SynthesisFrontiers in bioengineering and biotechnology2025
Effectiveness of AI-assisted rehabilitation for musculoskeletal disorders: a network meta-analysis of pain, range of motion, and functional outcomes.
Synthesis in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Integrative Rehabilitation for War-Related Polytrauma: A Narrative Review of Multidimensional Strategies and Implementation Challenges.Healthcare (Basel, Switzerland) · 2026Review
- Artificial Intelligence in Orthopaedics: Clinical Performance, Limitations, and Translational Readiness-A Review.Journal of clinical medicine · 2026Review
- Evaluating the performance and acceptability of an artificial intelligence digital health exercise platform in females with and without axial spondyloarthritis: a phase I study.Advances in rheumatology (London, England) · 2026Article
- Effects of Exercise-Based Telerehabilitation for Knee Osteoarthritis: A Systematic Review and a Study Protocol.Bioengineering (Basel, Switzerland) · 2026Review
- Advances in rehabilitation for bone and joint pain: a critical narrative review of evidence, gaps, and future directions.Frontiers in pain research (Lausanne, Switzerland) · 2026Review
- Intelligent Rehabilitation: Advances in Artificial Intelligence for Musculoskeletal Rehabilitation: A Narrative Review.Orthopedic research and reviews · 2026Review
- Ethical Horizons in Robotic Rehabilitation: Ensuring Safe AI Use Under the EU AI Act.Medical sciences (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aims to compare the effectiveness of 13 artificial intelligence (AI)-assisted rehabilitation strategies for individuals with musculoskeletal disorders (MSDs), categorized based on different intervention types, including AI feedback systems, exergaming platforms, telerehabilitation, and robotic solutions. The analysis focuses on improvements in pain relief, functional outcomes, and range of motion (ROM), based on a network meta-analysis (NMA) of randomized controlled trials (RCTs). Methods: A systematic review and NMA were conducted in accordance with PRISMA guidelines. Four databases (PubMed, Embase, Cochrane Library, Web of Science) were searched for RCTs published between January 2000 and April 2025. A total of 33 RCTs involving participants with MSDs were included. Interventions were categorized into 13 AI-assisted rehabilitation strategies. The outcomes were grouped into three domains: pain, functional outcomes, and ROM. Surface under the cumulative ranking curve (SUCRA) values and mean ranks were used to compare the relative effectiveness of each intervention. The Risk of Bias (RoB 2) tool was used to assess the bias risk of the studies, and the Confidence in Network Meta-Analysis (CINeMA) tool was applied to evaluate the credibility of the evidence. Results: For pain relief, Therapeutic Exergaming (SUCRA = 87.6%) and Robotic Exoskeleton (SUCRA = 86.3%) ranked highest. In functional outcomes, Gamified Exergaming (SUCRA = 99.6%) and Hybrid Physical Therapy combined with Exergaming (SUCRA = 81.2%) showed superior results. For ROM, Single-Joint Rehab Robot (SUCRA = 84.7%) and AI-Feedback Motion Training (SUCRA = 83.7%) were most effective. Conventional or Usual Care and Asynchronous Telerehabilitation consistently ranked lower across all outcomes. Conclusion: This study demonstrates that AI-assisted rehabilitation strategies significantly improve pain relief, functional recovery, and ROM in individuals with MSDs. Interventions such as Therapeutic Exergaming, Robotic Exoskeletons, Gamified Exergaming, and Single-Joint Rehab Robots performed excellently in their respective domains, highlighting the potential of AI technologies in personalized treatment and enhancing patient recovery. However, further long-term research is needed to confirm the sustained effects of these interventions and optimize their clinical application. Systematic Review Registration: PROSPERO CRD420251057777.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.