A 6 DoF, Wearable, Compliant Shoe Sensor for Total Ground Reaction Measurement
Bibliographic record
Abstract
In this paper, we present a compliant six-axis sensor for total ground reaction measurement, the calibration methodology, and preliminary data. The sensor is intended for gait analysis and is designed to have minimal effect on natural gait. A triaxial optical force sensor is combined with an array of pressure sensing films to form a wearable compliant six-axis force/moment sensor. Two sensor units were developed for the toe and heel and used in two types of experiments: stepping on the sensors that are mounted on the ground and attaching the sensors under the shoe while walking. The data from the sensors are compared with measurements obtained from a standard force plate. The deflections induced by the sensor compliance exhibit a slight nonlinear force-deflection relation. Regardless of the nonlinear effects, the sensor is accurately calibrated with a linear least squares method. To see how well these nonlinearities could be calibrated for, a nonlinear calibration with a neural network was used. For the sensors attached to the floor, a linear calibration achieved an RMSE of 4.49% while the neural network achieves 2.68%. For the wearable sensor, the linear calibration RMSE was 9.39% and the neural network RMSE was 5.21%. When the orientation data of the sensors (measured by a motion capture system) were added as an input to the neural network calibration, the RMSE was reduced to 3.25%.
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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 | 0.001 | 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".