Switched-Impedance Control of Surgical Robots in Teleoperated Beating-Heart Surgery
Bibliographic record
Abstract
A novel switched-impedance control method is proposed and implemented for telerobotic beating-heart surgery. Differing from cardiopulmonary-bypass-based arrested-heart surgery, beating-heart surgery creates challenges for the human operator (surgeon) due to the heart’s fast motions and, in the case of a teleoperated surgical robot, the oscillatory haptic feedback to the operator. This paper designs two switched reference impedance models for the master and slave robots to achieve both motion compensation and nonoscillatory force feedback during slave–heart interaction. By changing the parameters of the impedance models, different performances for both robots are obtained: (a) when the slave robot does not make contact with the beating heart, the slave robot closely follows the motion of the master robot as in a regular teleoperation system, (b) when contact occurs, the slave robot automatically compensates for the fast motions of the beating heart while the human operator perceives the nonoscillatory component of the slave–heart interaction forces, creating the feeling of making contact with an idle heart for the human operator. The proposed method is validated through simulations and experiments.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".