sEMG-based Motion Recognition for Robotic Surgery Training - A Preliminary Study - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2023

sEMG-based Motion Recognition for Robotic Surgery Training - A Preliminary Study

Abstract

Robotic surgery represents a major breakthrough in the evolution of medical technology. Accordingly, efficient skill training and assessment methods should be developed to meet the surgeon’s need of acquiring such robotic skills over a relatively short learning curve in a safe manner. Different from conventional training and assessment methods, we aim to explore the surface electromyography (sEMG) signal during the training process in order to obtain semantic and interpretable information to help the trainee better understand and improve his/her training performance. As a preliminary study, motion primitive recognition based on sEMG signal is studied in this work. Using machine learning (ML) technique, it is shown that the sEMG-based motion recognition method is feasible and promising for hand motions along 3 Cartesian axes in the virtual reality (VR) environment of a commercial robotic surgery training platform, which will hence serve as the basis for new robotic surgical skill assessment criterion and training guidance based on muscle activity information.Considering certain motion patterns were less accurately recognized than others, more data collection and deep learning-based analysis will be carried out to further improve the recognition accuracy in future research
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Dates and versions

lirmm-04192619 , version 1 (31-08-2023)

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Chenji Li, Chao Liu, Arnaud Huaulmé, Nabil Zemiti, Pierre Jannin, et al.. sEMG-based Motion Recognition for Robotic Surgery Training - A Preliminary Study. EMBC 2023 - 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Jul 2023, Sydney, Australia. ⟨10.1109/EMBC40787.2023.10340047⟩. ⟨lirmm-04192619⟩
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