TY - JOUR
T1 - Multimodal Sensorimotor Integration for Expert-in-The-Loop Telerobotic Surgical Training
AU - Shahbazi, Mahya
AU - Farokh, Atashzar S.
AU - Ward, Christopher
AU - Talebi, Heidar Ali
AU - Patel, Rajni V.
N1 - Funding Information:
Manuscript received August 1, 2017; revised January 10, 2018; accepted May 21, 2018. Date of publication August 27, 2018; date of current version December 4, 2018. This paper was recommended for publication by Associate Editor A. Ude and Editor P. Dupont upon evaluation of the reviewers’ comments. This work was supported in part by the Natural Sciences and Engineering Research Council (NSERC) of Canada under the Discovery Grants Program under Grant RGPIN1345 (PI: R.V. Patel), in part by the NSERC Collaborative Research and Training Experience (CREATE) program under Grant 371322-2009 (PI: R.V. Patel) in Computer-Assisted Medical Interventions, and in part by the Canada Research Chairs Program (R.V. Patel). (Corresponding author: Mahya Shahbazi.) M. Shahbazi and S. F. Atashzar are with the Department of Electrical and Computer Engineering, Western University, London ON N6A 3K7, Canada, and also with Canadian Surgical Technologies and Advanced Robotics (CSTAR), London ON N6G 2V4, Canada (e-mail:, [email protected]; satashza@ uwo.ca).
Publisher Copyright:
© 2004-2012 IEEE.
PY - 2018/12
Y1 - 2018/12
N2 - This paper presents a novel multimodal training platform integrated with hand-over-hand (HOH) haptic guidance for dual-console surgical robotic systems such as the da Vinci Si system. The expert-in-The-loop (EIL) framework incorporates a fuzzy interface system in order to provide a trainee with adaptive authority over the procedure as well as hand-over-hand haptic guidance adjusted in real time based on the proficiency level of the trainee. The EIL expertise-oriented framework enables performance of a surgical procedure by an expert surgeon on a patient, while simultaneously providing a trainee at any stage of the motor-skills development with multimodal training without jeopardizing patient safety. Closed-loop stability of the system is investigated using the circle criterion and it is shown that the proposed architecture is unconditionally stable. Experimental evaluations are presented in support of the proposed platform through the implementation of a dual-console surgical setup consisting of the classic da Vinci surgical system (Intuitive Surgical, Inc., Sunnyvale, CA, USA) and the dV-Trainer master console (Mimic Technology, Inc., Seattle, WA, USA). To the best of our knowledge, the implemented setup is the first research platform for dual-console studies involving the classic da Vinci surgical system.
AB - This paper presents a novel multimodal training platform integrated with hand-over-hand (HOH) haptic guidance for dual-console surgical robotic systems such as the da Vinci Si system. The expert-in-The-loop (EIL) framework incorporates a fuzzy interface system in order to provide a trainee with adaptive authority over the procedure as well as hand-over-hand haptic guidance adjusted in real time based on the proficiency level of the trainee. The EIL expertise-oriented framework enables performance of a surgical procedure by an expert surgeon on a patient, while simultaneously providing a trainee at any stage of the motor-skills development with multimodal training without jeopardizing patient safety. Closed-loop stability of the system is investigated using the circle criterion and it is shown that the proposed architecture is unconditionally stable. Experimental evaluations are presented in support of the proposed platform through the implementation of a dual-console surgical setup consisting of the classic da Vinci surgical system (Intuitive Surgical, Inc., Sunnyvale, CA, USA) and the dV-Trainer master console (Mimic Technology, Inc., Seattle, WA, USA). To the best of our knowledge, the implemented setup is the first research platform for dual-console studies involving the classic da Vinci surgical system.
KW - Dual-console robotics-Assisted minimally invasive surgery (RAMIS) system
KW - da Vinci research kit (dVRK)
KW - fuzzy interface system (FIS)
KW - multimodal sensorimotor integration
KW - robotics-Assisted surgical training
KW - teleoperation.
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U2 - 10.1109/TRO.2018.2861916
DO - 10.1109/TRO.2018.2861916
M3 - Article
AN - SCOPUS:85052628155
SN - 1552-3098
VL - 34
SP - 1549
EP - 1564
JO - IEEE Transactions on Robotics
JF - IEEE Transactions on Robotics
IS - 6
M1 - 8447434
ER -