Knee arthroscopy is the most common orthopedic procedure in the world with more than four million cases per year and costs the global healthcare system for over USD $15 billion. It is a type of Minimally Invasive Surgery (MIS). After 40 years since its clinical acceptance, knee arthroscopy has become a well-established diagnostic and therapeutic procedure in which a camera, i.e. arthroscope, and a surgical tool are introduced in the knee joint through small incisions in the skin. Despite several clinical advantages, arthroscopic technique faces long-withstanding challenges: physically-demanding ergonomics during patient manipulation, loss of depth perception and limited field of view, and unintuitive hand-eye coordination between scope and surgical instruments. These challenges make knee arthroscopy a complex procedure with a registrar baseline competency of 170 cases and an unclear assessment on unintended injuries on patients.
This project aims at developing a robotic surgical assistant for knee arthroscopy, composed of a robotic arm with an attached camera-arthroscope bundle for intra-articular navigation, and a robotic knee manipulator. The system will be capable of a) generating intra-articular 3D reconstructed models of the knee joint from arthroscopic images, b) following the movements of the surgeon’s tool with the arthroscopic camera (via visual servoing) and c) manipulating the knee to position it in the appropriate configuration, based on visual feedback.
- Professor Jonathan Roberts
- Professor Ross Crawford
- Associate Professor Thierry Peynot
- Dr Anjali Tumkur Jaiprakash
- Distinguished Professor Peter Corke
Other Team Members
- Andres Marmol Velez
- Mario Strydom