A haptic laparoscopic trainer based on affine velocity analysis: engineering and preliminary results

Abstract

Background There is a general agreement upon the importance of acquiring laparoscopic skills outside the operation room through simulation-based training. However, high-fidelity simulators are cost-prohibitive and elicit a high cognitive load, while low-fidelity simulators lack effective feedback. This paper describes a low-fidelity simulator bridging the existing gaps with affine velocity as a new assessment variable. Primary validation results are also presented. Methods Psycho-motor skills and engineering key features have been considered e.g. haptic feedback and complementary assessment variables. Seventy-seven participants tested the simulator (17 expert surgeons, 12 intermediates, 28 inexperienced interns, and 20 novices). The content validity was tested with a 10-point Likert scale and the discriminative power by comparing the four groups’ performance over two sessions. Results Participants rated the simulator positively, from 7.25 to 7.72 out of 10 (mean, 7.57). Experts and intermediates performed faster with fewer errors (collisions) than inexperienced interns and novices. The affine velocity brought additional differentiations, especially between interns and novices. Conclusion This affordable haptic simulator makes it possible to learn and train laparoscopic techniques. Self-assessment of basic skills was easily performed with slight additional cost compared to low-fidelity simulators. It could be a good trade-off among the products currently used for surgeons' training.

Video-based Surgical Skills Assessment using Long term Tool Tracking

“…Tool trajectory-based metrics have been calculated using robotic system kinematic output [27,30,20]. Estimating instrument trajectories from the laparoscope video feed using image-based tracking can unlock the ability to further explore automated assessment of technical skills, as no extra sensors or robotic system access are needed.…”