Determination of body segment masses and centers of mass using a force plate method in individuals of different morphology
Bibliographic record
Abstract
Body segment masses and center of mass (COM) locations are required to calculate intersegmental forces and net joint moments using inverse or forward dynamics equations. These inertial properties are estimated from methods involving cadavers or living individuals. The present clinical methods are limited to similar populations from which the anthropometric measures were obtained. This study presented a simple force plate method that can be used to determine subject-specific segment masses and COM locations and compared it to other well-known methods. The proposed method was tested in individuals with different body mass index (i.e., lean, normal, and obese) to verify its sensitivity. All the segmental mass and COM values obtained from the force plate method were within the range of those of the other methods for the entire sample. Significant differences were identified between the morphological groups in relative segmental masses at the upper arm and leg and foot, and COM locations at the leg and foot and head and trunk as obtained from the force plate method (p<0.05). The proposed method involves direct procedures to determine subject-specific segmental masses and COM locations. It is sensitive to detect differences between various morphological populations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".