A new approach to laparoscopic skill assessment: Motion smoothness and bimanual coordination
Bibliographic record
Abstract
Reliable and objective methods for assessing surgical skill are essential for improving surgical skills and clinical outcomes. While conventional methods rely on subjective evaluations, motion analysis can offer a quantitative alternative. This study aims to use motion tracking data to analyze the motion smoothness and bimanual coordination of various surgical skill levels during laparoscopic surgery. The participants were recruited and grouped into an expert group, an intermediate group, and a novice group on the basis of their experience with laparoscopic surgery. They completed peg transfer, bimanual peg transfer, and rubber band translocation tasks. Motion smoothness was assessed via logarithmic dimensionless tooltip motion jerk, and the dynamic time warping metric of tooltips velocities was employed to assess bimanual coordination. Seventeen participants, with four experts, five intermediates, and eight novices, were included. Compared with novices, the experts exhibited smoother motion in both the dominant hand (peg transfer: 16.30 vs. 18.05, p = 0.004; bimanual peg transfer: 15.21 vs. 17.45, p = 0.004; rubber band translocation: 14.32 vs. 15.87, p = 0.004) and non-dominant hand (peg transfer: 16.32 vs. 18.22, p = 0.004; bimanual peg transfer: 15.32 vs. 17.52, p = 0.004; rubber band translocation: 14.33 vs. 15.77, p = 0.004), and superior bimanual coordination (peg transfer: 8.77 m/s vs. 13.28 m/s, p = 0.004; bimanual peg transfer: 6.29 m/s vs. 11.13 m/s, p = 0.004; rubber band translocation: 4.50 m/s vs. 7.13 m/s, p = 0.004) across all tasks. They also outperformed intermediates in motion smoothness in the non-dominant hand and bimanual coordination in the peg transfer (16.32 vs. 17.35, p = 0.016; 8.77 m/s vs. 11.89 m/s, p = 0.016) and bimanual peg transfer (15.32 vs. 16.22, p = 0.016; 6.29 m/s vs. 8.63 m/s, p = 0.032) tasks. Similarly, intermediates demonstrated smoother motion in the non-dominant hand (peg transfer: 17.35 vs. 18.22, p = 0.002; bimanual peg transfer: 16.22 vs. 17.52, p = 0.002) and dominant hand (bimanual peg transfer: 16.06 vs. 17.45, p = 0.011), and better bimanual coordination (peg transfer: 11.89 m/s vs. 13.28 m/s, p = 0.002; bimanual peg transfer: 8.63 m/s vs. 11.13 m/s, p = 0.002) than novices did in these tasks. This study revealed that motion smoothness and bimanual coordination are capable of facilitating surgical skill differentiation across various skill levels. These findings underscore the utility of motion metrics for objective surgical skill assessment, potentially reducing the subjectivity, bias, and associated costs of conventional assessment approaches.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".