Comparison of marker-based and center-of-pressure-based approaches for calculating the margin of stability
Bibliographic record
Abstract
Introduction The margin of stability (MoS) is a widely used biomechanical measure of dynamic stability during gait, typically computed as the distance between the extrapolated center of mass (xCoM) and the center of pressure (CoP). According to Hof's model, the CoP-based approach is considered the preferred approach for defining where the xCoM is relative to the BoS and calculating the MoS. However, marker-based approaches often need to be used in research and clinical settings due to practical constraints and the lack of standardization in marker selection introduces variability in MoS estimates. This study aimed to assess the difference between different marker-based approaches and the CoP-based approach. Methods Using an open-access dataset of 30 healthy adults walking at a self-selected speed, MoS was calculated continuously during the stance phase in both the anteroposterior (AP) and mediolateral (ML) directions. Various marker-based approaches were evaluated, including commonly used markers (AP: HEEL, TOE; ML: HEEL, ANKLE, M5, MID) and a novel approach using the most anterior (for AP MoS) or most lateral (for ML MoS) marker in contact with the ground at each time point (AP: MOST ANTERIOR; ML: MOST LATERAL). Differences were quantified using paired t -tests with statistical parametric mapping and root mean square differences (RMSD) relative to the CoP-based approach. Results Results showed that the MOST ANTERIOR approach had the closest agreement with the CoP-based approach for AP MoS (RMSD = 47.04 mm), while the HEEL marker provided the closest agreement with the CoP-based approach for the ML MoS estimates (RMSD = 17.93 mm). Conclusion These findings highlight the importance of marker selection in MoS analysis and suggest that specific marker configurations, particularly those grounded in foot-ground contact for the AP-MoS, provide closest estimates relative to the CoP-based approach. This study offers evidence-based recommendations for improving consistency and comparability in future MoS studies using marker-based approaches.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".