Bibliographic record
Abstract
Balance impairment is common in the elderly, which may be improved by detecting eminent falls and informing the user.Force and foot localization sensors are necessary to measure the balance as required by such assistive devices.This thesis presents the design and evaluation of an insole for measurement of the complete ground reaction forces and center of pressure that can be integrated on a balance enhancement system.The insole was prototyped using rubber and a number of small force sensing elements.A calibration procedure was implemented for the sensors to calculate the vertical load and an artificial neural network model was implemented on training data to predict shear loads.Experiments with healthy subjects were conducted to evaluate the performance of the insole on both standing and walking conditions.The results show that the insole is capable of measuring the vertical component of the ground reaction force with good accuracy compared to a force plate, and the neural network was able to produce an estimate of the shear forces.Moreover, the insole is capable of measuring the variations of the center of pressure on different standing conditions and during walking. RMSEroot mean square error VGRF vertical ground reaction force xviii
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".