A piezoresistive tactile sensor for tissue characterization during catheter‐based cardiac surgery
Bibliographic record
Abstract
BACKGROUND: Currently, most of mitral valve annuloplasty surgeries are performed by using open heart surgery. However, if such operation would be performed by using minimally invasive surgery via catheter-based techniques (CBT), it offers various advantages for both surgeons and patients. METHODS: Two piezoresistive force sensors are used in the structure of the tactile sensor, which can easily be miniaturized and integrated into surgical catheters. The tactile sensor was fabricated and tested to characterize different elastomers, as the phantom of cardiac tissues. Based on a developed finite element analysis (FEA) of the elastomers, the interaction between the sensor and those materials were modelled to validate the output of the sensor. RESULTS: The results of the mechanical and psychophysical tests confirm the capability of the proposed sensor to measure the relative hardness/softness of different soft tissues. CONCLUSIONS: The proposed tactile sensor will help surgeons to characterize different types of cardiac tissues and would facilitate the use of CBT to perform mitral valve annuloplasty.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 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".