FIDGM: A Force Myography and IMU Dataset for Precise Gait Measurement
Bibliographic record
Abstract
This dataset contains sensor values from Force Myography (FMG) sensors and Inertial Measurement Units (IMUs) and corresponding Ankle Joint Power and Ground Reaction Force. The FMG strap was positioned about two inches above the ankle of the left leg. Four IMUs were positioned on foot, distal shank, distal thigh, and proximal thigh of the left leg. There are sensors values and corresponding reference values from nine participants and five different walking speeds (0.4 m/s, 0.7 m/s, 1.0 m/s, 1.3 m/s, and 1.6 m/s). This dataset portrays how values from different sensors vary with respect to Ankle Joint Power and Ground Reaction Force. The dataset can be utilized to train machine learning models to predict Ankle Joint Power and Ground Reaction Force using FMG and IMUs sensor values, which in turn can eliminate the requirement of a complex biomechanical setup to measure Ankle Joint Power and Ground Reaction Force.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.007 |
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; both teacher heads agree on what is shown here.
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".