Robotics-assisted catheter manipulation for improving cardiac ablation efficiency
Bibliographic record
Abstract
The quality of contact between the catheter tip and cardiac tissue has been identified as an important factor in the efficacy of the catheter-based cardiac ablation procedures. However, maintaining a constant tip/tissue contact force during the procedure is difficult due to cardiac and respiratory motions. Robotic manipulation of the catheter has the potential to overcome this difficulty and decrease the range of variations in the contact force during the ablation procedure. This paper investigates the possibility of performing motion compensation for conventional steerable ablation catheters using a robotic manipulator. The behavior of such catheters is analyzed in free space as well as in contact with static and moving targets and the limitations in the actuation mechanism are identified. Based on this analysis, a technique for synchronizing the motion of the catheter tip with cardiac motion is proposed. The suggested control system estimates the frequency of the moving target and reshapes the input trajectory accordingly. The performance of the resulting system is evaluated experimentally. The results show that in the experimental setting, the proposed technique reduces the variations in the contact force and noticeably improves the quality of tip/tissue 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 | 0.000 |
| 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 | 0.000 | 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".