Gait biomechanics and postural adaptations in forward head posture: a comparative cross-sectional study
Bibliographic record
Abstract
Abstract Background Forward head posture (FHP) is a common postural deviation in the sagittal plane. Despite the growing interest in FHP, research on gait biomechanics in individuals with FHP remains scarce. This study aimed to investigate gait biomechanics in FHP, with a gait performance-based craniovertebral angle (CVA) cut-off. Methods Forty-eight participants were included in the study, with CVA measurements used to assess head-and-neck posture. Three-dimensional kinematic and kinetic data were collected using a motion capture system during three walking trials at preferred speeds. Spatiotemporal gait parameters, joint angles, joint moments, joint powers, joint forces, center of mass (COM) trajectories, and COM-to-joint (knee and ankle) angles were analyzed. Time-series data were compared between the two groups using statistical parametric mapping to identify potential changes during the gait cycle. Results Forty-eight participants were divided into control (n = 26) and FHP (n = 22) groups based on a CVA cut-off of 44 degrees determined by K-means clustering. There were no significant differences in spatiotemporal gait parameters between the control and FHP groups. However, the FHP group exhibited significantly increased trunk flexion during the loading response and initial midstance (2.21–14.50%, p = 0.047), as well as pre-swing and initial swing phases of the gait cycle (46.45–68.86%, p = 0.039). The COM-to-knee angle was significantly reduced during mid-swing in the FHP group (71.26–87.92%, p = 0.007). Additionally, significant differences in sagittal knee joint power and longitudinal joint forces at the knee and ankle were observed in the final stages of the gait cycle (p < 0.05). No significant differences were found in COM trajectories or other gait parameters. Conclusion This study identified phase-specific compensatory trunk flexion in individuals with FHP, despite preserved overall gait characteristics. A CVA cut-off of 44 degrees was proposed as a criterion for diagnosing FHP based on walking performance. These findings suggest that individuals with FHP employ specific biomechanical adaptations to maintain gait stability and underscore the importance of considering biomechanical adaptations in FHP diagnosis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".