Computational study and validation of a novel passive hand tremor attenuator
Bibliographic record
Abstract
Tremors are a prevalent movement disorder due to a nervous system condition that leads to involuntary muscle movements observed in patients. This paper converts the tremorous anatomical human arm model to a single degree of freedom (SDOF) forced vibration problem. The mathematical modelling with Euler-Lagrange's equation is performed for the SDOF human arm model with two different potential vibration absorbers. A computational study is conducted on MATLAB Simulink by MathWorks Inc. (Natick, MA) to compare two absorbers, and the results are verified on the multibody dynamics simulation solution software, MSC Adams by Hexagon AB. It is concluded that the T beam-shaped vibration absorber represented a higher amplitude reduction, up to 80%, compared to the inertial mass absorber, which had an amplitude reduction of 65% over the range of frequencies. Experiments conducted with the T beam absorber prototype also support the computational findings. Future research focuses on designing an ergonomic wearable device with a proposed T-beam absorber that can passively attenuate the tremor at various frequencies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".