A robotic system to train activities of daily living in a virtual environment

In the past decade, several arm rehabilitation robots have been developed to assist neurological patients during therapy. Early devices were limited in their number of degrees of freedom and range of motion, whereas newer robots such as the ARMin robot can support the entire arm. Often, these devices are combined with virtual environments to integrate motivating game-like scenarios. Several studies have shown a positive effect of game-playing on therapy outcome by increasing motivation. In addition, we assume that practicing highly functional movements can further enhance therapy outcome by facilitating the transfer of motor abilities acquired in therapy to daily life. Therefore, we present a rehabilitation system that enables the training of activities of daily living (ADL) with the support of an assistive robot. Important ADL tasks have been identified and implemented in a virtual environment. A patient-cooperative control strategy with adaptable freedom in timing and space was developed to assist the patient during the task. The technical feasibility and usability of the system was evaluated with seven healthy subjects and three chronic stroke patients.

Concurrent and predictive validation of a novel robotic surgery simulator: a prospective, randomized study

We evaluated the concurrent and predictive validity of a novel robotic surgery simulator in a prospective, randomized study.

Robotic and laparoscopic high extended pelvic lymph node dissection during radical cystectomy: technique and outcomes

With the increasing use of laparoscopic and robotic radical cystectomy (RC), there are perceived concerns about the adequacy of lymph node dissection (LND).

Cost-effectiveness of open versus laparoscopic versus robotic-assisted laparoscopic cystectomy and urinary diversion

To provide insight into the recently published cost comparisons in the context of open, laparoscopic, and robotic-assisted laparoscopic radical cystectomy and to demonstrate the complexity of such economic analyses.

Face, content and construct validity of a novel robotic surgery simulator

We evaluated the face, content and construct validity of the novel da Vinci® Skills Simulator™ using the da Vinci Si™ Surgeon Console as the surgeon interface.

High-accuracy patient-to-image registration for the facilitation of image-guided robotic microsurgery on the head

Image-guided microsurgery requires accuracies an order of magnitude higher than today's navigation systems provide. A critical step toward the achievement of such low-error requirements is a highly accurate and verified patient-to-image registration. With the aim of reducing target registration error to a level that would facilitate the use of image-guided robotic microsurgery on the rigid anatomy of the head, we have developed a semiautomatic fiducial detection technique. Automatic force-controlled localization of fiducials on the patient is achieved through the implementation of a robotic-controlled tactile search within the head of a standard surgical screw. Precise detection of the corresponding fiducials in the image data is realized using an automated model-based matching algorithm on high-resolution, isometric cone beam CT images. Verification of the registration technique on phantoms demonstrated that through the elimination of user variability, clinically relevant target registration errors of approximately 0.1 mm could be achieved.

Validation of a novel robotic-assisted partial nephrectomy surgical training model

What's known on the subject? and What does the study add? One area of particular growth for robotic surgery has been partial nephrectomy. Despite a perceived notion that robotic-assisted partial nephrectomy is more easily adaptable compared to laparoscopic partial nephrectomy, there is nonetheless an associated learning curve. Validated training models with a corresponding assessment method for robotic-assisted partial nephrectomy were previously unavailable. We have designed and validated a RAPN surgical model appropriate for resident and fellow training.

Non-robotic thoracoscopic internal mammary artery preparation in the pig. A training model

Notwithstanding non-robotic, thoracoscopic preparation of the internal mammary artery (IMA) is a difficult surgical task, an appropriate experimental training model is lacking. We evaluated the young domestic pig for this purpose. Four domestic female pigs (30-40 kg body weight) were used for this study. Bilateral thoracoscopic preparation of the IMA was carried out under continuous, pressure controlled CO(2) insufflation. A 30 degrees rigid thoracoscope was inserted through a 10-mm port in the 5th/6th intercostal space (ICS) dorsally to the posterior axillary line. The dissection instrument (Ultracision Harmonic Scalpel) was inserted (5-mm port) in the 7th ICS at the posterior axillary line and the endo-forceps (5-mm port) in the 5th ICS at the posterior axillary line. Thoracoscopic IMA preparation in pig resulted more difficult than in man. A total of seven IMAs were prepared in their full intrathoracic length. A change in the preparation technique (lateral detachment of the endothoracic muscle) improved the safety of the procedure, allowing all four respective IMAs to be prepared safely, while the initial technique ensued an injury for 2 out of 3 vessels. The described young domestic pig model is suitable for experimental training of bilateral thoracoscopic IMA preparation.

Estimation of tool pose based on force-density correlation during robotic drilling

The application of image-guided systems with or without support by surgical robots relies on the accuracy of the navigation process, including patient-to-image registration. The surgeon must carry out the procedure based on the information provided by the navigation system, usually without being able to verify its correctness beyond visual inspection. Misleading surrogate parameters such as the fiducial registration error are often used to describe the success of the registration process, while a lack of methods describing the effects of navigation errors, such as those caused by tracking or calibration, may prevent the application of image guidance in certain accuracy-critical interventions. During minimally invasive mastoidectomy for cochlear implantation, a direct tunnel is drilled from the outside of the mastoid to a target on the cochlea based on registration using landmarks solely on the surface of the skull. Using this methodology, it is impossible to detect if the drill is advancing in the correct direction and that injury of the facial nerve will be avoided. To overcome this problem, a tool localization method based on drilling process information is proposed. The algorithm estimates the pose of a robot-guided surgical tool during a drilling task based on the correlation of the observed axial drilling force and the heterogeneous bone density in the mastoid extracted from 3-D image data. We present here one possible implementation of this method tested on ten tunnels drilled into three human cadaver specimens where an average tool localization accuracy of 0.29 mm was observed.

Feasibility of Using EMG for Early Detection of the Facial Nerve During Robotic Direct Cochlear Access

HYPOTHESIS Facial nerve monitoring can be used synchronous with a high-precision robotic tool as a functional warning to prevent of a collision of the drill bit with the facial nerve during direct cochlear access (DCA). BACKGROUND Minimally invasive direct cochlear access (DCA) aims to eliminate the need for a mastoidectomy by drilling a small tunnel through the facial recess to the cochlea with the aid of stereotactic tool guidance. Because the procedure is performed in a blind manner, structures such as the facial nerve are at risk. Neuromonitoring is a commonly used tool to help surgeons identify the facial nerve (FN) during routine surgical procedures in the mastoid. Recently, neuromonitoring technology was integrated into a commercially available drill system enabling real-time monitoring of the FN. The objective of this study was to determine if this drilling system could be used to warn of an impending collision with the FN during robot-assisted DCA. MATERIALS AND METHODS The sheep was chosen as a suitable model for this study because of its similarity to the human ear anatomy. The same surgical workflow applicable to human patients was performed in the animal model. Bone screws, serving as reference fiducials, were placed in the skull near the ear canal. The sheep head was imaged using a computed tomographic scanner and segmentation of FN, mastoid, and other relevant structures as well as planning of drilling trajectories was carried out using a dedicated software tool. During the actual procedure, a surgical drill system was connected to a nerve monitor and guided by a custom built robot system. As the planned trajectories were drilled, stimulation and EMG response signals were recorded. A postoperative analysis was achieved after each surgery to determine the actual drilled positions. RESULTS Using the calibrated pose synchronized with the EMG signals, the precise relationship between distance to FN and EMG with 3 different stimulation intensities could be determined for 11 different tunnels drilled in 3 different subjects. CONCLUSION From the results, it was determined that the current implementation of the neuromonitoring system lacks sensitivity and repeatability necessary to be used as a warning device in robotic DCA. We hypothesize that this is primarily because of the stimulation pattern achieved using a noninsulated drill as a stimulating probe. Further work is necessary to determine whether specific changes to the design can improve the sensitivity and specificity.

Investigation on the evolution of an indoor robotic localization system based on wireless networks

This work addresses the evolution of an artificial neural network (ANN) to assist in the problem of indoor robotic localization. We investigate the design and building of an autonomous localization system based on information gathered from wireless networks (WN). The article focuses on the evolved ANN, which provides the position of a robot in a space, as in a Cartesian coordinate system, corroborating with the evolutionary robotic research area and showing its practical viability. The proposed system was tested in several experiments, evaluating not only the impact of different evolutionary computation parameters but also the role of the transfer functions on the evolution of the ANN. Results show that slight variations in the parameters lead to significant differences on the evolution process and, therefore, in the accuracy of the robot position.