Abstract-Dexterity and procedural knowledge are two critical skills surgeons need to master to perform accurate and safe surgical interventions. However, current training systems do not allow to provide an in-depth analysis of surgical gestures to precisely assess these skills. Our objective is to develop a method for the automatic and quantitative assessment of surgical gestures. To reach this goal, we propose a new unsupervised algorithm that can automatically segment kinematic data from robotic training sessions. Without relying on any prior information or model, this algorithm detects critical points in the kinematic data which define relevant spatio-temporal segments. Based on the association of these segments, we obtain an accurate recognition of the gestures involved in the surgical training task. We then perform an advanced analysis and assess our algorithm using datasets recorded during real expert training sessions. After comparing our approach with the manual annotations of the surgical gestures, we observe 97.4% accuracy for the learning purpose and an average matching score of 81.9% for the fullyautomated gesture recognition process. Our results show that trainees workflow can be followed and surgical gestures may be automatically evaluated according to an expert database. This approach tends towards improving training efficiency by minimizing the learning curve.

Abstract-Minimally invasive surgery (MIS) challenges the surgeon's skills due to his/her separation from the operation area, which can be reached with long instruments only. Therefore, the surgeon looses access to the manipulation forces inside the patient. This reduces his/her dexterity when performing the operation. A new compact and lightweight robot for MIS is presented, which allows for the measurement of manipulation forces. The main advantage of this concept is that no miniaturized force sensor has to be integrated into surgical instruments and inserted into the patient. Rather, outside the patient, a standard sensor is attached to a modified trocar, which allows for the undisturbed measurement of manipulation forces. This approach reduces costs and sterilizability demands. Results of in vitro and in vivo force control experiments are presented to validate the concepts.Index Terms-Force control, force measurement, minimally invasive surgery (MIS).

IntroductionEndoscopic skull base surgery allows minimal invasive therapy through the nostrils to treat infectious or tumorous diseases. Surgical and anatomical education in this field is limited by the lack of validated training models in terms of geometric and mechanical accuracy. We choose to evaluate several consumer-grade materials to create a patient-specific 3D-printed skull base model for anatomical learning and surgical training.MethodsFour 3D-printed consumer-grade materials were compared to human cadaver bone: calcium sulfate hemihydrate (named Multicolor), polyamide, resin and polycarbonate. We compared the geometric accuracy, forces required to break thin walls of materials and forces required during drilling.ResultsAll materials had an acceptable global geometric accuracy (from 0.083mm to 0.203mm of global error). Local accuracy was better in polycarbonate (0.09mm) and polyamide (0.15mm) than in Multicolor (0.90mm) and resin (0.86mm). Resin and polyamide thin walls were not broken at 200N. Forces needed to break Multicolor thin walls were 1.6–3.5 times higher than in bone. For polycarbonate, forces applied were 1.6–2.5 times higher. Polycarbonate had a mode of fracture similar to the cadaver bone. Forces applied on materials during drilling followed a normal distribution except for the polyamide which was melted. Energy spent during drilling was respectively 1.6 and 2.6 times higher on bone than on PC and Multicolor.ConclusionPolycarbonate is a good substitute of human cadaver bone for skull base surgery simulation. Thanks to short lead times and reasonable production costs, patient-specific 3D printed models can be used in clinical practice for pre-operative training, improving patient safety.

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Minimally invasive surgery (MIS) challenges the surgeon's skills due to his separation from the operation area which can be reached with long instruments only. Therefore, the surgeon loses access to the manipulation forces inside the patient. This reduces his dexterity when performing the operation. A new compact and lightweight robot for MIS is presented which allows for the measurement of manipulation forces. The main advantage of this concept is that no miniaturized force sensor has to be integrated into surgical instruments and inserted into the patient. Rather, a standard sensor is attached to a modified trocar outside the patient, which allows for the measurement of manipulation forces. This approach reduces costs and sterilizability demands. Results of first force control experiments are presented to show the feasibility of the concepts.

In this paper we describe a new robotic brachytherapy needle-insertion system that is designed to replace the template used in the manual technique. After a brief review of existing robotic systems, we describe the requirements that we based our design upon. A detailed description of the proposed system follows. Our design is capable of positioning and inclining a needle within the same workspace as the manual template. To help improve accuracy, the needle can be rotated about its axis during insertion into the prostate. The system can be mounted on existing steppers and also easily accommodates existing seed dispensers, such as the Mick Applicator.

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