The use of fuzzy logic in the medical environment is very promising as it offers the possibility to incorporate the knowledge and experience of the physician into fuzzy sets and rules. The type-2 fuzzy logic makes it even possible to incorporate the knowledge of several physicians into a single controller, thus enhancing it with the uncertainty present among different physicians. Once the controller is defined the outputs depend solely on its current inputs. It does not take any process information into account. For that purpose the controller is enhanced with an adaptive algorithm. It allows gradual changes by also keeping the initial rules, which had been defined by the physician and are helping for his comprehension of how rules are being applied. The type-2 fuzzy controller and the adaptive algorithm are described and compared to each other in the application of blood pressure regulation with drugs.

This paper introduces a new method for remote surgical cutting by providing haptic guidance along a trajectory that is measured in-situ through a miniature, tool-tip mounted endoscopic camera. By directly augmenting the instrument with a camera, instead of relying on an additional conventional endoscope, the approach becomes independent from inherent calibration uncertainties of the telemanipulation system, other than the micro camera itself, and from registration of pre- and intra-operative surgical data. We calculate a smooth cut path with corresponding scalpel orientation to guide the user towards the optimal trajectory. Experiments are conducted with passive and active haptic virtual fixtures. During active fixturing the optimal forward velocity is calculated to follow the path. The results indicate an improvement in terms of position accuracy, blade orientation, and forward velocity.

We present a novel method for vision-based recovery of three-dimensional structures through simultaneous model reconstruction and camera position tracking from monocular images. Our approach does not rely on robust feature detecting schemes (such as SIFT, Good Features to Track etc.), but works directly on intensity values in the captured images. Thus, it is well-suited for reconstruction of surfaces that exhibit only little texture due to partial homogeneity of the surfaces.

Extra-corporal Circulation Support Systems (ECCS) are used in cardiac surgery on a daily basis. Surgeons and perfusionists supervise patients' vital signals such as heart rate or blood pressure and ensure secure and errorless operation of the system. An automated ECCS can help to reduce the workload of human operators and can provide a patient with optimal perfusion. In our opinion a fuzzy controller is predestinated for autonomus heart-lung machine (HLM) control, since it allows a straightforward implementation of expert knowledge and is able to deal with inherently imprecise data. In this work we present a comprehensive approach towards intelligent HLM automation that uses fuzzy logic as a control methodology. This approach includes the development of a mechanical circulatory model, a purely virtual model, as well as animal experiments.

The collaborative research center SFB453 (www.sfb453.de) aims to realize high-fidelity telepresence and teleaction systems. Telepresence and teleaction systems extend the human workspace to remote locations in order to overcome barriers like distance, scaling, danger or the human skin. Using a human-system interface the human operator controls a remotely located teleoperator. Multi-modal feedback in form of visual, auditory, and haptic data is used to increase the feeling of telepresence. Different application areas including minimally invasive surgery, on-orbit servicing, microassembly as well as tele-manufacturing and tele-maintenance are targeted.

Despite the fact that minimally invasive robotic surgery provides many advantages for patients, such as reduced tissue trauma and shorter hospitalization, complex tasks (e.g. tissue piercing or knot-tying) are still time-consuming, error-prone and lead to quicker fatigue of the surgeon. Automating these recurrent tasks could greatly reduce total surgery time for patients and disburden the surgeon while he can focus on higher level challenges. This work tackles the problem of autonomous tissue piercing in robot-assisted laparoscopic surgery with a circular needle and general purpose surgical instruments. To command the instruments to an incision point, the surgeon utilizes a laser pointer to indicate the stitching area. A precise positioning of the needle is obtained by means of a switching visual servoing approach and the subsequent stitch is performed in a circular motion.

Telesurgery systems integrate multimodal communication and robotic technologies to enable surgical procedures to be performed from remote locations. They allow human surgeons to intuitively control laparoscopic instruments and to navigate within the human body. In this paper, we present selected topics on multimodal interaction in the context of telesurgery applications. These are results from the collaborative research project SFB 453 on ldquoHigh-Fidelity Telepresence and Teleactionrdquo which is funded by the German Research Foundation in the larger Munich area. The focus in this paper is on multimodal information processing and communication including simulation of surgical targets in the human body. Furthermore, we present an overview of our advanced multimodal telesurgery demonstrators that provide a comprehensive platform for our collaborative telepresence research.

The term scaffolding, with respect to human education, was first coined in the 1970ies, although the basic concept originates back to the 1930ies. The main idea is to formalize the superior knowledge of a teacher in a certain way to generate support for a trainee. In practice, this concept can be implemented as concrete as a cloze, which assists pupils in learning a foreign language, or it might be as abstract as a social environment, which facilitates learning of specific tasks. This paper introduces a novel approach towards robotic learning by means of such a scaffolding framework. In this case, the scaffolding is constituted by abstract patterns, which facilitate the structuring and segmentation of information during "Learning by Demonstration". The methodology was applied to a real-world scenario of robot-assisted surgery.

A popular method for an easy and also flexible programming of robots is learning by demonstration. An intelligent controller learns a task from several examples carried out by an experienced user. Afterwards, the task can be adapted to new, formerly unknown environments. One particular challenge arising with this technique is generalization of demonstrations in order to get a generic description of the task. In this paper a new methodology for solving this problem is proposed. The main part of the algorithm exploits principles known from fluid dynamics.

In this paper we present an application of robotic systems in minimally invasive surgery. We have assembled a bi-manual telemanipulator capable of delicate operations. Each robotic arm has eight degrees of freedom which enables free manipulation via trocar kinematics. In addition minimally invasive instruments were equipped with strain gauge force sensors that can measure forces along three translational directions of the instrument's shaft. Forces are displayed to the user by means of two haptic devices which are also used for input. An endoscopic stereo-camera provides pictures from the region of operation to the user. In order to emulate a stereoscopic impression, pictures can be displayed by means of either a head mounted display, a CRT-screen equipped with shutter technology or a 3D video projection. With this system we have assessed the quality of force feedback and we have performed typical operations known from cardiac surgery. We also have shown that it is possible to perform certain recurrent tasks (like knot tying) automatically. Within this context we have implemented two application examples. In the first example a surgical knot is recorded and afterwards replayed with increased speed at the same position. The second example is the instantiation of a predefined knot at an arbitrary position.

Coronary angiography has become an important tool in modern medicine by providing an additional modality for heart disease diagnostics. Even though the recorded images (or image sequences) are digitally available, their analysis is very elementary in nature in most cases: the surgeon studies the angiograms before the operation, and operates without having them available in the operation room. It is up to the surgeon's memory to accurately remember the relevant details like locations of stenosis or occlusion. To improve both the analysis and the on-site availability of angiograms,but also to drastically increase the usefulness of the angiogram as a diagnostical modality, we present a novel approach which combines several advanced techniques into a single tool allowing real-time augmentation of in situ beating heart image sequences with the corresponding angiogram. The software toolset we developed so far contains the removal of specularites from the glossy heart surface and the reconstruction of the original image colors, color based coronary artery segmentation in beating heart image sequences, angiogram segmentation and symbolic representation, OpenGL based augmentation and visualization, mass-spring-NURBS-based soft tissue simulation. Future work will focus on developing robust matching techniques and on integrating the software tools into an operation room suitable hardware setup.

Minimally invasive robotic surgery systems has entered daily practice in dedicated clinical centers. Especially heart surgery profits from this new technique, due to a higher accuracy compared to conventional endoscopic interventions. Nevertheless some drawbacks have restricted a broader acceptance of these devices. The most urgent issues are lack of haptic feedback and prolonged operation time. Our research project tackles both topics, on the one hand by adding high fidelity force-feedback, on the other hand by automating recurrent manipulation tasks. These features have been integrated into the Endo[PA]R (endoscopic partially-autonomous robot) system, an open evaluation platform for robotic surgery. The setup comprises two low-payload robots equipped with sensorized surgical instruments and a third robot carrying a stereo camera system. Trocar kinematics, enabling surgical manipulation through small incisions, has been implemented for all robotic arms. In order to ensure operation close to reality, a thorax and heart phantom for surgical training was used in the experiments. Stereo vision is provided via a head-mounted display and force-reflective input devices are employed for user interaction. The system was evaluated by surgeons and it was capable of performing autonomous knot-tying.