High-fidelity, low-cost, automated method to assess laparoscopic skills objectively

Area of Science:

• Surgical Education
• Biomedical Engineering
• Medical Technology Assessment

Background:

• Objective assessment of surgical technical skill is crucial for training.
• Existing methods may be subjective or require specialized equipment.
• Developing accessible tools for skill evaluation is a key challenge.

Purpose of the Study:

• To determine if a low-cost, motion analysis system can objectively quantify surgical technical skill.
• To assess the system's ability to differentiate between surgical trainee skill levels.

Main Methods:

• Utilized an "off-the-shelf" digital video system to record surgical trainees performing a peg transfer exercise.
• Applied a custom computer vision algorithm to analyze pixel data and measure hand/instrument movement smoothness.
• Trainees were categorized into beginner (PGY-1), intermediate (PGY-3), and advanced (PGY-5/fellow) levels.

Main Results:

• Significant differences in movement smoothness scores were observed across trainee levels.
• Beginner trainees exhibited the poorest performance, while advanced trainees achieved the highest scores.
• Advanced trainees outperformed intermediate trainees, and both outperformed beginner trainees (p < 0.04).

Conclusions:

• Computer vision-based motion analysis provides a valid and objective measure of surgical technical expertise.
• The system is simple, low-cost, and uses readily available technology.
• This approach can reduce reliance on subjective expert assessments in surgical training evaluation.