Concept: Automotive navigation system
The Kalman filter has been widely applied in the field of dynamic navigation and positioning. However, its performance will be degraded in the presence of significant model errors and uncertain interferences. In the literature, the fading filter was proposed to control the influences of the model errors, and the H-infinity filter can be adopted to address the uncertainties by minimizing the estimation error in the worst case. In this paper, a new multiple fading factor, suitable for the Global Positioning System (GPS) and the Inertial Navigation System (INS) integrated navigation system, is proposed based on the optimization of the filter, and a comprehensive filtering algorithm is constructed by integrating the advantages of the H-infinity filter and the proposed multiple fading filter. Measurement data of the GPS/INS integrated navigation system are collected under actual conditions. Stability and robustness of the proposed filtering algorithm are tested with various experiments and contrastive analysis are performed with the measurement data. Results demonstrate that both the filter divergence and the influences of outliers are restrained effectively with the proposed filtering algorithm, and precision of the filtering results are improved simultaneously.
Implant placement has been widely used in various kinds of surgery. However, accurate intraoperative drilling performance is essential to avoid injury to adjacent structures. Although some commercially-available surgical navigation systems have been approved for clinical applications, these systems are expensive and the source code is not available to researchers. 3D Slicer is a free, open source software platform for the research community of computer-aided surgery. In this study, a loadable module based on Slicer has been developed and validated to support surgical navigation. This research module allows reliable calibration of the surgical drill, point-based registration and surface matching registration, so that the position and orientation of the surgical drill can be tracked and displayed on the computer screen in real time, aiming at reducing risks. In accuracy verification experiments, the mean target registration error (TRE) for point-based and surface-based registration were 0.31±0.06mm and 1.01±0.06mm respectively, which should meet clinical requirements. Both phantom and cadaver experiments demonstrated the feasibility of our surgical navigation software module.
Intraoperative navigated ultrasonography has reached clinical acceptance, while published data for the accuracy of some systems are missing. We technically quantified and optimised the accuracy of the integration of an external ultrasonography system into a BrainLab navigation system.
Navigational skills decline with age, and this decline is even more pronounced in cognitively impaired (CI) older adults. Navigation assistance is an emerging functionality of robotic rollators (RRs). The evidence on the effectiveness of RR-integrated navigation systems in potential end-users is, however, scarce.
Transfer alignment is always a key technology in a strapdown inertial navigation system (SINS) because of its rapidity and accuracy. In this paper a transfer alignment model is established, which contains the SINS error model and the measurement model. The time delay in the process of transfer alignment is analyzed, and an H∞ filtering method with delay compensation is presented. Then the H∞ filtering theory and the robust mechanism of H∞ filter are deduced and analyzed in detail. In order to improve the transfer alignment accuracy in SINS with time delay, an adaptive H∞ filtering method with delay compensation is proposed. Since the robustness factor plays an important role in the filtering process and has effect on the filtering accuracy, the adaptive H∞ filter with delay compensation can adjust the value of robustness factor adaptively according to the dynamic external environment. The vehicle transfer alignment experiment indicates that by using the adaptive H∞ filtering method with delay compensation, the transfer alignment accuracy and the pure inertial navigation accuracy can be dramatically improved, which demonstrates the superiority of the proposed filtering method.
Rotational malpositioning of the tibial component can lead to poor functional outcome in TKA. Although various surgical techniques have been proposed, precise rotational placement of the tibial component was difficult to accomplish even with the use of a navigation system. The purpose of this study is to assess whether combined CT-based and image-free navigation systems replicate accurately the rotational alignment of tibial component that was preoperatively planned on CT, compared with the conventional method.
Accuracy of screw fixation using the O-arm(®) and StealthStation(®) navigation system for unstable pelvic ring fractures
- European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
- Published 4 months ago
Screw fixation for unstable pelvic ring fractures is generally performed using the C-arm. However, some studies reported erroneous piercing with screws, nerve injuries, and vessel injuries. Recent studies have reported the efficacy of screw fixations using navigation systems. The purpose of this retrospective study was to investigate the accuracy of screw fixation using the O-arm(®) imaging system and StealthStation(®) navigation system for unstable pelvic ring fractures.
Line scanning cameras, which capture only a single line of pixels, have been increasingly used in ground based mobile or robotic platforms. In applications where it is advantageous to directly georeference the camera data to world coordinates, an accurate estimate of the camera’s 6D pose is required. This paper focuses on the common case where a mobile platform is equipped with a rigidly mounted line scanning camera, whose pose is unknown, and a navigation system providing vehicle body pose estimates. We propose a novel method that estimates the camera’s pose relative to the navigation system. The approach involves imaging and manually labelling a calibration pattern with distinctly identifiable points, triangulating these points from camera and navigation system data and reprojecting them in order to compute a likelihood, which is maximised to estimate the 6D camera pose. Additionally, a Markov Chain Monte Carlo (MCMC) algorithm is used to estimate the uncertainty of the offset. Tested on two different platforms, the method was able to estimate the pose to within 0.06 m/1.05 ∘ and 0.18 m/2.39 ∘ . We also propose several approaches to displaying and interpreting the 6D results in a human readable way.
Challenging environments pose difficulties for terrain navigation, and therefore wearable and multimodal navigation systems have been proposed to overcome these difficulties. Few such navigation systems, however, have been evaluated in field conditions. We evaluated how a multimodal system can aid in navigating in a forest in the context of a military exercise. The system included a head-mounted display, headphones, and a tactile vibrating vest. Visual, auditory, and tactile modalities were tested and evaluated using unimodal, bimodal, and trimodal conditions. Questionnaires, interviews and observations were used to evaluate the advantages and disadvantages of each modality and their multimodal use. The guidance was considered easy to interpret and helpful in navigation. Simplicity of the displayed information was required, which was partially conflicting with the request for having both distance and directional information available.
- International journal of computer assisted radiology and surgery
- Published 8 months ago
Radiofrequency ablation for liver tumors (liver RFA) is widely performed under ultrasound guidance. However, discriminating between the tumor and the needle is often difficult because of cavitation caused by RFA-induced coagulation. An unclear ultrasound image can lead to complications and tumor residue. Therefore, image-guided navigation systems based on fiducial registration have been developed. Fiducial points are usually set on a patient’s skin. But the use of internal fiducial points can improve the accuracy of navigation. In this study, a new device is introduced to use internal fiducial points using 2D US.