Skill assessment of an epidural anesthesia using the PeriSIM simulator

Thibault Senac (1) , Arnaud Lelevé (1) , Richard Moreau (1) , Laurent Krähenbühl (1) , Florent Sigwalt (2) , Christian Bauer (2)

1 AIS - Ampère, Département Automatique pour l'Ingénierie des Systèmes
2 HCL - Hospices Civils de Lyon

Currently, the training in the lumbar epidural anesthesia procedure, a very common procedure, is mainly performed on patients under the supervision of experts. The reason for this situation is that the simulators that exist on the market are not realistic enough to efficiently learn this particularly haptic-sense-based gesture. To avoid this ethical issue and provide an efficient, repeatable, and affordable way of safely learning this gesture, the Ampére laboratory designed PeriSIM: a haptic training computer-based simulator. In this article, the trainees’ skill assessment is tackled. This work presents various machine learning approaches to the evaluation of trainees and introduces a complete skill assessment algorithm to use in conjunction with the PeriSIM simulator. This work also aims to determine the important variables of an lumbar epidural anesthesia procedure for objective assessment purpose.

Mots clés: Needles; Anesthesia; Ligaments; Force; Measurement; Acceleration; Training

Domaines: Automatique / Robotique

Thibault Senac, Arnaud Lelevé, Richard Moreau, Laurent Krähenbühl, Florent Sigwalt, et al.. Skill assessment of an epidural anesthesia using the PeriSIM simulator. IEEE Transactions on Medical Robotics and Bionics, 2021, 3 (1), pp.106-114. ⟨10.1109/TMRB.2020.3048247⟩. ⟨hal-03092054⟩