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Teleoperated robotic systems have introduced more intuitive control for minimally invasive surgery, but the optimal method for training remains unknown. Recent motor learning studies have demonstrated that exaggeration of errors helps trainees learn to perform tasks with greater speed and accuracy. We hypothesized that training in a force field that pushes the operator away from a desired path would improve their performance on a virtual reality ring-on-wire task. Forty surgical novices trained under a no-force, guidance, or error-amplifying force field over five days. Completion time, translational and rotational path error, and combined error-time were evaluated under no force field on the final day. The groups significantly differed in combined error-time, with the guidance group performing the worst. Error-amplifying field participants showed the most improvement and did not plateau in their performance during training, suggesting that learning was still ongoing. Guidance field participants had the worst performance on the final day, confirming the guidance hypothesis. Participants with high initial path error benefited more from guidance. Participants with high initial combined error-time benefited more from guidance and error-amplifying force field training. Our results suggest that error-amplifying and error-reducing haptic training for robot-assisted telesurgery benefits trainees of different abilities differently., Comment: 11 pages, 7 Figure, Under Review

Surgical procedures require a high level of technical skill to ensure efficiency and patient safety. Due to the direct effect of surgeon skill on patient outcomes, the development of cost-effective and realistic training methods is imperative to accelerate skill acquisition. Teleoperated robotic devices allow for intuitive ergonomic control, but the learning curve for these systems remains steep. Recent studies in motor learning have shown that visual or physical exaggeration of errors helps trainees to learn to perform tasks faster and more accurately. In this study, we extended the work from two previous studies to investigate the performance of subjects in different force field training conditions, including convergent (assistive), divergent (resistive), and no force field (null)., Comment: 2 pages, 2 figures, Hamlyn Symposium on Medical Robotics 2019

Purpose: Previous research has shown that obtaining non-expert crowd evaluations of surgical performances concords with the gold standard of expert surgeon review, and that faster playback speed increases ratings for videos of higher-skilled surgeons in laparoscopic simulation. The aim of this research is to extend this investigation to real surgeries that use non-expert crowd evaluations. We address two questions (1) whether crowds award more favorable ratings to videos shown at increased playback speeds, and (2) if crowd evaluations of the first minute of a surgical procedure differ from crowd evaluations of the entire performance. Methods: A set of 56 videos of practicing surgeons were used to evaluate the technical skill of the surgeons at each video playback speed used for the first minute of the previously rated performance, using the GEARS assessment criteria. Results: Crowds on average did rate videos higher as playback speed was increased. This effect was observed for both proficient and expert surgeons. Each increase in the playback speed by 0.8x was associated with, on average, a 0.16-point increase in the GEARS score for expert surgeons and a 0.27-point increase in GEARS score for proficient surgeons, with both groups being perceived as obtaining relatively equal skill at the fastest playback speed. It was also found that 22 out of the 56 surgeons were perceived to be significantly different in skill when just viewing the first minute of performance. Conclusion: The observed increase in skill ratings with video playback speed replicates findings for laparoscopy in [2], and extends to real robotic surgeries. Furthermore, the large differences in skill labels when comparing the first minute of surgery to the entire 15 minute video warrants further investigation into how much perceived skill ratings vary in time (sub-task level) vs. summative metrics (task level)., Comment: arXiv admin note: text overlap with arXiv:1911.00737

Purpose: Finding effective methods of discriminating surgeon technical skill is a complex problem to solve computationally. Previous research has shown non-expert crowd evaluations of surgical performances are as accurate as the gold standard, expert surgeon review. The aim of this research is to learn whether crowdsourced evaluators give higher ratings of technical skill to video of performances with increased playback speed, the use in discriminating skill levels, and if this increase is related to the evaluator consciously being aware that the video is being manually edited. Methods: A set of ten peg transfer videos (5 novices, 5 experts), were used to evaluate the perceived skill of the performers at each video playback speed used (0.4x-3.6x). Objective metrics used for measuring technical skill were also computed for comparison by manipulating the corresponding kinematic data of each performance. Two videos of an expert and novice performing dry lab laparoscopic trials of peg transfer tasks were used to obtain evaluations at each playback speed (0.2x-3.0x) of perception of whether a video is played at real-time playback speed or not. Results: We found that while both novices and experts had increased perceived technical skill as the video playback was increased, the amount of increase was significantly greater for experts. Each increase in playback speed by 0.4x was associated with, on average, a 0.72-point increase in the GOALS score (95% CI: 0.60-0.84 point increase; p < 0.001) for expert videos and only a 0.24-point increase in the GOALS score (95% CI: 0.13-0.36 point increase; p < 0.001) for novice videos. Conclusion: Due to the differential increase in perceived technical skill due to increased playback speed for experts, the difference between novice and expert skill levels of surgical performances may be more easily discerned by manually increasing the video playback speed.

Surgeons' technical skill directly impacts patient outcomes. To date, the angular motion of the instruments has been largely overlooked in objective skill evaluation. To fill this gap, we have developed metrics for surgical skill evaluation that are based on the orientation of surgical instruments. We tested our new metrics on two datasets with different conditions: (1) a dataset of experienced robotic surgeons and nonmedical users performing needle-driving on a dry lab model, and (2) a small dataset of suturing movements performed by surgeons training on a porcine model. We evaluated the performance of our new metrics (angular displacement and the rate of orientation change) alongside the performances of classical metrics (task time and path length). We calculated each metric on different segments of the movement. Our results highlighted the importance of segmentation rather than calculating the metrics on the entire movement. Our new metric, the rate of orientation change, showed statistically significant differences between experienced surgeons and nonmedical users / novice surgeons, which were consistent with the classical task time metric. The rate of orientation change captures technical aspects that are taught during surgeons' training, and together with classical metrics can lead to a more comprehensive discrimination of skills.