Tendon-sheath analysis for modeling and control of steerable ablation catheters
Bibliographic record
Abstract
Steerable catheters are key tools in performing cardiac ablation for treating arrhythmia (heart rhythm disorder). The catheter is steered through the vasculature from the insertion point in the groin area to the atrium. Effective contact between the distal ablation tip and cardiac tissue is established by rotating the catheter and adjusting the flexion in the catheter's distal shaft. The manipulation system of unidirectional steerable catheters uses a pull-wire mechanism that connects the proximal handle to the distal ablation tip. The mechanical design of this tendon-based transmission system satisfies constraints on the size and diameter of an ablation catheter, but shows nonlinear effects that introduce difficulties in manipulating the flexible distal tip. In order to control such flexion, in this paper, the steerable catheter is considered as a tendon-sheath-driven mechanism. Since it is not possible to affix a force sensor to measure tendon tension at the distal tip, transmission characteristics are obtained using force measurements at the proximal side and visual cues from the distal end. The tendon transmission model is then used to design a control system that compensates for the nonlinear effects of the actuation mechanism and generates the desired flexion at the distal tip. Performance of the proposed controller is evaluated through simulation studies and implementation on an experimental setup. The results show that the proposed control method significantly improves the performance of the system in attaining and tracking the desired tip angle. The results presented in this study contribute towards developing position control schemes for robotics-assisted catheter manipulation systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".