AI-Assisted Physiotherapy for Patients with Non-Specific Low Back Pain: A Systematic Review and Meta-Analysis
Article
Kapil, D., Wang, J., Olawade, D. B. and Vanderbloemen, L. 2025. AI-Assisted Physiotherapy for Patients with Non-Specific Low Back Pain: A Systematic Review and Meta-Analysis. Applied Sciences. 15 (3), p. Art. 1532. https://doi.org/10.3390/app15031532
Authors | Kapil, D., Wang, J., Olawade, D. B. and Vanderbloemen, L. |
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Abstract | Background: Non-specific low back pain (LBP) is a widespread condition with significant impacts on physical activity, muscle strength, psychological well-being, and economic status. Traditional physiotherapy shows variable efficacy, prompting growing interest in AI-assisted physiotherapy for its potential to offer personalized feedback and multidisciplinary care integration. Objective: This systematic review and meta-analysis aimed to evaluate AI-assisted physiotherapy’s effectiveness in reducing pain intensity and functional impairment and improving mental health compared to usual physiotherapy. Method: A comprehensive search strategy was employed across Embase, MEDLINE, Cochrane Library, and Web of Science databases from inception to 30 May 2024. Comparative studies were identified and screened using PICOS criteria. Data extraction involved detailed study characteristics and outcomes, with methodological quality assessed via the Cochrane Risk of Bias tool. Meta-analyses using random-effects models calculated standardized mean differences (SMDs). Results: Eight studies met the inclusion criteria. Compared to usual physiotherapy, AI-assisted physiotherapy did not demonstrate any statistically significant differences in outcomes across the aspects studied, including pain intensity (SMD = −0.2711, 95% CI: −0.5109 to −0.0313, p = 0.267), functional impairment (SMD = −0.2508, 95% CI: −0.5574 to 0.0559, p = 0.1089), and mental health (SMD = −0.0328, 95% CI: −0.1972 to 0.1316, p = 0.6956). These findings indicate that AI-assisted physiotherapy had no demonstrable additional effect compared to usual physiotherapy for patients with LBP. Sensitivity analyses were conducted to address inter-study heterogeneity, confirming the robustness of these results. Conclusions: While AI-assisted physiotherapy shows potential in managing LBP by providing personalized treatment and feedback, the current evidence does not demonstrate significant advantages over usual physiotherapy. Further large-scale, long-term, and methodologically rigorous randomized controlled trials are necessary to validate these findings, assess their clinical relevance, and explore broader public health applications. |
Journal | Applied Sciences |
Journal citation | 15 (3), p. Art. 1532 |
ISSN | 2076-3417 |
Year | 2025 |
Publisher | MDPI |
Publisher's version | License File Access Level Anyone |
Digital Object Identifier (DOI) | https://doi.org/10.3390/app15031532 |
Publication dates | |
Online | 03 Feb 2025 |
Publication process dates | |
Accepted | 31 Jan 2025 |
Deposited | 03 Feb 2025 |
Copyright holder | © 2025 The Authors |
https://repository.uel.ac.uk/item/8yz31
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