Automated Performance Assessment of Trainees in Trauma Surgery Education
The project team of Synbone and the pd|z has reached a first milestone in which it demonstrates that the performance assessment of surgical trainees can be automated.
In the Innosuisse project initiated last October, SYNBONE and pd|z have collaborated to develop an advancement in trauma surgery education. This effort aims to create technology to improve surgical instruction efficacy, with initial outcomes now being presented.
The latest progress showcases the ability to automatically assess the performance of trauma procedures and generate crucial performance metrics. The technology can accurately identify deterministic interactions between surgical instruments and bones, allowing precise detection of procedural activities. In instances where object relationships within surgical scenarios are ambiguous, AI algorithms recognize motion patterns to monitor activities. Based on the detected activities, the trainee performance of the individual tasks can be determined.
The analysis is performed on a digitalin twin of the real scene. This way, relevant metrics and feedback can be provided to the trainees. To further enable an immersive training environment, simulated X-ray imaging is employed to train real-life navigational skills, facilitating advanced training on complex surgical procedures.
In the coming months, the technology will be further advanced to understand the behavior and measure the performance of trainees in more complex procedures.
Please contact Tobias Stauffer for further information
