Dynamic interaction between a fingerpad and a flat surface: experiments and analysis
Bibliographic record
Abstract
Many neural and vascular diseases in hands and fingers have been related to the degenerative responses of local neural and vascular systems in fingers to excessive dynamic loading. Since fingerpads serve as a coupling element between the hand and the objects, the investigation of the dynamic coupling between fingertip and subjects could provide important information for the understanding of the pathomechanics of these neural and vascular diseases. In the present study, the nonlinear and time-dependent force responses of fingertips during dynamic contact have been investigated experimentally and theoretically. Four subjects (2 male and 2 female) with an average age of 24 years participated in the study. The index fingers of right and left hands of each subject were compressed using a flat platen via a micro testing machine. A physical model was proposed to simulate the nonlinear and time-dependent force responses of fingertips during dynamic contact. Using a force relaxation test and a fast loading test at constant loading speed, the material/structural parameters underlying the proposed physical model could be identified. The predicted rate-dependent force/displacement curves and time-histories of force responses of fingertips were compared with those measured in the corresponding experiments. Our results suggest that the force responses of fingertips during the dynamic contacts are nonlinear and time-dependent. The physical model was verified to characterize the nonlinear, rate-dependent force-displacement behaviors, force relaxations, and time-histories of force responses of fingertips during dynamic contact.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".