Date of Award
School of Engineering
Laparoscopic Surgery, also known as Minimally Invasive Surgery, is a surgical technique where surgeons perform surgery through small incisions in the patient’s abdomen using a camera to monitor the movements of the instruments inside the patient. In order for the surgery to be performed, the surgeon must possess a unique set of skills obtained through training using a variety of techniques. Simulators are the preferred method of training for laparoscopic surgery since they provide medical residents with real world scenarios as well as a tremendous amount of feedback on what he/she did wrong or right. However, due to the high cost associated with laparoscopic simulators, laparoscopic box trainers are more commonly used, but fail to provide trainees with the necessary feedback to create an effective training experience. The Electronic Laparoscopic Trainer (ELT) is a low cost device that provides users with a virtual reality like experience using a laparoscopic box trainer, but fails to accurately track the motion of the laparoscopic instruments. This paper describes and validates an optical tracking system to monitor the laparoscopic instruments inside of the laparoscopic box trainer that can be added to the ELT to increase its effectiveness during training. The algorithm performs a series of steps that are taken a frame at a time to obtain the 3D real world tracking point of the laparoscopic instrument, which are used to calculate quantitative values for various aspects of the user’s performance that represent how effective, controlled, and safe the user’s movements were. Testing confirmed that the algorithm can accurately track the distance traveled and direction of up to two laparoscopic instruments in 3D real space and is capable of differentiating between users of varying skill levels by using performance metrics such as the amount of time each instrument is in the field of view and path length.
Rytlewski, William D., "Optical Tracking System to Monitor Laparoscopic Training" (2015). Masters Theses. 777.