Endoscopic procedures have transformed minimally invasive surgery as they allow the examination and intervention on a patient’s anatomy through natural orifices, without the need for external incisions. However, the complexity of anatomical pathways and the limited dexterity of existing instruments, limit such procedures mainly to diagnosis and biopsies. This paper proposes a new robotic platform: the Intuitive imaging sensing navigated and kinematically enhanced () robot that aims to improve the field of endoscopic surgery. The proposed robotic platform includes a snake-like robotic endoscope equipped with a camera, a light-source and two robotic instruments, supported with a robotic arm for global positioning and for insertion of the and a master interface for master–slave teleoperation. The proposed robotic platform design focuses on ergonomics and intuitive control. The control workflow was first validated in simulation and then implemented on the robotic platform. The results are consistent with the simulation and show the clear clinical potential of the system. Limitations such as tendon backlash and elongation over time will be further investigated by means of combined hardware and software solutions. In conclusion, the proposed system contributes to the field of endoscopic surgical robots and could allow to perform more complex endoscopic surgical procedures while reducing patient trauma and recovery time.
While minimally invasive surgery offers great benefits in terms of reduced patient trauma, bleeding, as well as faster recovery time, it still presents surgeons with major ergonomic challenges. Laparoscopic surgery requires the surgeon to bimanually control surgical instruments during the operation. A dedicated assistant is thus required to manoeuvre the camera, which is often difficult to synchronise with the surgeon's movements. This article introduces a robotic system in which a rigid endoscope held by a robotic arm is controlled via the surgeon's eye movement, thus forgoing the need for a camera assistant. Gaze gestures detected via a series of eye movements are used to convey the surgeon's intention to initiate gaze contingent camera control. Hidden Markov Models (HMMs) are used for real-time gaze gesture recognition, allowing the robotic camera to pan, tilt, and zoom, whilst immune to aberrant or unintentional eye movements. A novel online calibration method for the gaze tracker is proposed, which overcomes calibration drift and simplifies its clinical application. This robotic system has been validated by comprehensive user trials and a detailed analysis performed on usability metrics to assess the performance of the system. The results demonstrate that the surgeons can perform their tasks quicker and more efficiently when compared to the use of a camera assistant or foot switches.
PurposeIn microsurgery, accurate recovery of the deformation of the surgical environment is important for mitigating the risk of inadvertent tissue damage and avoiding instrument maneuvers that may cause injury. The analysis of intraoperative microscopic data can allow the estimation of tissue deformation and provide to the surgeon useful feedback on the instrument forces exerted on the tissue. In practice, vision-based recovery of tissue deformation during tool–tissue interaction can be challenging due to tissue elasticity and unpredictable motion.MethodsThe aim of this work is to propose an approach for deformation recovery based on quasi-dense 3D stereo reconstruction. The proposed framework incorporates a new stereo correspondence method for estimating the underlying 3D structure. Probabilistic tracking and surface mapping are used to estimate 3D point correspondences across time and recover localized tissue deformations in the surgical site.ResultsWe demonstrate the application of this method to estimating forces exerted on tissue surfaces. A clinically relevant experimental setup was used to validate the proposed framework on phantom data. The quantitative and qualitative performance evaluation results show that the proposed 3D stereo reconstruction and deformation recovery methods achieve submillimeter accuracy. The force–displacement model also provides accurate estimates of the exerted forces.ConclusionsA novel approach for tissue deformation recovery has been proposed based on reliable quasi-dense stereo correspondences. The proposed framework does not rely on additional equipment, allowing seamless integration with the existing surgical workflow. The performance evaluation analysis shows the potential clinical value of the technique.
Abstract-The field of robotic surgery increasingly advances towards highly articulated and continuum robots, requiring new kinematic strategies to enable users to perform dexterous manipulation in confined workspaces. This development is driven by surgical interventions accessing the surgical workspace through natural orifices such as the mouth or the anus. Due to the long and narrow nature of these access pathways, external triangulation at the fulcrum point is very limited or absent, which makes introducing multiple degrees of freedom at the distal end of the instrument necessary. Additionally, high force and miniaturization requirements make the control of such instruments particularly challenging. This paper presents the kinematic considerations needed to effectively manipulate these novel instruments and allow their dexterous control in confined spaces. A non-linear calibration model is further used to map joint to actuator space and improve significantly the precision of the instrument's motion. The effectiveness of the presented approach is quantified with bench tests, and the usability of the system is assessed by three user studies simulating the requirements of a realistic surgical task.
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