A 3-DOF compact haptic interface for endoscopic endonasal approach surgery simulation
Bibliographic record
Abstract
Endoscopic endonasal approach surgery is now the preferred treatment for most pituitary and related skull base tumors. However, this procedure requires a high level of hands-on skills and rich clinical experience. During the operation, haptic feedback, as the only one sense of bidirectional information interaction, plays an important role in surgical decision-making especially for bone-drilling. Existing surgical simulators provide either no haptic device or multipurpose haptic devices, which is difficult to reproduce the characteristics of surgical tool handling. In this paper, a custom-designed 3-DOF (pitch, yaw, radial) compact haptic interface for this surgery simulation is presented. It is dedicated to mimicking the touch sense of the surgical tools inserted through the nostril. Its main innovation is the mechanism design to maintain as much fidelity of the tool handling in the surgical training as in a real operation. The mechanism design is presented in detail as well as the kinematics and the force transmission. The mechanical characteristics of this haptic interface are also analyzed and presented.
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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) | 0.001 | 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) | 0.005 | 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".