A haptic laparoscopic trainer based on affine velocity analysis: engineering and preliminary results - Archive ouverte HAL
Journal Articles BMC Surgery Year : 2021

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.
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Dates and versions

hal-03174365 , version 1 (19-03-2021)

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Benjamin de Witte, Charles Barnouin, Richard Moreau, Arnaud Lelevé, Xavier Martin, et al.. A haptic laparoscopic trainer based on affine velocity analysis: engineering and preliminary results. BMC Surgery, 2021, 21 (1), ⟨10.1186/s12893-021-01128-z⟩. ⟨hal-03174365⟩
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