Single-incision laparoscopic surgery (SILS) is on the path of becoming a standard procedure in minimally invasive surgery due to the outstanding results obtained both during and after the medical act, these being defined by the reduced hospitalization time, the reduced recovery time, and the reduced visibility of the incision. The paper presents the modeling and simulation of a new parallel robot concept with 6 Degrees of Freedom (DOF), called PARA-SILSROB used for the single incision laparoscopic surgery. The paper focuses on the inverse kinematics, the preliminary design, and the robot control system architecture of PARA-SILSROB. A CAD motion simulation validates the mathematical model using Siemens NX.

The problem: Single-incision surgery is a complex procedure in which any additional information automatically collected from the operating field can be of significance. While the use of robotic devices has greatly improved surgical outcomes, there are still many unresolved issues. One of the major surgical complications, with higher occurrence in cancer patients, is intraoperative hemorrhages, which if detected early, can be more efficiently controlled. Aim: This paper proposes a hazard detection system which incorporates the advantages of both Artificial Intelligence (AI) and Augmented Reality (AR) agents, capable of identifying, in real-time, intraoperative bleedings, which are subsequently displayed on a Hololens 2 device. Methods: The authors explored the different techniques for real-time processing and determined, based on a critical analysis, that YOLOv5 is one of the most promising solutions. An innovative, real-time, bleeding detection system, developed using the YOLOv5 algorithm and the Hololens 2 device, was evaluated on different surgical procedures and tested in multiple configurations to obtain the optimal prediction time and accuracy. Results: The detection system was able to identify the bleeding occurrence in multiple surgical procedures with a high rate of accuracy. Once detected, the area of interest was marked with a bounding box and displayed on the Hololens 2 device. During the tests, the system was able to differentiate between bleeding occurrence and intraoperative irrigation; thus, reducing the risk of false-negative and false-positive results. Conclusion: The current level of AI and AR technologies enables the development of real-time hazard detection systems as efficient assistance tools for surgeons, especially in high-risk interventions.

Augmented Reality (AR) became a very useful tool for various domains, with multiple applications in different medical fields, where this technology is integrated in medical training, image-based diagnosis, simulation of medical tasks, or in guiding systems for surgical procedures. The introduction of AR technology in robotic assisted surgery is relatively new and challenging considering the required precision for this type of medical task. The objective of this study is to develop an AR simulator for robotic assisted Single Incision Laparoscopic Surgery (SILS) where the robot performing the procedure is embedded in a virtual environment, providing both an interactive training and a simulation environment. The architecture and particularities of the proposed robot for SILS are analyzed for a better understanding of the structure, to obtain the validation of the kinematic model. The final result is represented in the form of an application which can be operated with Hololens 2 device.

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