Learning kinematic constraints in laparoscopic surgery

Felix C. Huang*, Ferdinando A. Mussa-Ivaldi, Carla M. Pugh, James L. Patton

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

To better understand how kinematic variables impact learning in surgical training, we devised an interactive environment for simulated laparoscopic maneuvers, using either 1) mechanical constraints typical of a surgical box-trainer” or 2) virtual constraints in which free hand movements control virtual tool motion. During training, the virtual tool responded to the absolute position in space (Position-Based) or the orientation (Orientation-Based) of a hand-held sensor. Volunteers were further assigned to different sequences of target distances (Near-Far-Near or Far-Near-Far). Training with the Orientation-Based constraint enabled much lower path error and shorter movement times during training, which suggests that tool motion that simply mirrors joint motion is easier to learn. When evaluated in physically constrained (physical box-trainer) conditions, each group exhibited improved performance from training. However, Position-Based training enabled greater reductions in movement error relative to Orientation-Based (mean difference: 14.0 percent; CI: 0.7, 28.6). Furthermore, the Near-Far-Near schedule allowed a greater decrease in task time relative to the Far-Near-Far sequence (mean -13.5 percent, CI: -19.5, -7.5). Training that focused on shallow tool insertion (near targets) might promote more efficient movement strategies by emphasizing the curvature of tool motion. In addition, our findings suggest that an understanding of absolute tool position is critical to coping with mechanical interactions between the tool and trocar.

Original languageEnglish (US)
Article number6025353
Pages (from-to)356-364
Number of pages9
JournalIEEE Transactions on Haptics
Volume5
Issue number4
DOIs
StatePublished - 2012

Keywords

  • Laparoscopic surgery
  • kinematic constraints
  • motor learning

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Science Applications

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