Using Mass Distribution Information to Model the Human Thigh for Body Segment Parameter Estimation
Bibliographic record
Abstract
Accurate estimations of body segment inertial parameters (BSPs) are required to calculate the kinetics of motion. The purpose of this study was to develop a geometric model of the human thigh segment based on mass distribution properties determined from dual energy x ray absorptiometry (DEXA). One hundred subjects from four populations underwent a DEXA scan and anthropometric measurements were taken. The mass distribution properties of the thigh segment were determined for 20 subjects, a geometric model was developed, and the model was applied to the remaining 80 subjects. The model was validated by comparing to benchmark DEXA measurements. Four other popular models in the literature were also evaluated in the same manner No one set of predictors performed best for a particular group or BSP, however modeling the mass distribution properties of the segment allows the assumption of constant density while still accurately representing the inertial properties of the segment and provides promise for future development of BSP models.
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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 | 0.001 | 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 | 0.000 |
| 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".