Robotassisterad kirurgi har blivit alltmer förekommande som operationsmetod till fördel för dess kirurgiska precision. Utifrån den kirurgiska teknologin ställs ytterligare krav på anestesisjuksköterskan, som under operationerna ansvarar för patientens anestesi, upprätthållande av fri luftväg, hemodynamisk stabilitet. Tillsammans med teamet ansvarar anestesisjuksköterskan för patientens positionering och säkerhet. Syftet med studien var att belysa anestesisjuksköterskors vårdande av patienter som genomgick robotassisterad kirurgi. En kvalitativ ansats ligger till grund för studien och en ostrukturerad deltagande observationsstudie har genomförts. Sex anestesisjuksköterskor observerades vid tolv olika tillfällen. Materialet från observationer analyserades med Elo och Kyngäs induktiva kvalitativa innehållsanalys. Nio subkategorier och tre kategorier framkom efter analysen. I kategorin arbetsmiljön på operationssalen framkom bland annat att anestesisjuksköterskan arbetade i en miljö med begränsad åtkomst till patienten och utrustningen. I kategorin omtanke och vårdande observerades anestesisjuksköterskans lugnande samtal och stöttning till patienten samt handlingar för patientens välbefinnande. I tredje kategorin patientsäkert arbetssätt arbetade anestesisjuksköterskan tillsammans i teamet med förebyggande säkerhetsåtgärder. Slutligen arbetar anestesisjuksköterskan i en högteknologisk miljö, som kräver anpassning utifrån anestesiologiskt perspektiv. Trots den emellanåt besvärliga arbetssituationen som anestesisjuksköterskan befinner sig upprätthålls både patientsäkerhet samt ett gott teamarbete. / Robot-assisted surgery has become increasingly prevalent, in favor of it´s surgical precision. The surgical technology additional requirements are imposed on the nurse anesthetist, who is responsible for the patient´s anesthesia, free airway and hemodynamic stability. Together with the team, the nurse anesthetist is responsible for the patient's positioning and safety. The purpose of this study was to shed light on the nurse anesthetists' care of patients who underwent robot-assisted surgery. A qualitative approach was used and an unstructured participatory observational study has been conducted. Six nurse anesthetists were observed on twelve occasions. The material was analyzed with Elo and Kyngäs inductive qualitative content analysis. Nine subcategories and three categories emerged. The category Work environment in the operating room showed that the nurse anesthetist worked in an environment with limited access to the patient. The Solicitude and caring category, showed the nurse anesthetist gave support to the patient and made actions for well-being. In the category Patient-safe working methods, the nurse anesthetist worked with the team on preventive safety measures. Finally, the nurse anesthetist works in a high-tech environment which requires adaptation. Despite the sometimes difficult work situation for the nurse anesthetist, both patient safety and good teamwork are maintained.

Yes / Most of surgical simulators employ a linear elastic model to simulate soft tissue material properties due to its computational efficiency and the simplicity. However, soft tissues often have elaborate nonlinearmaterial characteristics. Most prominently, soft tissues are soft and compliant to small strains, but after initial deformations they are very resistant to further deformations even under large forces. Such material characteristic is referred as the nonlinear material incompliant which is computationally expensive and numerically difficult to simulate. This paper presents a constraint-based finite-element algorithm to simulate the nonlinear incompliant tissue materials efficiently for interactive simulation applications such as virtual surgery. Firstly, the proposed algorithm models the material stiffness behavior of soft tissues with a set of 3-D strain limit constraints on deformation strain tensors. By enforcing a large number of geometric constraints to achieve the material stiffness, the algorithm reduces the task of solving stiff equations of motion with a general numerical solver to iteratively resolving a set of constraints with a nonlinear Gauss–Seidel iterative process. Secondly, as a Gauss–Seidel method processes constraints individually, in order to speed up the global convergence of the large constrained system, a multiresolution hierarchy structure is also used to accelerate the computation significantly, making interactive simulations possible at a high level of details . Finally, this paper also presents a simple-to-build data acquisition system to validate simulation results with ex vivo tissue measurements. An interactive virtual reality-based simulation system is also demonstrated.

L'évolution des techniques chirurgicales, par l'utilisation de robots, permet des interventions mini-invasives avec une très grande précision et ouvre des perspectives d'interventions chirurgicales à distance, comme l'a démontré la célèbre expérimentation « Opération Lindbergh » en 2001. La contrepartie de cette évolution réside dans des volumes de données considérables qui nécessitent des ressources importantes pour leur transmission. La compression avec pertes de ces données devient donc inévitable. Celle-ci constitue un défi majeur dans le contexte médical, celui de l'impact des pertes sur la qualité des données et leur exploitation. Mes travaux de thèse concernent l'étude de techniques permettant l'évaluation de la qualité des vidéos dans un contexte de robotique chirurgicale. Deux approches méthodologiques sont possibles : l'une à caractère subjectif et l'autre à caractère objectif. Nous montrons qu'il existe un seuil de tolérance à la compression avec pertes de type MPEG2 et H.264 pour les vidéos chirurgicales. Les résultats obtenus suite aux essais subjectifs de la qualité ont permis également de mettre en exergue une corrélation entre les mesures subjectives effectuées et une mesure objective utilisant l'information structurelle de l'image. Ceci permet de prédire la qualité telle qu'elle est perçue par les observateurs humains. Enfin, la détermination d'un seuil de tolérance à la compression avec pertes a permis la mise en place d'une plateforme de transmission en temps réel sur un réseau IP de vidéos chirurgicales compressées avec le standard H.264 entre le CHU de Nancy et l'école de chirurgie / The digital revolution in medical environment speeds up development of remote Robotic-Assisted Surgery and consequently the transmission of medical numerical data such as pictures or videos becomes possible. However, medical video transmission requires significant bandwidth and high compression ratios, only accessible with lossy compression. Therefore research effort has been focussed on video compression algorithms such as MPEG2 and H.264. In this work, we are interested in the question of compression thresholds and associated bitrates are coherent with the acceptance level of the quality in the field of medical video. To evaluate compressed medical video quality, we performed a subjective assessment test with a panel of human observers using a DSCQS (Double-Stimuli Continuous Quality Scale) protocol derived from the ITU-R BT-500-11 recommendations. Promising results estimate that 3 Mbits/s could be sufficient (compression ratio aroundthreshold compression level around 90:1 compared to the original 270 Mbits/s) as far as perceived quality is concerned. Otherwise, determining a tolerance to lossy compression has allowed implementation of a platform for real-time transmission over an IP network for surgical videos compressed with the H.264 standard from the University Hospital of Nancy and the school of surgery

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<p>This thesis presents a computational model of the surgical stitching tasks and a path planning algorithm for robotic assisted stitching. The overall goal of the research is to enable surgical robots to perform automatic suturing. Suturing comprises several distinct steps, one of them is the stitching. During stitching, reaching the desired exit point is difficult because it must be accomplished without direct visual feedback. Moreover, the stitching is a time consuming procedure repeated multiple times during suturing. Therefore, it would be desirable to enhance the surgical robots with the ability of performing automatic suturing. The focus of this work is on the automation of the stitching task. The thesis presents a model based path planning algorithm for the autonomous stitching. The method uses a nonlinear model for the curved needle - soft tissue interaction. The tissue is modeled as a deformable object using continuum mechanics tools. This thesis uses a mesh free deformable tissue model namely, Reproducing Kernel Particle Method (RKPM). RKPM was chosen as it has been proven to accurately handle large deformation and requires no re-meshing algorithms. This method has the potential to be more realistic in modeling various material characteristics by using appropriate strain energy functions. The stitching task is simulated using a constrained deformable model; the deformable tissue is constrained by the interaction with the curved needle. The stitching model was used for needle trajectory path planning during stitching. This new path planning algorithm for the robotic stitching was developed, implemented, and evaluated. Several simulations and experiments were conducted. The first group of simulations comprised random insertions from different insertion points without planning to assess the modeling method and the trajectory of the needle inside the tissue. Then the parameters of the simulations were set according to the measured experimental parameters. The proposed path planning method was tested using a surgical ETHICON needle of type SH 1=2 Circle with the radius of 8:88mm attached to a robotic manipulator. The needle was held by a grasper which is attached to the robotic arm. The experimental results illustrate that the path planned curved needle insertions are fifty percent more accurate than the unplanned ones. The results also show that this open loop approach is sensitive to model parameters.</p> / Master of Applied Science (MASc)