Evaluation of robotic surgery skills using dynamic time warping

Area of Science:

• Robotics in Surgery
• Medical Engineering
• Surgical Skill Assessment

Background:

• Robot-assisted minimally invasive surgery (RMIS) adoption necessitates objective surgical skill evaluation.
• Current kinematic analysis methods for surgical skills are limited by metrics and scoring.
• There is a growing demand for efficient and objective methods to assess surgical proficiency.

Purpose of the Study:

• To propose a novel algorithm for efficient and objective surgical skill assessment.
• To enhance the evaluation of surgical skills in robot-assisted procedures.
• To address limitations in existing kinematic analysis methods for surgical training.

Main Methods:

• Developed an algorithm utilizing instrument tip trajectories and dynamic time warping (DTW).
• Created an optimal trajectory template based on 'Therbligs' theory.
• Implemented a sliding time window for real-time feedback and incorporated an evaluation indicator for crucial motion features.

Main Results:

• The algorithm demonstrated significant differences between expert and novice surgical performance (p < 0.05).
• Evaluated 60 instrument tip trajectories from experts and novices performing peg transfer tasks.
• Successfully distinguished trajectories with operational mistakes from correct ones.

Conclusions:

• The proposed method effectively distinguishes and evaluates surgical performance using kinematic data.
• The algorithm shows potential for further development in surgical skill assessment.
• The real-time feedback capability suggests its utility as an intraoperative monitoring system.