A Sensorized Instrument for Skills Assessment and Training in Minimally Invasive Surgery
Bibliographic record
Abstract
Minimally invasive surgery (MIS) is carried out using long, narrow instruments and significantly reduces trauma to the body, postoperative pain, and recovery time. Unfortunately, the restricted access conditions, limited instrument motion, and degraded sense of touch inherent in MIS result in new perceptual-motor relationships, which are unfamiliar to the surgeon and require training to overcome. Current training methods do not adequately address the needs of surgeons interested in acquiring these skills. Although a significant amount of research has been focused on the development of sensorized systems for surgery, there is still a need for a system that can be used in any training scenario (laparoscopic trainer, animal laboratories, or real surgery) for the purpose of skills assessment and training. A sensorized laparoscopic instrument has been designed that is capable of noninvasively measuring its interaction with tissue in the form of forces or torques acting in all five degrees-of-freedom (DOFs) available during MIS. Strain gauges attached to concentric shafts within the instrument allow the forces acting in different directions to be isolated. An electromagnetic tracking system is used for position tracking. Two prototypes of the sensorized instrument were constructed. Position calibration shows a maximum root mean square (RMS) error of 1.3 mm. The results of the force calibration show a maximum RMS error of 0.35 N for the actuation force, 0.07 N in the x and y directions, and 1.5 N mm for the torque calibration with good repeatability and low hysteresis. Axial measurements were significantly affected by drift, noise, and coupling leading to high errors in the readings. Novel sensorized instruments for skills assessment and training have been developed and a patent has been filed for the design and operation. The instruments measure forces and torques acting at the tip of the instrument corresponding to all five DOFs available during MIS and provide position feedback in six DOFs. The instruments are similar in shape, size, and weight to traditional laparoscopic instruments allowing them to be used in any training environment. Furthermore, replaceable tips and handles allow the instruments to be used for a variety of different tasks.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".