abstract

Joint Surgeon Attributes Estimation in Robot-Assisted Surgery

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Denny YuAuthors Info & Claims

HRI '18: Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction

Pages 285 - 286

https://doi.org/10.1145/3173386.3176981

Published: 01 March 2018 Publication History

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Abstract

This paper proposes a computational framework to estimate surgeon attributes during Robot-Assisted Surgery (RAS). The three investigated attributes are workload, performance, and expertise levels. The framework leverages multimodal sensing and joint estimation and was evaluated with twelve surgeons operating on the da Vinci Skills Simulator. The multimodal signals include heart rate variability, wrist motion, electrodermal, electromyography, and electroencephalogram activity. The proposed framework reached an average estimation error of 11.05%, and jointly inferring surgeon attributes reduced estimation errors by 10.02%.

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Cited By

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D'Ambrosia CAronoff-Spencer EHuang EGoldhaber NChristensen HBroderick RAppelbaum L(2023)The neurophysiology of intraoperative error: An EEG study of trainee surgeons during robotic-assisted surgery simulationsFrontiers in Neuroergonomics10.3389/fnrgo.2022.10524113Online publication date: 9-Jan-2023
https://doi.org/10.3389/fnrgo.2022.1052411
Nagyné Elek RHaidegger T(2021)Non-Technical Skill Assessment and Mental Load Evaluation in Robot-Assisted Minimally Invasive SurgerySensors10.3390/s2108266621:8(2666)Online publication date: 10-Apr-2021
https://doi.org/10.3390/s21082666
Castillo-Segura PFernández-Panadero CAlario-Hoyos CMuñoz-Merino PDelgado Kloos C(2021)Objective and automated assessment of surgical technical skills with IoT systems: A systematic literature reviewArtificial Intelligence in Medicine10.1016/j.artmed.2020.102007112(102007)Online publication date: Feb-2021
https://doi.org/10.1016/j.artmed.2020.102007
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Index Terms

Joint Surgeon Attributes Estimation in Robot-Assisted Surgery
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. User models

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Published In

HRI '18: Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction

March 2018

431 pages

ISBN:9781450356152

DOI:10.1145/3173386

General Chairs:
Takayuki Kanda
ATR, Japan
,
Selma Ŝabanović
Indiana University Bloomington, USA
,
Program Chairs:
Guy Hoffman
Cornell University, USA
,
Adriana Tapus
ENSTA-ParisTech, France

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 01 March 2018

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Walther Embedding Program
Surgical Intuitive

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HRI '18

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SIGAI
SIGCHI
IEEE-RAS

HRI '18: ACM/IEEE International Conference on Human-Robot Interaction

March 5 - 8, 2018

IL, Chicago, USA

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HRI '18 Paper Acceptance Rate 49 of 206 submissions, 24%;

Overall Acceptance Rate 192 of 519 submissions, 37%

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D'Ambrosia CAronoff-Spencer EHuang EGoldhaber NChristensen HBroderick RAppelbaum L(2023)The neurophysiology of intraoperative error: An EEG study of trainee surgeons during robotic-assisted surgery simulationsFrontiers in Neuroergonomics10.3389/fnrgo.2022.10524113Online publication date: 9-Jan-2023
https://doi.org/10.3389/fnrgo.2022.1052411
Nagyné Elek RHaidegger T(2021)Non-Technical Skill Assessment and Mental Load Evaluation in Robot-Assisted Minimally Invasive SurgerySensors10.3390/s2108266621:8(2666)Online publication date: 10-Apr-2021
https://doi.org/10.3390/s21082666
Castillo-Segura PFernández-Panadero CAlario-Hoyos CMuñoz-Merino PDelgado Kloos C(2021)Objective and automated assessment of surgical technical skills with IoT systems: A systematic literature reviewArtificial Intelligence in Medicine10.1016/j.artmed.2020.102007112(102007)Online publication date: Feb-2021
https://doi.org/10.1016/j.artmed.2020.102007
Brickler DTeather RDuchowski ABabu S(2020)A Fitts’ Law Evaluation of Visuo-haptic Fidelity and Sensory Mismatch on User Performance in a Near-field Disc Transfer Task in Virtual RealityACM Transactions on Applied Perception10.1145/341998617:4(1-20)Online publication date: 14-Dec-2020
https://dl.acm.org/doi/10.1145/3419986

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Recommendations

Impacts of Telemanipulation in Robotic Assisted Surgery

Multimodal Physiological Signals for Workload Prediction in Robot-assisted Surgery

Identifying barriers in telesurgery by studying current team practices in robot-assisted surgery

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