An integrator-backstepping control approach for out-of-plane needle deflection minimization
Bibliographic record
Abstract
In this paper, we develop a needle steering strategy designed to reduce the out-of-plane deflection of a flexible, bevel-tipped needle for clinical needle insertion applications. This is performed through an integrator-backstepping approach. Integrator-backstepping is a nonlinear feedback controller design that divides the entire system into a sequence of smaller design problems that are easier to manage. Simulations were performed to observe the effects of our controller design on the system's response, specifically the rate at which the out-of-plane deflection converges. We tested our proposed method using a biological tissue phantom composed of two separate heterogeneous layers and using an 18 gauge brachytherapy needle. A paired-sample t-test was performed to compare out-of-plane needle deflection results with and without the use of our needle steering algorithm under varying bevel-angle starting conditions. Results showed a significant decrease in the out-of-plane needle deflection with the use of our controller at the 1% significance level. The absolute-mean out-of-plane needle deflection at a depth of 140 mm changed from 7.1 mm to 0.7 mm with the implementation of our needle steering approach. Our proposed steering method does not require “drilling” motions often encountered in duty-cycling controllers, and has been shown to be effective for clinical needles travelling through multiple heterogeneous tissue layers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".