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Sensor-based indicators of performance changes between sessions during robotic surgery training.

Chuhao Wu1, Jackie Cha1, Jay Sulek2

  • 1Purdue University, West Lafayette, IN, United States.

Applied Ergonomics
|September 22, 2020
PubMed
Summary
This summary is machine-generated.

New metrics measuring surgeon engagement and eye movements can predict robotic surgery training success. These findings enhance current assessment tools for surgical education and skills development.

Keywords:
ElectroencephalogramEye trackingPerformanceRobotic surgerySimulated training

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Area of Science:

  • Medical Education
  • Surgical Training
  • Robotic Surgery

Background:

  • Current assessment tools for robotic surgery training are limited.
  • Effective surgeon training is crucial for safe and efficient robotic procedures.

Purpose of the Study:

  • To measure changes in trainees' cognitive and behavioral states during robotic surgery training.
  • To assess the correlation between these states and performance improvements.

Main Methods:

  • Seven surgical trainees performed 12 robotic skills exercises.
  • Electroencephalogram (EEG) activity and eye movements were monitored.
  • Engagement index, pupil diameter, and gaze entropy were calculated alongside performance scores.

Main Results:

  • Changes in performance correlated with engagement index (r=-.25) and gaze entropy (r=-.37).
  • Cognitive and behavioral metrics predicted training outcomes with 72.5% accuracy.
  • EEG and eye-tracking metrics offer insights into surgical skill acquisition.

Conclusions:

  • Cognitive and behavioral metrics correlate with performance changes in robotic surgery training.
  • These measures can supplement existing feedback tools for educators and trainees.
  • Objective assessment of cognitive and behavioral states can improve surgical skills evaluation.