Motion and Viewing Analysis of Surgeons During Minimally Invasive Gynecological Interventions

During minimally invasive surgery (MIS), surgeons manipulate sharp and stiff instruments in the vicinity of fragile tissue, blood vessels, and critical nerves, where poor depth perception can have dramatic consequences. Since typically, 2-dimensional visualization is offered, to correctly infer the 3rd dimension, surgeons rely on their anatomical knowledge and experience. During unforeseen events, correct depth information can make the difference between success and failure. This explains the steep and long learning curve for surgeons. The absence of proper depth information slows down execution and leads to an unnecessary large mental load.

A recent document from the European Association of Endoscopic Surgery showed that 3D shortens operative time and learning curves and reduces complications. 'What the best way is to visualize 3D content' remains an open question. Near-to-eye displays provide small screens in front of each eye, while stereoscopic displays use glasses to project the 3D content to the eyes. The Da Vinci surgical system uses two individual optical panels. These systems are bulky, or restrict head movement, thus users have remarks on the ergonomics. The glasses for stereoscopic displays obscure the view, reduce brightness, and alter the color. Correct color is crucial to recognize tissue types and details or parts in shaded areas. Stereoscopic 3D displays lead to headache and eye-fatigue, called visually induced motion sickness in 11-22% of surgeons after several surgeries.

Autostereoscopic Visualization (ASV) is appealing for medical applications. Besides the improvement of depth perception, it allows 'glasses-free' operation. One of the key components of such displays is eye-tracking, that locates the eyes of the user to be able to render the 3D image to that viewpoint. ASV is a single-viewer application, which can be challenging in an operating room, with multiple people present. Therefore, a rigorous investigation is needed to maximize the performance of the algorithm and ensure the quality of service needed for medical use. It is crucial to collect data from real scenarios by recording the operation, the pose, motion of surgeons and the entire staff. These recordings will deliver solid understanding of the circumstances and rate of occurrences where eye-tracking and 3D visualization fails (or could fail). Furthermore, patterns can be recognized that could help to develop a robust eye-tracking algorithm and safety features for ASV.