A predictive model for classifying low back pain status base…
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- DOI 10.1186/s12891-026-09488-4
- PMID https://pubmed.ncbi.nlm.nih.gov/41501813
- PMCID https://www.ncbi.nlm.nih.gov/pmc/articles/12869960
- OpenAlex ID W7118448388
- Type Article
- Language EN
- Published 07 Jan 2026
- Volume 27 (1)
- Pages 94
- Source BMC Musculoskeletal Disorders
- Publisher BioMed Central
- FWCI 4.32
- Countries 2
- Institutions 2
- Added 08 Jan 2026
- Updated 28 Oct 2026
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A predictive model for classifying low back pain status based on lumbopelvic kinematics measured using inertial measurement units: a cross-sectional study
Article 2026 EN Gold
BACKGROUND: Low back pain (LBP) is a leading cause of disability worldwide. Impaired lumbopelvic control contributes to chronic and recurrent LBP, often presenting as aberrant movement patterns. This study aimed to investigate whether inertial measurement units (IMUs) can classify individuals with no LBP (NoLBP), chronic LBP (CLBP), and a history of LBP (HxLBP) based on lumbopelvic kinematics. MET…
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1 SDGsAuthors & Affiliations
6 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | Sasithorn Kongoun | Mahidol University (TH) | |
| 2 | Katayan Klahan | Mahidol University (TH) | — |
| 3 | Natchaya Rujirek | Mahidol University (TH) | — |
| 4 | Roongtiwa Vachalathiti | Mahidol University (TH) | |
| 5 | Jim Richards | University of Lancashire (GB) | |
| 6 | Peemongkon Wattananon Corresponding | Mahidol University (TH) |
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