Reliability and usability of a novel inertial sensor-based system to test craniocervical flexion movement control
Bibliographic record
Abstract
BACKGROUND: Neck pain has a significant global impact, ranking as the fourth leading cause of disability. Recurrent neck pain often leads to impaired sensorimotor control, particularly in craniocervical flexion (CFF). The Craniocervical Flexion Test (CCFT) has been widely investigated to assess the performance of deep cervical flexor muscles. However, its use requires skilled assessors who need to subjectively detect compensations, progressive increases in range of motion (ROM) or excessive superficial flexor activation during the test. The aim of this study was to design and develop a novel Craniocervical Flexion Movement Control Test (CFMCT) based on inertial sensor technology and real-time computer feedback and to evaluate its safety and usability, as well as inter and intra-rater reliability in both healthy individuals and patients with neck pain. METHODS: We used inertial sensor technology associated with new software that provides real-time computer feedback to assess CCF movement control through two independent test protocols, the progressive consecutive stages protocol (including progressive incremental stages of ROM) and the random stages protocol (providing dynamic and less predictable movement patterns). We determined intra and inter-rater reliability and standard error of the measurement for both protocols. The participants rated their usability was analysed through the System Usability Scale (SUS) and possible secondary effects associated with the tests were registered. RESULTS: The progressive consecutive stages protocol and the random stages protocol were safe and easy to use (SUS scores of 82.00 ± 11.55 in the pain group and 79.56 ± 13.36 in the asymptomatic group). The progressive consecutive stages protocol demonstrated good inter-rater reliability (intraclass correlation coefficient [ICC] ≥ 0.75) and moderate to good intra-rater reliability (ICC 0.62-0.80). However, the random stages protocol exhibited lower intra-rater reliability, especially in the neck pain group, where the reliability values were poor in some cases (ICC 0.48-0.72). CONCLUSION: The CFMCT (progressive consecutive stages protocol) is a promising instrument to evaluate CCF motor control in patients with chronic neck pain. It has potential for telehealth assessment and easy adherence for exercise prescription and seems to be a safe and usable tool for patients with pain and asymptomatic individuals. Its use as a test or for exercise needs to be further investigated to facilitate its transfer to clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".