Intention recognition for gaze controlled robotic minimally invasive laser ablation

Eye tracking technology has shown promising results for allowing hands-free control of robotically-mounted cameras and tools. However existing systems present only limited capabilities in allowing the full range of camera motions in a safe, intuitive manner. This paper introduces a framework for the recognition of surgeon intention, allowing activation and control of the camera through natural gaze behaviour. The system is resistant to noise such as blinking, while allowing the surgeon to look away safely at any time. Furthermore, this paper presents a novel approach to control the translation of the camera along its optical axis using a combination of eye tracking and stereo reconstruction. Combining eye tracking and stereo reconstruction allows the system to determine which point in 3D space the user is fixating, enabling a translation of the camera to achieve the optimal viewing distance. In addition, the eye tracking information is used to perform automatic laser targeting for laser ablation. The desired target point of the laser, mounted on a separate robotic arm, is determined with the eye tracking thus removing the need to manually adjust the laser's target point before starting each new ablation. The calibration methodology used to obtain millimetre precision for the laser targeting without the aid of visual servoing is described. Finally, a user study validating the system is presented, showing clear improvement with median task times under half of those of a manually controlled robotic system.

[1]  Adrian Park,et al.  Quantifying mental workloads of surgeons performing natural orifice transluminal endoscopic surgery (NOTES) procedures , 2011, Surgical Endoscopy.

[2]  J R Monson,et al.  Cause and prevention of electrosurgical injuries in laparoscopy. , 1994, Journal of the American College of Surgeons.

[3]  A. Rané,et al.  Initial experience with the EndoAssist camera-holding robot in laparoscopic urological surgery , 2007, Journal of robotic surgery.

[4]  Raquel Urtasun,et al.  Efficient Joint Segmentation, Occlusion Labeling, Stereo and Flow Estimation , 2014, ECCV.

[5]  Guang-Zhong Yang,et al.  Gaze contingent control for an articulated mechatronic laparoscope , 2010, 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[6]  Guang-Zhong Yang,et al.  Gaze contingent cartesian control of a robotic arm for laparoscopic surgery , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Guang-Zhong Yang,et al.  Gaze contingent articulated robot control for robot assisted minimally invasive surgery , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Abed Malti,et al.  Robust hand-eye calibration for computer aided medical endoscopy , 2010, 2010 IEEE International Conference on Robotics and Automation.

[9]  R. Bittner,et al.  The AESOP robot system in laparoscopic surgery: Increased risk or advantage for surgeon and patient? , 2004, Surgical Endoscopy And Other Interventional Techniques.

[10]  George P. Mylonas,et al.  Gaze-contingent control for minimally invasive robotic surgery , 2006, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.