JISAP: Joint Inference for Surgeon Attributes Prediction during Robot-Assisted Surgery

Tian Zhou, Jackie S. Cha, Glebys T. Gonzalez, Chandru P. Sundaram, Juan P. Wachs, Denny Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In Robot-Assisted Surgery, predicting surgeon attributes such as task workload, operation performance, and expertise levels is important in providing tailored assistance. This paper proposes Joint Inference for Surgeon Attributes Prediction (JISAP), a computational framework to jointly infer surgeon attributes (i.e., task workload, operation performance, and expertise level) from multimodal physiological signals (heart rate variability, wrist motion, electrodermal, electromyography, and electroencephalogram activity). JISAP was evaluated with a dataset of twelve surgeons operating on the da Vinci Skills Simulator. It was found that JISAP can simultaneously predict surgeon attributes with a percentage error of 11.05%. Additionally, joint inference was found to outperform isolated inference with a boost of 10%.

Original languageEnglish (US)
Title of host publication2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2246-2251
Number of pages6
ISBN (Electronic)9781728140049
DOIs
StatePublished - Nov 2019
Externally publishedYes
Event2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019 - Macau, China
Duration: Nov 3 2019Nov 8 2019

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
CountryChina
CityMacau
Period11/3/1911/8/19

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Fingerprint Dive into the research topics of 'JISAP: Joint Inference for Surgeon Attributes Prediction during Robot-Assisted Surgery'. Together they form a unique fingerprint.

  • Cite this

    Zhou, T., Cha, J. S., Gonzalez, G. T., Sundaram, C. P., Wachs, J. P., & Yu, D. (2019). JISAP: Joint Inference for Surgeon Attributes Prediction during Robot-Assisted Surgery. In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019 (pp. 2246-2251). [8968097] (IEEE International Conference on Intelligent Robots and Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS40897.2019.8968097