Increased risk for falling associated with obesity: mathematical modeling of postural control
Bibliographic record
Abstract
Recent epidemiological studies report that obesity is positively related to fracture incidence. In the present experiment, a model of postural control was used to examine the impact of an abnormal distribution of body fat in the abdominal area upon postural stability. Obese and lightweight humanoids were destabilized by imposing a small initial angular speed from a neutral standing position. To avoid a loss of stability yielding a stepping reaction or a fall, an ankle torque is necessary to counteract the perturbation. Three torque parameters--ankle torque onset, time to peak torque, and muscular ankle torque--were entered in a program to simulate the intrinsic variability of the human postural control system. A loss of stability was detected when the center of pressure exceeded stability margins. The most striking observation is the nonlinear increase of torque needed to stabilize the humanoid when the motor response was characterized by delayed temporal parameters. The effect was more pronounced when an anterior position of the center of mass was included in the simulations. This suggests that, when submitted to daily postural stresses and perturbations, obese persons (particularly those with an abnormal distribution of body fat in the abdominal area) may be at higher risk of falling than lightweight individuals.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".