Differentiating Sitting, Standing, and Walking Through Regional Plantar Pressure Characteristics
Bibliographic record
Abstract
Prolonged static weight bearing (WBR) is thought to aggravate plantar heel pain and is common in the workplace, which may put employees at greater risk of developing plantar heel pain. However, objective measures of physical activity and sedentary behaviors in the workplace are lacking, making it difficult to establish or refute the connection between work exposure and plantar heel pain. Characterizing loading patterns during common workplace postures will enhance the understanding of foot function and inform the development of new measurement tools. Plantar pressure data during periods of sitting, standing, and walking were measured in ten healthy participants using the F-Scan in-shoe measurement system (Tekscan Inc, Boston, MA). Peak and average pressure, peak and average contact area, and average pressure differential were analyzed in ten different regions of the foot. A two-way repeated measures analysis of variance (ANOVA) assessed the posture by foot region interaction for each measurement parameter; significant effects of posture by foot region were identified for all five measurement parameters. Ten foot region by measurement parameter combinations were found to significantly differentiate all three postures simultaneously; seven used pressure measures to differentiate while three used area measures. The heel, lateral midfoot (LM), and medial and central forefoot (CFF) encompassed nine of ten areas capable of differentiating all postures simultaneously. This work demonstrates that plantar pressure is a viable means to characterize and differentiate three common workplace postures. The results of this study can inform the development of measurement tools for quantifying posture duration at work.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".