2\/35) were rated \u201chigh risk,\u201d with performance bias identified as a consistent methodological characteristic across the corpus. Delivery models were predominantly hybrid (14\/35, 40%) or home-based (13\/35, 37%), with 8 studies (8\/35, 23%) using an exclusively clinical model.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Digital health has shown a notable increase in the kinematic monitoring feature, offering effective solutions to movement quality (Coordination and Alignment) and psychological engagement (Motivation). Nevertheless, there is a consistent gap in strength-related studies, as current decentralized tools lack the capability to quantify physiological load. The next phase of innovations should be a shift to integrated 4-pillar solutions that would coordinate resistance-based training with high-precision biomechanical monitoring. The CAMS framework is proposed as an exploratory classification tool to guide future research design and technology evaluation in postsurgical digital rehabilitation.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/100548","type":"journal-article","created":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T08:15:07Z","timestamp":1786436107000},"page":"e100548-e100548","source":"Crossref","is-referenced-by-count":0,"title":["Digital Technologies in Postsurgical Orthopedic Rehabilitation: Scoping Review Mapping Interventions to the CAMS Framework (2020\u20102025)"],"prefix":"10.2196","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6806-8034","authenticated-orcid":false,"given":"Ngan Kuen","family":"Lai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-5121-124X","authenticated-orcid":false,"given":"Hai","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9703-7043","authenticated-orcid":false,"given":"Tet Khuan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3973-3917","authenticated-orcid":false,"given":"Muhammad Nur Affendy","family":"Nor'a","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-3643-7518","authenticated-orcid":false,"given":"Jeffery","family":"Sijore","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-0247-6668","authenticated-orcid":false,"given":"Wei Yang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1299-8179","authenticated-orcid":false,"given":"YongSheng","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,10,20]]},"reference":[{"issue":"2","key":"R1","doi-asserted-by":"publisher","first-page":"101","DOI":"10.2106\/JBJS.19.00695","article-title":"Effects of virtual exercise rehabilitation in-home therapy compared with traditional care after total knee arthroplasty: VERITAS, a randomized controlled trial","volume":"102","author":"Prvu Bettger","journal-title":"J Bone Joint Surg Am"},{"issue":"1","key":"R2","doi-asserted-by":"publisher","DOI":"10.1002\/msc.70041","article-title":"Effectiveness of virtual reality for pain management in musculoskeletal disorders across anatomical regions: a systematic review and meta-analysis","volume":"23","author":"Zitti","journal-title":"Musculoskeletal Care"},{"issue":"10","key":"R3","doi-asserted-by":"publisher","DOI":"10.1177\/23259671241271729","article-title":"Effectiveness of in-home, augmented reality-based telerehabilitation after anterior cruciate ligament reconstruction: a randomized controlled trial","volume":"12","author":"Lim","journal-title":"Orthop J Sports Med"},{"issue":"4","key":"R4","doi-asserted-by":"publisher","first-page":"44","DOI":"10.15758\/ajk.2025.27.4.44","article-title":"Emerging role of visual biofeedback in rehabilitation following ACL reconstruction","volume":"27","author":"Kim","journal-title":"Asian J Kinesiol"},{"key":"R5","doi-asserted-by":"publisher","DOI":"10.3389\/fbioe.2023.1335251","article-title":"Effective evaluation of HGcnMLP method for markerless 3D pose estimation of musculoskeletal diseases patients based on smartphone monocular video","volume":"11","author":"Hu","journal-title":"Front Bioeng Biotechnol"},{"issue":"2","key":"R6","doi-asserted-by":"publisher","DOI":"10.3390\/s24020554","article-title":"Wearable sensor to monitor quality of upper limb task practice for stroke survivors at home","volume":"24","author":"Seo","journal-title":"Sensors (Basel)"},{"issue":"5","key":"R7","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1080\/17483107.2021.1906960","article-title":"Robotic assistive and rehabilitation devices leading to motor recovery in upper limb: a systematic review","volume":"18","author":"Khalid","journal-title":"Disabil Rehabil Assist Technol"},{"key":"R8","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2025.1531067","article-title":"Rehabilitation robotics and allied digital technologies: opportunities, barriers and solutions for improving their clinical implementation. 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