MinIAttention: Attention Management in Minimal Invasive Surgery

  • Anzengruber-Tánase, Bernhard (Researcher)
  • Gunawardena, Nishan (Researcher)
  • Hochedlinger, Nina (Researcher)
  • Pernek, Igor (Researcher)
  • Schobesberger, Martin (Researcher)
  • Weigl, Klemens (Researcher)
  • Ferscha, Alois (PI)

Project: Funded researchFFG - Austrian Research Promotion Agency

Project Details

Description

Laparoscopic surgical suboptimal outcomes in patient safety measures are correlated with (i) cognitive load / level of attention of the operating surgeon, (ii) the frequency and degree of disruptions to the surgical workflow, and (iii) the misalignment of visual and motor axes in laparoscopic equipment / setting (eye-hand coordination). This project will create the foundational, design and operational principles of future, surgeon-friendly minimal invasive surgery operating room information technologies (MIS-IT), which –given the ever growing complexity in surgical workflows, as well as instrument and equipment settings– will have to build on human attention as a scarce resource. On the formal model’s and methods’ side, MinIAttention will (i) identify types of human attention, as well as (ii) cognitive and physiological mechanisms revealing its relation to perception, memory, decision making, and learning. (iii) characterize aspects of attention of surgeons during MIS operations, by (iv) focusing on established theories of individual attention and respective attention models.
StatusFinished
Effective start/end date01.02.201631.07.2019

Collaborative partners

  • Johannes Kepler University Linz (lead)
  • KARL STORZ GmbH & Co. KG (Project partner)
  • University of Sussex (Project partner)
  • Albert-Ludwigs-Universität Freiburg (Project partner)
  • Kepler Universitätsklinikum GmbH (Project partner)

Fields of science

  • 102019 Machine learning
  • 102009 Computer simulation
  • 102 Computer Sciences
  • 102022 Software development
  • 102021 Pervasive computing
  • 102013 Human-computer interaction
  • 102025 Distributed systems
  • 102020 Medical informatics
  • 211902 Assistive technologies
  • 202017 Embedded systems
  • 211912 Product design

JKU Focus areas

  • Digital Transformation