Effect of force feedback on performance of robotics-assisted suturing
Bibliographic record
Abstract
This paper is aimed at exploring the effect of force feedback on the performance of a knot-tightening task in robotics-assisted minimally invasive surgery (RAMIS). In this work, we evaluate performance during the knot-tightening task in three scenarios: without force feedback, with visual force feedback and with direct force reflection on the subject's hand. Different performance measures have been implemented: quality of the knot, amount and consistency of the tightening force applied on the suture, user's control of the instrument, tissue damage, and task completion time. Seven subjects participated in this study and were asked to tighten the second throw of surgical knots using a dual arm teleoperation system that is capable of force reflection in 7 Degrees of Freedom (DOFs), 6-DOF rigid body motion plus the gripper. The results show that visual force feedback allows superior performance in the quality of the suture knots with high consistency in the tightening force, while direct force feedback can significantly improve the user's control of the instrument.
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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 | 0.009 |
| 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 | 0.000 | 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".