Assessment of a three-dimensional robotic model for biomechanical-data acquisition of human movement
Bibliographic record
Abstract
The use of a kinematic robotic model has not been implemented in the biomechanical-data acquisition protocol, as it has in workplace analysis, ergonomics and design. The purpose of this paper was to assess the use of a kinematic model to retrieve frames of human movements from data obtained at a low sampling frequency. From experimental trials with an original sampling frequency of 60 Hz, the data were sampled again at two lower frequencies, 5 Hz and 10 Hz. The model was then used to reconstitute the data to its original frequency (60 Hz). The results demonstrated that it was possible to retrieve a full 3-D human movement from a sampling rate lower than normal without sacrificing accuracy. It was observed from both reduced sampling frequencies that the error level was comparable to the usual accuracy of a DLT 3-D reconstruction technique. It was therefore concluded that the data retrieved from these two frequencies were very similar to the original data sampled at 60 Hz.
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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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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".