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.

Augmented environments for the targeting of hepatic lesions during image-guided robotic liver surgery

BACKGROUND Stereotactic navigation technology can enhance guidance during surgery and enable the precise reproduction of planned surgical strategies. Currently, specific systems (such as the CAS-One system) are available for instrument guidance in open liver surgery. This study aims to evaluate the implementation of such a system for the targeting of hepatic tumors during robotic liver surgery. MATERIAL AND METHODS Optical tracking references were attached to one of the robotic instruments and to the robotic endoscopic camera. After instrument and video calibration and patient-to-image registration, a virtual model of the tracked instrument and the available three-dimensional images of the liver were displayed directly within the robotic console, superimposed onto the endoscopic video image. An additional superimposed targeting viewer allowed for the visualization of the target tumor, relative to the tip of the instrument, for an assessment of the distance between the tumor and the tool for the realization of safe resection margins. RESULTS Two cirrhotic patients underwent robotic navigated atypical hepatic resections for hepatocellular carcinoma. The augmented endoscopic view allowed for the definition of an accurate resection margin around the tumor. The overlay of reconstructed three-dimensional models was also used during parenchymal transection for the identification of vascular and biliary structures. Operative times were 240 min in the first case and 300 min in the second. There were no intraoperative complications. CONCLUSIONS The da Vinci Surgical System provided an excellent platform for image-guided liver surgery with a stable optic and instrumentation. Robotic image guidance might improve the surgeon's orientation during the operation and increase accuracy in tumor resection. Further developments of this technological combination are needed to deal with organ deformation during surgery.

Effects of arm training with the robotic device ARMin I in chronic stroke: three single cases

BACKGROUND: Several clinical studies on chronic stroke conducted with end-effector-based robots showed improvement of the motor function in the affected arm. Compared to end-effector-based robots, exoskeleton robots provide improved guidance of the human limb and are better suited to train task-oriented movements with a large range of motions. OBJECTIVE: To test whether intensive arm training with the arm exoskeleton ARMin I is feasible with chronic-stroke patients and whether it improves motor function in the paretic arm. METHODS: Three single cases with chronic hemiparesis resulting from unilateral stroke (at least 14 months after stroke). A-B design with 2 weeks of multiple baseline measurements (A), 8 weeks of training (B) with repetitive measurements and a follow-up measurement 8 weeks after training. The training included shoulder and elbow movements with the robotic rehabilitation device ARMin I. Two subjects had three 1-hour sessions per week and 1 subject received five 1-hour sessions per week. The main outcome measurement was the upper-limb part of the Fugl-Meyer Assessment (FMA). RESULTS: The ARMin training was well tolerated by the patients, and the FMA showed moderate, but significant improvements for all 3 subjects (p < 0.05). Most improvements were maintained 8 weeks after discharge. CONCLUSIONS: This study indicates that intensive training with an arm exoskeleton is feasible with chronic-stroke patients. Moderate improvements were found in all 3 subjects, thus further clinical investigations are justified.

Robotic lobectomy: tips, pitfalls and troubleshooting

The robotic approach in thoracic surgery has rapidly gained popularity in recent years. As with the introduction of any new technology, this warrants not only adaptation of the operative technique itself, but also the evolution of appropriate troubleshooting strategies. A selected number of helpful tips and technical procedural manoeuvres have been compiled to prevent intraoperative problems, as well as to overcome challenging situations that can arise during robotic lobectomies. In robotic surgery, as opposed to open surgery or video-assisted thoracic surgery, these tips serve an important purpose for the operating surgeon, as well as the entire surgical team involved in the procedure. All the assembled recommendations have proved their effectiveness and have been successfully used by the authors in many procedures. Furthermore, these manoeuvres have been found to be of great importance in the training and proctoring of thoracic surgeons, fellows and residents (bed-side assistants). This guide of clearly arranged tips and troubleshooting strategies offers surgeons a useful tool to overcome difficult situations in robotic lobectomy and preferably improve the reproducibility and safety of their procedures.

Temperature Prediction Model for Bone Drilling Based on Density Distribution and In Vivo Experiments for Minimally Invasive Robotic Cochlear Implantation

Surgical robots have been proposed ex vivo to drill precise holes in the temporal bone for minimally invasive cochlear implantation. The main risk of the procedure is damage of the facial nerve due to mechanical interaction or due to temperature elevation during the drilling process. To evaluate the thermal risk of the drilling process, a simplified model is proposed which aims to enable an assessment of risk posed to the facial nerve for a given set of constant process parameters for different mastoid bone densities. The model uses the bone density distribution along the drilling trajectory in the mastoid bone to calculate a time dependent heat production function at the tip of the drill bit. Using a time dependent moving point source Green's function, the heat equation can be solved at a certain point in space so that the resulting temperatures can be calculated over time. The model was calibrated and initially verified with in vivo temperature data. The data was collected in minimally invasive robotic drilling of 12 holes in four different sheep. The sheep were anesthetized and the temperature elevations were measured with a thermocouple which was inserted in a previously drilled hole next to the planned drilling trajectory. Bone density distributions were extracted from pre-operative CT data by averaging Hounsfield values over the drill bit diameter. Post-operative [Formula: see text]CT data was used to verify the drilling accuracy of the trajectories. The comparison of measured and calculated temperatures shows a very good match for both heating and cooling phases. The average prediction error of the maximum temperature was less than 0.7 °C and the average root mean square error was approximately 0.5 °C. To analyze potential thermal damage, the model was used to calculate temperature profiles and cumulative equivalent minutes at 43 °C at a minimal distance to the facial nerve. For the selected drilling parameters, temperature elevation profiles and cumulative equivalent minutes suggest that thermal elevation of this minimally invasive cochlear implantation surgery may pose a risk to the facial nerve, especially in sclerotic or high density mastoid bones. Optimized drilling parameters need to be evaluated and the model could be used for future risk evaluation.

A Neuromonitoring Approach to Facial Nerve Preservation During Image-guided Robotic Cochlear Implantation.

HYPOTHESIS A multielectrode probe in combination with an optimized stimulation protocol could provide sufficient sensitivity and specificity to act as an effective safety mechanism for preservation of the facial nerve in case of an unsafe drill distance during image-guided cochlear implantation. BACKGROUND A minimally invasive cochlear implantation is enabled by image-guided and robotic-assisted drilling of an access tunnel to the middle ear cavity. The approach requires the drill to pass at distances below 1 mm from the facial nerve and thus safety mechanisms for protecting this critical structure are required. Neuromonitoring is currently used to determine facial nerve proximity in mastoidectomy but lacks sensitivity and specificity necessaries to effectively distinguish the close distance ranges experienced in the minimally invasive approach, possibly because of current shunting of uninsulated stimulating drilling tools in the drill tunnel and because of nonoptimized stimulation parameters. To this end, we propose an advanced neuromonitoring approach using varying levels of stimulation parameters together with an integrated bipolar and monopolar stimulating probe. MATERIALS AND METHODS An in vivo study (sheep model) was conducted in which measurements at specifically planned and navigated lateral distances from the facial nerve were performed to determine if specific sets of stimulation parameters in combination with the proposed neuromonitoring system could reliably detect an imminent collision with the facial nerve. For the accurate positioning of the neuromonitoring probe, a dedicated robotic system for image-guided cochlear implantation was used and drilling accuracy was corrected on postoperative microcomputed tomographic images. RESULTS From 29 trajectories analyzed in five different subjects, a correlation between stimulus threshold and drill-to-facial nerve distance was found in trajectories colliding with the facial nerve (distance <0.1 mm). The shortest pulse duration that provided the highest linear correlation between stimulation intensity and drill-to-facial nerve distance was 250 μs. Only at low stimulus intensity values (≤0.3 mA) and with the bipolar configurations of the probe did the neuromonitoring system enable sufficient lateral specificity (>95%) at distances to the facial nerve below 0.5 mm. However, reduction in stimulus threshold to 0.3 mA or lower resulted in a decrease of facial nerve distance detection range below 0.1 mm (>95% sensitivity). Subsequent histopathology follow-up of three representative cases where the neuromonitoring system could reliably detect a collision with the facial nerve (distance <0.1 mm) revealed either mild or inexistent damage to the nerve fascicles. CONCLUSION Our findings suggest that although no general correlation between facial nerve distance and stimulation threshold existed, possibly because of variances in patient-specific anatomy, correlations at very close distances to the facial nerve and high levels of specificity would enable a binary response warning system to be developed using the proposed probe at low stimulation currents.

Retraining of interjoint arm coordination after stroke using robot-assisted time-independent functional training

We have developed a haptic-based approach for retraining of interjoint coordination following stroke called time-independent functional training (TIFT) and implemented this mode in the ARMin III robotic exoskeleton. The ARMin III robot was developed by Drs. Robert Riener and Tobias Nef at the Swiss Federal Institute of Technology Zurich (Eidgenossische Technische Hochschule Zurich, or ETH Zurich), in Zurich, Switzerland. In the TIFT mode, the robot maintains arm movements within the proper kinematic trajectory via haptic walls at each joint. These arm movements focus training of interjoint coordination with highly intuitive real-time feedback of performance; arm movements advance within the trajectory only if their movement coordination is correct. In initial testing, 37 nondisabled subjects received a single session of learning of a complex pattern. Subjects were randomized to TIFT or visual demonstration or moved along with the robot as it moved though the pattern (time-dependent [TD] training). We examined visual demonstration to separate the effects of action observation on motor learning from the effects of the two haptic guidance methods. During these training trials, TIFT subjects reduced error and interaction forces between the robot and arm, while TD subject performance did not change. All groups showed significant learning of the trajectory during unassisted recall trials, but we observed no difference in learning between groups, possibly because this learning task is dominated by vision. Further testing in stroke populations is warranted.

Validation of a modified AVHRR aerosol optical depth retrieval algorithm over Central Europe

The Advanced Very High Resolution Radiometer (AVHRR) carried on board the National Oceanic and Atmospheric Administration (NOAA) and the Meteorological Operational Satellite (MetOp) polar orbiting satellites is the only instrument offering more than 25 years of satellite data to analyse aerosols on a daily basis. The present study assessed a modified AVHRR aerosol optical depth τa retrieval over land for Europe. The algorithm might also be applied to other parts of the world with similar surface characteristics like Europe, only the aerosol properties would have to be adapted to a new region. The initial approach used a relationship between Sun photometer measurements from the Aerosol Robotic Network (AERONET) and the satellite data to post-process the retrieved τa. Herein a quasi-stand-alone procedure, which is more suitable for the pre-AERONET era, is presented. In addition, the estimation of surface reflectance, the aerosol model, and other processing steps have been adapted. The method's cross-platform applicability was tested by validating τa from NOAA-17 and NOAA-18 AVHRR at 15 AERONET sites in Central Europe (40.5° N–50° N, 0° E–17° E) from August 2005 to December 2007. Furthermore, the accuracy of the AVHRR retrieval was related to products from two newer instruments, the Medium Resolution Imaging Spectrometer (MERIS) on board the Environmental Satellite (ENVISAT) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Aqua/Terra. Considering the linear correlation coefficient R, the AVHRR results were similar to those of MERIS with even lower root mean square error RMSE. Not surprisingly, MODIS, with its high spectral coverage, gave the highest R and lowest RMSE. Regarding monthly averaged τa, the results were ambiguous. Focusing on small-scale structures, R was reduced for all sensors, whereas the RMSE solely for MERIS substantially increased. Regarding larger areas like Central Europe, the error statistics were similar to the individual match-ups. This was mainly explained with sampling issues. With the successful validation of AVHRR we are now able to concentrate on our large data archive dating back to 1985. This is a unique opportunity for both climate and air pollution studies over land surfaces.

Minimally invasive postmortem telebiopsy

For the past 10 years, medical imaging techniques have been increasingly applied to forensic investigations. To obtain histological and toxicological information, tissue and liquid samples are required. In this article, we describe the development of a low-cost, secure, and reliable approach for a telematic add-on for remotely planning biopsies on the Virtobot robotic system. Data sets are encrypted and submitted over the Internet. A plugin for the OsiriX medical image viewer allows for remote planning of needle trajectories that are used for needle placement. The application of teleradiological methods to image-guided biopsy in the forensic setting has the potential to reduce costs and, in conjunction with a mobile computer tomographic scanner, allows for tissue sampling in a mass casualty situation involving nuclear, biological, or chemical agents, in a manner that minimizes the risk to involved staff.

Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks

Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.