Center of Mass Approximation During Walking as a Function of Trunk and Swing Leg Acceleration
Bibliographic record
Abstract
The 3D center of body mass (COM) trajectory provides us with a measure of movement performance and level of stability while walking. As an alternative to directly calculating the COM from motion trajectories and anthropometric data, we propose developing models to estimate the COM trajectory during walking on irregular surfaces. The inputs to the models were acquired via two accelerometers, one representing the trunk segment placed on T2 and the second representing the swing leg placed on the lateral malleolus. The subjects walked on a fixed surface and encountered an uneven, irregular surface, causing instability in the balance system. The results were encouraging, providing an estimate of the COM trajectory with a low error of 4.17plusmn1.94%. The reasonable accuracy, portability, ease of use and low cost (compared with video motion analysis systems) of the accelerometers increases the range of clinical applications of the proposed method
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".