{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T20:46:17Z","timestamp":1792097177211,"version":"4.4.0"},"reference-count":22,"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 Globally, sedentary behavior is a leading risk factor for noncommunicable diseases and premature death. Although telerehabilitation has emerged as a promising method to increase access to physical therapy, the potential of artificial intelligence (AI) and machine vision technologies to objectively monitor and promote physical activity (PA) in home settings remains underexplored.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This scoping review aimed to map and systematize current evidence on the use of AI and machine vision in telephysiotherapy to promote PA and reduce sedentary behavior among healthy adults.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n The review followed the Joanna Briggs Institute scoping review methodology and was reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. The PCC (population, concepts, and context) framework defined participants as healthy adults, the concept as AI or machine learning (ML) and machine vision technologies, and the context as remote, home-based telephysiotherapy for objective PA monitoring and\/or outcome measurement in interventions aimed at promoting daily activity. Searches were conducted in PubMed, ProQuest, Science Direct, and Wiley Online Library for peer-reviewed primary studies published between 2016 and 2024. Inclusion and exclusion criteria were applied systematically using the Rayyan platform.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Of 7253 initial records, 4 studies met the inclusion criteria. Identified digital solutions comprised ML algorithms (eg, extreme gradient boosting and hybrid classifiers), deep learning models such as graph convolutional networks, video-based center-of-pressure assessments using RGB cameras, and ontology-driven semantic data structuring for personalization. The most frequently studied technologies combined wearable sensors with ML-based behavior change frameworks to assess usability and prototype feasibility. However, none of the studies demonstrated statistically significant improvements in reducing sedentary time or increasing PA levels among participants. The studies predominantly used exploratory or pilot designs, with small sample sizes (range: 10\u201032 participants) and short follow-up periods (\u226412 wk), limiting the strength of the conclusions.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Current evidence on the application of AI and machine vision in telephysiotherapy remains scarce and largely exploratory. Although the integration of wearable technology and ML algorithms shows technical feasibility and personalization potential, there is insufficient evidence to confirm improvements in PA outcomes. Future research should prioritize longitudinal clinical trials, ensure the inclusion of diverse populations, and evaluate behavioral outcomes to determine the real-world impact of these technologies in telerehabilitation.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/80459","type":"journal-article","created":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T19:20:08Z","timestamp":1774293608000},"page":"e80459-e80459","source":"Crossref","is-referenced-by-count":0,"title":["Leveraging AI and Machine Vision in Telephysiotherapy for Promoting Physical Activity and Reducing Sedentary Behavior: Scoping Review"],"prefix":"10.2196","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-4995-2876","authenticated-orcid":false,"given":"Liva","family":"Redliha","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6554-0716","authenticated-orcid":false,"given":"Guna","family":"Semjonova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4874-7904","authenticated-orcid":false,"given":"Liva","family":"Araka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,10,15]]},"reference":[{"key":"R1","doi-asserted-by":"publisher","DOI":"10.9790\/1959-0905013041","article-title":"Prevalence of overweight and obesity and its associated factors among adult people at Chitwan, Nepal","volume":"9","author":"Adhikari","journal-title":"IOSR J Nurs Health Sci"},{"issue":"5","key":"R2","doi-asserted-by":"publisher","first-page":"625","DOI":"10.1177\/0269215516645148","article-title":"Real-time telerehabilitation for the treatment of musculoskeletal conditions is effective and comparable to standard practice: a systematic review and meta-analysis","volume":"31","author":"Cottrell","journal-title":"Clin Rehabil"},{"key":"R3","unstructured":"World health statistics 2024: monitoring health for the SDGs, sustainable development goals. World Health Organization; 2024. URL: https:\/\/iris.who.int\/server\/api\/core\/bitstreams\/74b12494-f213-4b5b-9533-18442147e1fb\/content [Accessed 29-04-2026]"},{"key":"R4","unstructured":"Rekomend\u0101cijas fizisko aktivit\u0101\u0161u veicin\u0101\u0161anai latvijas iedz\u012bvot\u0101jiem (politikas veidot\u0101jiem un \u012bstenot\u0101jiem) [Report in Latvian]. Latvijas Republikas Vesel\u012bbas ministrija; 2019. URL: https:\/\/www.vm.gov.lv\/lv\/media\/6408\/download [Accessed 29-04-2026]"},{"issue":"6","key":"R5","doi-asserted-by":"publisher","first-page":"365","DOI":"10.4082\/kjfm.20.0165","article-title":"Sedentary lifestyle: overview of updated evidence of potential health risks","volume":"41","author":"Park","journal-title":"Korean J Fam Med"},{"key":"R6","volume":"145","author":"Brennan","journal-title":"Stud Health Technol Inform"},{"issue":"3","key":"R7","doi-asserted-by":"publisher","first-page":"62","DOI":"10.3390\/ai6030062","article-title":"AI-driven telerehabilitation: benefits and challenges of a transformative healthcare approach","volume":"6","author":"Calabr\u00f2","journal-title":"AI"},{"issue":"10","key":"R8","doi-asserted-by":"publisher","first-page":"2119","DOI":"10.11124\/JBIES-20-00167","article-title":"Updated methodological guidance for the conduct of scoping reviews","volume":"18","author":"Peters","journal-title":"JBI Evid Synth"},{"issue":"7","key":"R9","doi-asserted-by":"publisher","first-page":"467","DOI":"10.7326\/M18-0850","article-title":"PRISMA Extension for Scoping Reviews (PRISMA-ScR): checklist and explanation","volume":"169","author":"Tricco","journal-title":"Ann Intern Med"},{"issue":"1","key":"R10","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1080\/1364557032000119616","article-title":"Scoping studies: towards a methodological framework","volume":"8","author":"Arksey","journal-title":"Int J Soc Res Methodol"},{"key":"R11","unstructured":"The use of machine vision and artificial intelligence in tele-physiotherapy to reduce sedentary lifestyles and promote physical activity: a scoping review. OSF. URL: https:\/\/doi.org\/10.17605\/OSF.IO\/SFC97 [Accessed 29-04-2026]"},{"issue":"1","key":"R12","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-022-24118-4","article-title":"Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation","volume":"12","author":"Chatterjee","journal-title":"Sci Rep"},{"key":"R13","unstructured":"Du C . Deep-learning\u2013based video analysis for human action evaluation [Dissertation]. University of California; 2022. URL: https:\/\/db.rsu.lv\/login?url=https:\/\/www.proquest.com\/dissertations-theses\/deep-learning-based-video-analysis-human-action\/docview\/2761184410\/se-2?accountid=32994 [Accessed 29-04-2026]"},{"key":"R14","unstructured":"Boyer P . Machine learning at-home physiotherapy adherence [Dissertation]. University of Toronto; 2023. URL: https:\/\/db.rsu.lv\/login?url=https:\/\/www.proquest.com\/dissertations-theses\/machine-learning-at-home-physiotherapy-adherence\/docview\/2889795235\/se-2?accountid=32994 [Accessed 29-04-2026]"},{"key":"R15","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.107485","article-title":"A deep learning system to monitor and assess rehabilitation exercises in home-based remote and unsupervised conditions","volume":"166","author":"Mennella","journal-title":"Comput Biol Med"},{"issue":"12","key":"R16","doi-asserted-by":"publisher","first-page":"380","DOI":"10.3390\/fi14120380","article-title":"Comparative analysis of skeleton-based human pose estimation","volume":"14","author":"Chung","journal-title":"Future Internet"},{"issue":"4","key":"R17","doi-asserted-by":"publisher","DOI":"10.3390\/healthcare13040411","article-title":"Modern smart gadgets and wearables for diagnosis and management of stress, wellness, and anxiety: a comprehensive review","volume":"13","author":"Jolly","journal-title":"Healthcare (Basel)"},{"issue":"2","key":"R18","doi-asserted-by":"publisher","first-page":"67","DOI":"10.3390\/act14020067","article-title":"Effectiveness of powered hand exoskeleton on upper extremity function in people with chronic stroke","volume":"14","author":"Yeh","journal-title":"Actuators"},{"issue":"2","key":"R19","doi-asserted-by":"publisher","first-page":"94","DOI":"10.7861\/futurehosp.6-2-94","article-title":"The potential for artificial intelligence in healthcare","volume":"6","author":"Davenport","journal-title":"Future Healthc J"},{"issue":"9","key":"R20","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1177\/1357633X211022907","article-title":"The clinical effectiveness of telehealth: a systematic review of meta-analyses from 2010 to 2019","volume":"29","author":"Snoswell","journal-title":"J Telemed Telecare"},{"issue":"16","key":"R21","doi-asserted-by":"publisher","DOI":"10.3390\/s23167238","article-title":"Telerehabilitation with ARC intellicare to cope with motor and respiratory disabilities: results about the process, usability, and clinical effect of the \u201cRicominciare\u201d pilot study","volume":"23","author":"Capecci","journal-title":"Sensors (Basel)"},{"issue":"3","key":"R22","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1080\/10400435.2019.1593260","article-title":"Assistive game controller for artificial intelligence\u2013enhanced telerehabilitation post-stroke","volume":"33","author":"Burdea","journal-title":"Assist Technol"}],"container-title":["JMIR Rehabilitation and Assistive Technologies"],"original-title":[],"language":"en","deposited":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T20:16:26Z","timestamp":1792095386000},"score":1,"resource":{"primary":{"URL":"https:\/\/rehab.jmir.org\/2026\/1\/e80459"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,15]]},"references-count":22,"URL":"https:\/\/doi.org\/10.2196\/80459","relation":{},"ISSN":["2369-2529"],"issn-type":[{"value":"2369-2529","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,15]]},"article-number":"v13i5e80459"}}