Surgeon Gesture Recognition Sensor System for a Laparoscopic Suture Manoeuvre

Laparoscopic surgery, a type of minimally invasive abdominal surgery, offers numerous benefits, including reduced mortality, shorter hospital stays, and lower costs. However, it also presents challenges such as a steep learning curve, loss of 3D vision and ergonomic issues. To address these challenges, robotic systems have been introduced to improve precision and control. This paper proposes a robust kinematic data acquisition system for capturing surgeon movements during laparoscopic procedures using two infrared trackers and a real-time Kalman filter, which reduces positioning errors and estimates tool poses when tracking is lost. Using this system, a dataset was created from the kinematic data of two laparoscopic instruments during a surgical suture manoeuvre. This dataset was used to train a gesture recognition system capable of identifying surgeon actions in the manoeuvre, contributing to the advancement of human-robot collaboration in laparoscopic surgery.