Haptics-enabled surgical training system with guidance using deep learning

Ehren Biglari, Marie Feng, John Quarles, Edward Sako, John Calhoon, Ronald Rodriguez, Yusheng Feng

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

Abstract

In this paper, we present a haptics-enabled surgical training system integrated with deep learning for characterization of particular procedures of experienced surgeons to guide medical residents-in-training with quantifiable patterns. The prototype of virtual reality surgical system is built for open-heart surgery with specific steps and biopsy operation. Two abstract surgical scenarios are designed to emulate incision and biopsy surgical procedures. Using deep learning algorithm (autoencoder), the two surgical procedures were trained and characterized. Results show that a vector with 30 real-valued components can quantify both surgical patterns. These values can be used to compare how a resident- in-training performs differently as opposed to an experienced surgeon so that quantifiable corrective training guidance can be provided.

Original languageEnglish (US)
Title of host publicationUniversal Access in Human-Computer Interaction
Subtitle of host publicationAccess to Learning, Health and Well-Being - 9th International Conference, UAHCI 2015 Held as Part of HCI International 2015, Proceedings
EditorsConstantine Stephanidis, Margherita Antona, Constantine Stephanidis
PublisherSpringer Verlag
Pages267-278
Number of pages12
ISBN (Print)9783319206837
DOIs
StatePublished - 2015
Event9th International Conference on Universal Access in Human-Computer Interaction, UAHCI 2015 Held as Part of 17th International Conference on Human-Computer Interaction, HCI International 2015 - Los Angeles, United States
Duration: Aug 2 2015Aug 7 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9177
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Universal Access in Human-Computer Interaction, UAHCI 2015 Held as Part of 17th International Conference on Human-Computer Interaction, HCI International 2015
Country/TerritoryUnited States
CityLos Angeles
Period8/2/158/7/15

Keywords

  • Autoencoder
  • Deep learning algorithm
  • Haptic device
  • Machine learning
  • Motion tracking and quantification
  • Virtual surgical training system

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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