Using a High Resolution Motion Capture System to Determine 6-DOF Whole-Body Vibration Accelerations
Bibliographic record
Abstract
Comprehensive investigations of the human response to vibration require many markers, accelerometers, and electrodes. The use of multiple measurement systems can result in time intensive subject preparation, large memory requirements for data storage and processing, skin motion artifacts, and subject encumbrance. The purpose of this study was to determine if a VICON™ motion capture system could reliably and accurately measure translational and rotational acceleration levels produced by mobile machines, thereby eliminating the need for accelerometers and potentially minimizing the aforementioned problems. Simulating these vibration exposures in a laboratory, it was found that translational displacements ≥ 0.1 mm produced absolute peak and RMS average acceleration measurement differences less than 5% between the VICON™ system and an accelerometer. The absolute peak and RMS rotational accelerations determined by the VICON™ system and those produced by a PRSCO™ hexapodrobot differed by 5.44 ± 3.87% and 3.57 ± 2.44% respectively. Accounting for the vibration attenuation of the human body, the VICON™ system also appears well suited for determining 6-DOF acceleration levels in laboratory seat-to-head vibration transmission studies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".