Application of a Perception Neuron^® System in Simulation-Based Surgical Training

Area of Science:

• Surgical Education
• Motion Analysis
• Medical Simulation

Background:

• Simulation enhances surgical training, but optimizing trainee body motions remains a challenge.
• Effective body motion adoption is crucial for surgical skill development.
• Few systems quantify the relationship between body motion and simulation performance.

Purpose of the Study:

• To investigate the utility of the Perception Neuron system for evaluating surgical trainee body motions.
• To assess the correlation between motion capture data and traditional simulation scores.
• To determine if motion economy relates to overall proficiency in surgical simulation.

Main Methods:

• Ten medical students performed simulated thyroidectomy tasks using the da Vinci Skills Simulator and a thyroidectomy training model.
• Participants wore a Perception Neuron system to capture body motion data.
• Motion capture (MC) scores, including task completion time and economy-of-motion, were calculated and correlated with simulation scores.

Main Results:

• All scores (training model, dVSS, MC) significantly improved from cycle 1 to cycle 2.
• The three scoring systems demonstrated significant positive correlations.
• High-proficiency trials showed significantly better right-hand economy-of-motion compared to low-proficiency trials.

Conclusions:

• The Perception Neuron system is applicable for analyzing surgical trainee movements in simulation-based education.
• Motion analysis metrics derived from the Perception Neuron system correlate with established simulation scoring.
• Optimizing body motion economy is linked to improved performance in surgical simulation.