An Eye-Gaze-Controlled Needle Deployment Robot: Design, Modeling, and Experimental Evaluation

Robot-assisted minimally invasive needle percutaneous intervention promotes the biopsy operation accuracy and speed as well. Yet, Leksell-based needle displacement platform is bulky and unsuitable for certain applications such as MRI-guided surgery. Also, controllers such as joysticks or keyboards conventionally used by surgeons to command robotic systems require extra preoperative training and intraoperative sterilization. As a step forward to improve the current robot-assisted biopsy system, a compact four degree of freedom (DoF) needle deployment robot is designed, and a deep learning-based eye gaze control method, using only one camera, is derived to facilitate the interaction efficiency and efficacy. A first-generation prototype is constructed to evaluate the performance of the proposed eye-gaze-controlled needle deployment method. Experimental results demonstrate that the proposed system can achieve satisfactory positioning precision, with a maximum average error of
$\boldsymbol {0.3883}^{\circ }$
, and it is capable of tracking the eye fixation angle in real-time.