Adaptive Surgical Robotic Training Using Real-Time Stylistic Behavior Feedback Through Haptic Cues
Surgical skill directly affects surgical procedure outcomes; thus, effective training is needed to ensure satisfactory results. Many objective assessment metrics have been developed that provide the trainee with descriptive feedback about their performance however, these metrics often lack feedback...
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Published in | IEEE transactions on medical robotics and bionics Vol. 3; no. 4; pp. 959 - 969 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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United States
IEEE
01.11.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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Abstract | Surgical skill directly affects surgical procedure outcomes; thus, effective training is needed to ensure satisfactory results. Many objective assessment metrics have been developed that provide the trainee with descriptive feedback about their performance however, these metrics often lack feedback on how to improve performance. The most effective training method is one that is intuitive, easy to understand, personalized, and provided in a timely manner. We propose a framework to enable user-adaptive training using near real-time detection of performance, based on intuitive styles of surgical movements, and design a haptic feedback framework to assist with correcting styles of movement. We evaluate the ability of three types of force feedback (spring, damping, and spring plus damping feedback), computed based on prior user positions to improve different stylistic behaviors of the user during kinematically constrained reaching movement tasks. The results indicate that five out of six styles studied here were improved using at least one of the three types of force feedback. Task performance metrics were compared in the presence of the three types of feedback. Task time was statistically significantly lower when applying spring feedback, compared to the other two types of feedback. Path straightness and targeting error were statistically significantly improved when using spring-damping feedback compared to the other two types of feedback. This study presents a groundwork for adaptive training in robotic surgery based on near real-time human-centric models of surgical behavior. |
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AbstractList | Surgical skill directly affects surgical procedure outcomes; thus, effective training is needed to ensure satisfactory results. Many objective assessment metrics have been developed that provide the trainee with descriptive feedback about their performance however, these metrics often lack feedback on how to improve performance. The most effective training method is one that is intuitive, easy to understand, personalized, and provided in a timely manner. We propose a framework to enable user-adaptive training using near real-time detection of performance, based on intuitive styles of surgical movements, and design a haptic feedback framework to assist with correcting styles of movement. We evaluate the ability of three types of force feedback (spring, damping, and spring plus damping feedback), computed based on prior user positions to improve different stylistic behaviors of the user during kinematically constrained reaching movement tasks. The results indicate that five out of six styles studied here were improved using at least one of the three types of force feedback. Task performance metrics were compared in the presence of the three types of feedback. Task time was statistically significantly lower when applying spring feedback, compared to the other two types of feedback. Path straightness and targeting error were statistically significantly improved when using spring-damping feedback compared to the other two types of feedback. This study presents a groundwork for adaptive training in robotic surgery based on near real-time human-centric models of surgical behavior. Surgical skill directly affects surgical procedure outcomes; thus, effective training is needed to ensure satisfactory results. Many objective assessment metrics have been developed that provide the trainee with descriptive feedback about their performance however, often lack feedback on how to improve performance. The most effective training method is one that is intuitive, easy to understand, personalized to the user,and provided in a timely manner. We propose a framework to enable user-adaptive training using near real-time detection of performance, based on intuitive styles of surgical movements, and design a haptic feedback framework to assist with correcting styles of movement. We evaluate the ability of three types of force feedback (spring, damping, and spring plus damping feedback), computed based on prior user positions, to improve different stylistic behaviors of the user during kinematically constrained reaching movement tasks. The results indicate that five out of six styles studied here were improved using at least one of the three types of force feedback. Task performance metrics were compared in the presence of the three types of feedback. Task time was statistically significantly lower when applying spring feedback, compared to the other two types of feedback. Path straightness and targeting error were statistically significantly improved when using spring-damping feedback compared to the other two types of feedback. This study presents a groundwork for adaptive training in robotic surgery based on near real-time human-centric models of surgical behavior. |
Author | Fey, Ann Majewicz Ershad, Marzieh Rege, Robert |
Author_xml | – sequence: 1 givenname: Marzieh surname: Ershad fullname: Ershad, Marzieh email: marzieh.ershadlangroodi@utdallas.edu organization: Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX, USA – sequence: 2 givenname: Robert surname: Rege fullname: Rege, Robert organization: Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA – sequence: 3 givenname: Ann Majewicz surname: Fey fullname: Fey, Ann Majewicz organization: Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA |
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Cites_doi | 10.1001/jamasurg.2015.2405 10.1038/s41598-019-40821-1 10.1097/01.sla.0000151982.85062.80 10.1002/lary.23369 10.1177/001872086901100602 10.1109/EMBC.2018.8512728 10.1007/s11548-018-1738-2 10.1007/978-3-319-46720-7_59 10.1109/TOH.2012.33 10.1109/MCG.2004.1274062 10.1109/HAPTICS.2018.8357183 10.2196/jmir.9330 10.1109/TOH.2009.4 10.1109/WHC.2013.6548441 10.1097/00000658-199705000-00002 10.1109/TOH.2016.2516984 10.3109/10929080801957712 10.1109/TOH.2011.31 10.1109/RBME.2016.2538080 10.1109/ROBOT.2009.5152705 10.1016/j.ajog.2016.06.033 10.1109/URAI.2017.7992664 10.21037/atm.2016.12.24 10.1109/HAPTICS.2008.4479929 10.1007/s11548-019-01920-6 10.1007/s00464-015-4602-2 10.1016/j.cosrev.2016.09.001 10.1109/HAPTIC.2010.5444635 10.1109/HAPTICS.2008.4479944 10.1109/HAVE.2006.283801 |
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SubjectTerms | adaptive and intelligent educational systems Damping Feedback Force feedback Haptic interfaces Medical robotics Performance enhancement Performance measurement Real time Robotic surgery Surgery Surgical robotics Training |
Title | Adaptive Surgical Robotic Training Using Real-Time Stylistic Behavior Feedback Through Haptic Cues |
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