Artificial intelligence based real-time video ergonomic assessment and training improves resident ergonomics

Area of Science:

• Surgical training and technology
• Human factors and ergonomics
• Artificial intelligence in medicine

Background:

• Surgical professions involve prolonged hours and strenuous activity, leading to significant ergonomic challenges.
• Assessing and mitigating these ergonomic risks is crucial for resident well-being and performance.

Purpose of the Study:

• To pilot a sensorless artificial intelligence (AI)-assisted ergonomics analysis application for surgical residents.
• To determine the feasibility and impact of AI-driven ergonomic feedback in a simulated surgical environment.

Main Methods:

• Thirteen surgical residents performed simulated laparoscopic tasks.
• Ergonomic metrics, including joint angles, were captured using a sensorless AI app before and after an ergonomics curriculum review.
• Surveys and focus groups were employed to gather qualitative data on resident awareness and training needs.

Main Results:

• Residents demonstrated improved ergonomic scores, specifically in neck and right shoulder angles, following the intervention.
• The AI-assisted feedback increased residents' awareness of ergonomic principles.
• All participating trainees expressed a desire for further ergonomics training.

Conclusions:

• Sensorless AI software offers a feasible method for providing immediate ergonomic feedback to surgical trainees.
• This technology has the potential to enhance surgical ergonomics and improve resident training.
• Further research is warranted to explore the broader applications of sensorless AI in surgical ergonomics.