AI-Enabled Telerehabilitation for Chronic Nonspecific Neck Pain: Multicenter Randomized Controlled Trial
Background: Exercise therapy is effective in managing chronic nonspecific neck pain (CNP). Nevertheless, the high burden of CNP continues to place pressure on existing rehabilitation services, especially in remote or resource-constrained settings where continuous and standardized physical therapy may be difficult to access. By combining home-based exercise with remote supervision and movement feedback, AI-enabled telerehabilitation may broaden access to rehabilitation and support the continued management of CNP. Objective: This study examined whether an AI-enabled telerehabilitation program was noninferior to standard outpatient rehabilitation for improving neck-related disability in individuals with CNP and compared the effects of the 2 interventions on pain, health-related quality of life, and cervical range of motion. Methods: This multicenter, prospective, parallel-group randomized noninferiority trial was conducted at Peking Union Medical College Hospital and Beijing Jishuitan Hospital. Patients with CNP of at least 3 months' duration were randomized 1:1 to a telerehabilitation group (TG) or outpatient rehabilitation group (OG) using concealed, web-based, variable blocks stratified by center and baseline Neck Disability Index (NDI) severity. Both groups completed identical 24-week strengthening and stretching programs (3 sessions per wk; ≈30 min per session) and were assessed at weeks 0, 4, 8, 12, and 24. TG trained at home using sensor-based movement recognition and threshold rules; OG received face-to-face outpatient rehabilitation. Week-24 NDI was the primary outcome; Numeric Pain Rating Scale (NPRS), EQ-5D, and cervical range of motion were secondary. Noninferiority required the upper 95% CI bound of the TG-OG NDI difference to be <10 percentage points (5/50). Analyses were intention-to-treat; assessors and statisticians were blinded. Results: =.15) at week 24. At week 24, the upper 95% CI bound was below the prespecified noninferiority margin of 10 percentage points on the 0 to 100 NDI scale, equivalent to 5 points on the original 0 to 50 scale, demonstrating noninferiority of TG. Both groups showed clinically meaningful reductions in NDI, with comparable improvements in NPRS, EQ-5D, and cervical range of motion. No intervention-related harms occurred. Conclusions: Over 24 weeks, AI-enabled telerehabilitation was noninferior to exercise-matched outpatient rehabilitation for neck-related disability, with broadly comparable improvements in pain, health-related quality of life, and cervical range of motion. AI-enabled telerehabilitation may be a practical alternative for patients with CNP who are unable to attend outpatient rehabilitation.
Authors
- Yiwei Zhao (ORCID: https://orcid.org/0000-0003-3935-5637)
- Ye Lin (ORCID: https://orcid.org/0000-0001-8195-9042)
- D Liu (ORCID: https://orcid.org/0000-0002-7372-0098)
- Siyi Cai (ORCID: https://orcid.org/0000-0003-2174-0297)
- Yanbin Zhang (ORCID: https://orcid.org/0000-0001-7779-4775)
- Jiamin Zheng (ORCID: https://orcid.org/0009-0003-2766-2645)
Institutions
- Capital Medical University (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking Union Medical College Hospital (CN)
- Beijing Jishuitan Hospital (CN)
- University of Chicago (US)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2026-10-15
- DOI
- https://doi.org/10.2196/87487
- Primary Topic
- Musculoskeletal pain and rehabilitation
- Type
- article
- Field-Weighted Citation Impact
- 0.00