PVDF-Based Microfabricated Tactile Sensor for Minimally Invasive Surgery
Bibliographic record
Abstract
This paper aimed to develop a miniaturized tactile sensor capable of measuring force and force position in minimally invasive surgery. Thein situmeasurement of tactile information is a step forward toward restoring the loss of the sense of touch that has occurred due to shift from traditional to minimally invasive surgeries. The sensor was designed such that it can sense low forces which could be comparable to those produced by pulsating delicate arteries, yet can withstand high forces comparable to grasping forces. The influence of some hidden anatomical features, such as lumps, voids, and arteries, on the stress distribution at the grasping surface was studied. In this paper, the capability of the sensor to determine and locate any point load was also investigated. The proposed sensor was designed and manufactured to be highly sensitive, using polyvinylidene fluoride (PVDF). The microfabrication procedure of the sensor, including corner compensation for toothlike projections and patterning of PVDF film, was discussed. The micromachined sensor was tested, and the experimental results were compared with the results of 3-D finite element modeling.$\hfill$[2007-0286]
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".