Soft robotic devices have desirable traits for applications in minimally invasive surgery (MIS), but many interdisciplinary challenges remain unsolved. To understand current technologies, we carried out a keyword search using the Web of Science and Scopus databases, applied inclusion and exclusion criteria, and compared several characteristics of the soft robotic devices for MIS in the resulting articles. There was low diversity in the device designs and a wide-ranging level of detail regarding their capabilities. We propose a standardized comparison methodology to characterize soft robotics for various MIS applications, which will aid designers producing the next generation of devices.

Overall, eye-tracking methodology has contributed significantly to the training, assessment, and feedback practices used in the clinical setting. The technology provides reliable quantitative data, which can be interpreted to give an indication of clinical skill, provide training solutions and aid in feedback and reflection. This review provides a detailed summary of evidence relating to eye-tracking methodology and its uses as a training method, changes in visual gaze behavior during the learning curve, eye-tracking methodology for proficiency assessment and its uses as a feedback tool.

Abstract. In robotically assisted laparoscopic surgery, soft-tissue motion tracking and structure recovery are important for intraoperative surgical guidance, motion compensation and delivering active constraints. In this paper, we present a novel method for feature based motion tracking of deformable soft-tissue surfaces in totally endoscopic coronary artery bypass graft (TECAB) surgery. We combine two feature detectors to recover distinct regions on the epicardial surface for which the sparse 3D surface geometry may be computed using a pre-calibrated stereo laparoscope. The movement of the 3D points is then tracked in the stereo images with stereo-temporal constrains by using an iterative registration algorithm. The practical value of the technique is demonstrated on both a deformable phantom model with tomographically derived surface geometry and in vivo robotic assisted minimally invasive surgery (MIS) image sequences.

We have successfully demonstrated the effectiveness of a novel framework to enable a supervisor eye-gaze to be projected onto a trainee's laparoscopic screen. Furthermore, we have shown that utilizing eye-tracking technology to provide visual instruction improves completion times and reduces errors in a simulated environment. Although this technology requires significant development, the potential applications are wide-ranging.