Navigation Errors Research Articles

Accuracy of acetabular cup insertion in an anterolateral supine approach using an accelerometer-based portable navigation system.

The purpose of this study was to determine the accuracy of acetabular cup insertion during total hip arthroplasty (THA) in a supine position using an accelerometer-based portable navigation system. A single-surgeon study was conducted in which 62 prospective patients with navigation and 42 retrospective patients without navigation as historical controls were compared. The patients underwent THA via an anterolateral supine approach. The absolute values of errors of radiographic inclination and anteversion were calculated. The navigation error was also calculated. The factors that affected the absolute values of errors of cup alignment were determined. The mean absolute error of the postoperative CT measurement from the target angle for radiographic inclination was 3.8° in the navigation group and 6.6° in the control group (P < 0.001). The mean absolute error for anteversion was 3.3° in the navigation group and 5.9° in the control group (P < 0.001). The mean absolute values of navigation error were 3.7° ± 2.8° in inclination and 3.0° ± 2.6° in anteversion. Changes in the pelvic tilt angle among preoperative, intraoperative, and postoperative were the significant risk factors for the absolute values of navigation error of anteversion relative to the anterior pelvic plane. Other factors affecting the absolute values of errors in the navigation group were not found for radiographic inclination and anteversion. The portable navigation system significantly improved the accuracy of cup inclination and anteversion. Changes in the pelvic tilt were the risk factors for the error of anteversion relative to the anterior pelvic plane.

Vertical-surface navigation in the Neotropical whip spider Paraphrynus laevifrons (Arachnida: Amblypygi).

Studies on whip spider navigation have focused on their ability to locate goal locations in the horizontal plane (e.g., when moving along the ground). However, many species of tropical whip spiders reside and move along surfaces in the vertical plane (e.g., trees). Under controlled laboratory conditions, the current study investigated the ability of the tropical whip spider, Paraphrynus laevifrons, to return to a home shelter on a vertical surface in the presence of numerous, similar and competing refuge sites, as well as the distribution of navigational errors in the vertical, horizontal and diagonal plane. We also assessed the relative importance of sensory cues originating from a previously occupied home shelter compared to the position of a previously occupied shelter in guiding shelter choice. It was found that P. laevifrons displays robust fidelity in re-locating a home shelter on a vertical surface. When navigational errors did occur, they were not significantly different in all three directions. Additionally, cue-conflict test trials revealed that cues associated with an original home shelter, likely self-deposited chemical signals, were more important than sources of positional information in guiding the shelter choice of P. laevifrons.

GNSS/IMU/ODO/LiDAR-SLAM Integrated Navigation System Using IMU/ODO Pre-Integration.

In this paper, we proposed a multi-sensor integrated navigation system composed of GNSS (global navigation satellite system), IMU (inertial measurement unit), odometer (ODO), and LiDAR (light detection and ranging)-SLAM (simultaneous localization and mapping). The dead reckoning results were obtained using IMU/ODO in the front-end. The graph optimization was used to fuse the GNSS position, IMU/ODO pre-integration results, and the relative position and relative attitude from LiDAR-SLAM to obtain the final navigation results in the back-end. The odometer information is introduced in the pre-integration algorithm to mitigate the large drift rate of the IMU. The sliding window method was also adopted to avoid the increasing parameter numbers of the graph optimization. Land vehicle tests were conducted in both open-sky areas and tunnel cases. The tests showed that the proposed navigation system can effectually improve accuracy and robustness of navigation. During the navigation drift evaluation of the mimic two-minute GNSS outages, compared to the conventional GNSS/INS (inertial navigation system)/ODO integration, the root mean square (RMS) of the maximum position drift errors during outages in the proposed navigation system were reduced by 62.8%, 72.3%, and 52.1%, along the north, east, and height, respectively. Moreover, the yaw error was reduced by 62.1%. Furthermore, compared to the GNSS/IMU/LiDAR-SLAM integration navigation system, the assistance of the odometer and non-holonomic constraint reduced vertical error by 72.3%. The test in the real tunnel case shows that in weak environmental feature areas where the LiDAR-SLAM can barely work, the assistance of the odometer in the pre-integration is critical and can effectually reduce the positioning drift along the forward direction and maintain the SLAM in the short-term. Therefore, the proposed GNSS/IMU/ODO/LiDAR-SLAM integrated navigation system can effectually fuse the information from multiple sources to maintain the SLAM process and significantly mitigate navigation error, especially in harsh areas where the GNSS signal is severely degraded and environmental features are insufficient for LiDAR-SLAM.

Перспективы развития безэкипажных судов в Российской Федерации

The article considers the actuality of crewless shipping. The development of technical means in the marine shipbuilding industry has been pointed out. The statistical data on accidents at sea are given; as a result of the data analysis, there have been identified the main causes &#x0D; of the accidents: non-compliance with generally accepted methods of controlling a vessel, ignoring the specific hydrometeorological parameters of the navigation and mooring areas, non-compliance with safety and technical operation rules, navigation errors, etc. The human factor has been stated to remain the main and most frequent cause of accidents at sea. The types of accidents at sea are considered in detail (damage to ship devices and mechanisms, ship's hull, loss of life, bulk, explosion, fire, loss of a towed object, winding on a screw, grounding, serious bodily harm, collision, loss of stability, buoyancy, collision with a submerged object). The advantages of using a crewless vessel are substantiated, as well as the prospects associated with the introduction of such vessels: reduction in accident rate due to the exclusion of the human factor, lower negative and harmful effects on the environment, increased reliability of transportation due to changes in the structure &#x0D; of vessels, increased economic efficiency due to the uselessness of crew support, etc. There has been given an example of creating a project for the e-Navigation test area executed by Kronstadt in 2016. The test water area includes all e-Navigation coverage areas, combines 13 ports, training centers, over 300 sea vessels, several ship traffic control systems into a single electronic space. Within the framework of the project, developers introduce and test new equipment, conduct training for the crews. The conclusions have been made about possibility for the Russian Federation of accelerating the introduction of new technologies in the global market of shipping companies, increasing competitiveness and reducing dependence on foreign technologies

Design and Performance Validation of Integrated Navigation System Based on Geometric Range Measurements and GIS Map for Urban Aerial Navigation

This article proposes an efficient integrated navigation algorithm to secure reliable navigation solutions in urban flight environments where satellite navigation is not available. Also, this study investigates a new sensor deployment and filter configuration that can perform real-time navigation onboard small drones by reducing the complexity and computational burden of the conventional point cloud-based pose estimation. The proposed method first derives the geometric relationship between the ranging vector and the known three-dimensional map, where the number of range sensors and deployment structure is refined. Then, we designed the inertial navigation filter structure combining the derived measurement model and evaluated the estimation performance in a realistic urban flight environment. The validity of the proposed algorithm is verified through both error analysis using a simulator with a high-fidelity model and real navigation error analysis from onboard flight test adjacent to urban buildings. In conclusion, this paper presents a distinctive navigation method from the existing point cloud-based approaches and the performance of real-time three-dimensional navigation with a position error of about 1–2 m in satellite unavailability environment.

Collision Risk Analysis and Oil Spill Dispersion Modelling in Lombok Strait

Lombok Strait is one of the water areas that designated for international shipping lanes since it has been adopted as the Indonesia Archipelagic Sea lane (IASL) II in 1998. Foreign-flagged ships passing through the strait from southbound to northbound and vice versa. Along with being an archipelagic sea lane, the strait also occupied by high-density crossing traffic connecting Bali and Lombok islands. This crossing traffic mainly dominated by passenger ferry Ro-Ro and pleasure ships as both Bali and Lombok islands are well known as tourist destinations. Aside from being a tourist destination, several islands around the Lombok Strait are also dedicated to Marine Protected Areas (MPA). There are two areas designated for MPA by the Indonesian government in the vicinity of Lombok Strait; Nusa Penida on the west side of IASL II and Gili Matra on the east side. The traffic condition allows the potential for collisions on ships passing through and crossing the Lombok Strait which is very likely caused by navigation errors, human errors, weather conditions, and other technical problems. This study aims to determine the collision risk analysis in terms of annual frequency of collision and grounding as well as the potential dispersion of oil that occurs in the event of a ship collision near the MPA of Nusa Penida. Based on one-year traffic data and forecasted to 20 years, collision and grounding frequencies analysis was conducted using iWRAP method. The analysis found that annual frequency including head-on, overtaking, crossing, merging, bend, and grounding is 4.73×10-1. In addition to the frequency of collisions, oil spill dispersion simulations were carried out using GNOME under two different conditions wind and sea current directions; wind and sea currents that heading to the Northwest, and Southwest. Given a scenario of collision occurred close to Nusa Penida island involving tanker ship that resulting hull damage and oil spill while the wind and sea current directed to Southwest, simulation resulting that oil spill will disperse and polluting MPA of Nusa Penida.

Improved mobility performance with an artificial vision therapy system using a thermal sensor

Objective. To evaluate the benefit of integrating thermal imaging into an artificial vision therapy system, the Argus II retinal prosthesis, in simplifying a complex scene and improving mobility performance in the presence of other persons. Approach. Four Argus II retinal implant users were evaluated on two tasks: to locate and approach target persons in a booth, and to navigate a hallway while avoiding people. They completed the tasks using both the original Argus II system (the ‘Argus II camera’) and a thermal-integrated Argus II system (the ‘thermal camera’). The safety and efficiency of their navigation were evaluated by their walking speed, navigation errors, and the number of collisions. Main results. Navigation performance was significantly superior when using the thermal camera compared to using the Argus II camera, including 75% smaller angle of deviation (p < 0.001), 48% smaller error of distance (p < 0.05), and 30% fewer collisions (p < 0.05). The thermal camera also brought the additional benefit of allowing the participants to perform the task in the dark as efficiently as in the light. More importantly, these benefits did not come at a cost of reduced walking speed. Significance. Using the thermal camera in the Argus II system, compared to a visible-light camera, could improve the wearers’ navigation performance by helping them better approach or avoid other persons. Adding the thermal camera to future artificial vision therapy systems may complement the visible-light camera and improve the users’ mobility safety and efficiency, enhancing their quality of life.

Tradespace Analysis of GNSS Space Segment Architectures

Global navigation satellite systems (GNSS) provide ubiquitous, continuous, and reliable positioning, navigation, and timing information around the world. However, GNSS space segment design decisions have been based on the precursor Global Positioning System, which was designed in the 1970s. This article revisits those early design decisions in view of major technological advancements and new GNSS environmental threats. The rich tradespace between user navigation error (UNE) performance and constellation deployment costs is explored and conclusions are complemented by sensitivity analysis and association rule mining. This article finds that constellations at an orbit altitude of ~2 earth radii can outperform existing GNSS in terms of cost, robustness, and UNE. These insights should be taken into account when designing future generations of GNSS.

An Autonomous Initial Alignment and Observability Analysis for SINS With Bio-Inspired Polarized Skylight Sensors

A novel autonomous initial alignment for the stationary strapdown inertial navigation system (SINS) with the bio-inspired polarized skylight sensors (PSS) is proposed to improve the precision and convergence speed in this paper. A pair of perpendicularly polarized skylight sensors with six-channels are used to measure and calculate the polarization azimuth angles, which is finally constructed a new polarized measurement error equation. With the SINS error equations, the SINS/PSS integrated navigation error equations are developed to achieve autonomous and fast initial alignment. Two types of observability, geometric observability and stochastic observability, are introduced to evaluate the integrated navigation systems. The geometric observability, which is defined by calculating the rank of the observability matrix, is analysed. It is found that the integrated navigation systems are not completely observable. Further, the degree of observability based on singular value decomposition is also used to examine the observable degree of the SINS/PSS integrated navigation system. The stochastic observability is associated with observability analysis with the estimated precision of the designed filter. The Kalman filter is designed to estimate the unknown state based on the measurements from the inertial measurement unit and PSS. Simulations and experiments demonstrate that the SINS/PSS achieve a rapid initial alignment with higher precision. Compared with the SINS, the vertical misalignment angle accuracy of SINS/PSS is improved by more than 90%, and the time cost is shortened by 60% in the simulation test. For the initial alignment experiment, the vertical misalignment greatly improved the accuracy and shorten the time cost.

Control of quadrotor trajectory tracking with sliding mode control optimized by neural networks

Quadrotor or unmanned helicopter is a mobile robot which often flies in unknown environment to perform special missions. In navigational tasks, the robot is intended to fly autonomously toward a target position by following an optimum trajectory. For a successful navigation, controlled attitude, minimum position and velocity error and obstacles collision avoidance are often considered during trajectory tracking procedure. By considering environmental variabilities and due to the existence of noises, uncertainties and unpredictable factors, it is indispensable to steer and control moving robots using sophisticated autonomous algorithms. In this work, a nonlinear model of four-rotor helicopter is simulated. An optimized terminal sliding mode control is then designed to control trajectory tracking. In order to improve the time indices for sliding mode controller, this controller is modified with neural networks. The idea is to optimize the controller parameters through a network learning process which is based on the control process error. The proposed method is evaluated with simulated and real-world indoor navigation tasks. Trajectories that are tracked by quadrotor are generated by a simultaneous localization and mapping algorithm and refined with an optimization technique. A well-known simultaneous localization and mapping technique (a camera-based extended Kalman filter-simultaneous localization and mapping) is employed to generate maps, and a path planning algorithm (particle swarm optimization) is utilized to optimize a collision-free flight path using the probability-based maps generated by simultaneous localization and mapping. Simulations and experiment are done in unknown but structured indoor environments containing a number of obstacles. The steady state error, the reaching and settle time and the chattering effect are all quantified and assessed. The controlled experimental flight robustness and sensitivity are further verified for noises occurred on vision and data acquisition system. Results indicate suitable performance for the proposed neural network-sliding mode controller. Less error and more stability were achieved comparative to the conventional sliding mode controllers.

Surgical Tracking, Registration, and Navigation Characterization for Image-guided Renal Interventions.

Most image-guided interventions rely on surgical tracking and image/model to patient registration to establish a spatial relationship between the patient and the pre- and intraprocedural images, by using surgical tracking and localization systems. In this work, we characterize the tracking, registration and navigation accuracy using two different surgical localization systems - the NDI Polaris Spectra optical tracking system and the NDI Aurora electromagnetic tracking system - in the context of an image-guided renal intervention, using a 3D printed life-size model of a patient-specific kidney phantom generated from a CT image. Our results reported a 0.05 mm fiducial localization error, 0.70 mm fiducial registration error, and 0.78 mm target registration error, and 0.63 mm overall navigation error using the optical tracking, and 0.12 mm fiducial localization error, 0.78 mm fiducial registration error, 0.93 mm target registration error and 0.89 mm overall navigation error using electromagnetic tracking. Additionally, our study also showed similarity between the overall navigation accuracy using optical (0.63 mm RMS error) or electromagnetic tracking (0.89 mm RMS error) and the overall navigation accuracy achieved using direct visualization of the surgical scene (0.68 mm and 1.06 RMS error respectively), which serves as a baseline control metric.

Four-Way Classification of EEG Responses To Virtual Robot Navigation.

Studies have shown the possibility of using brain signals that are automatically generated while observing a navigation task as feedback for semi-autonomous control of a robot. This allows the robot to learn quasi-optimal routes to intended targets. We have combined the subclassification of two different types of navigational errors, with the subclassification of two different types of correct navigational actions, to create a 4-way classification strategy, providing detailed information about the type of action the robot performed. We used a 2-stage stepwise linear discriminant analysis approach, and tested this using brain signals from 8 and 14 participants observing two robot navigation tasks. Classification results were significantly above the chance level, with mean overall accuracy of 44.3% and 36.0% for the two datasets. As a proof of concept, we have shown that it is possible to perform fine-grained, 4-way classification of robot navigational actions, based on the electroencephalogram responses of participants who only had to observe the task. This study provides the next step towards comprehensive implicit brain-machine communication, and towards an efficient semi-autonomous brain-computer interface.

Simulation reduces navigational errors in cerebral angiography training

BackgroundSimulation-based medical education (SBME) is growing as a powerful aid in delivering proficient skills training in many specialties. Cerebral angiography (CA), a spatially and navigationally challenging endovascular procedure, can benefit from SBME by training targetable skills outside of the Angiosuite. In order to standardize and specify training requirements, navigational challenges and needs have to be identified. Furthermore, to enable successful adoption of these strategies, simulation adoption barriers, such as necessity of supervisory resources, must be reduced. In this study, we assessed the navigational challenges in simulated CA through a self-guided novice training program.MethodsNovice participants (n = 14) received virtual reality (ANGIO Mentor, Simbionix) diagnostic cerebral angiography training and were tested on a right middle cerebral artery aneurysm case over 8 sessions with a reference instructional outline. The navigational trajectories for the guidewire and catheter were analyzed and rates in erroneous vessel access were analyzed. Participants were given a Mental Rotations Test (MRT) and were analyzed based on MRT performance.ResultsAfter 8 sessions, there was a significant (p < 0.05) reduction on navigational error prevalence. The L-SUB and L-CCA saw the biggest drop in erroneous access, whereas the R-ECA, the biggest consumer of error time, saw no changes in access frequency. Individuals with high MRT score performed much better (p < 0.05) than those with low MRT score.ConclusionsThrough self-guided simulation training, we demonstrated the navigational challenges encountered in simulated CA. To establish better assessments and standards in medical training, we can create self-guided training curricula aimed at correcting errors, enabling repetitive practice, and reducing human resource needs.

Autonomous optical navigation of Mars probe aided by one-way Doppler measurements in capture stage

The optical navigation errors of Mars probe in the capture stage depend closely on which targets are selected to be observed in the Mars system. As for this problem, an integrated navigation scheme is proposed wherein the optical observation is aided by one-way Doppler measurements. The errors are then analyzed respectively for the optical observation and one-way Doppler measurements. The real-time calculating scheme which exploits the extended Kalman filter (EKF) framework is designed for the integrated navigation. The simulation tests demonstrate that the errors of optical navigation, which select the Mars moon as the observation target, are relatively smaller than those in the Mars-orientation optical navigation case. On one hand, the integrated navigation errors do not depend on the selecting pattern of optical observation targets. On the other hand, the integrated navigation errors are significantly reduced as compared with those in the optical-alone autonomous navigation mode.

The Role of Virtual Reality in Improving Health Outcomes for Community-Dwelling Older Adults: Systematic Review.

BackgroundVirtual reality (VR) delivered through immersive headsets creates an opportunity to deliver interventions to improve physical, mental, and psychosocial health outcomes. VR app studies with older adults have primarily focused on rehabilitation and physical function including gait, balance, fall prevention, pain management, and cognition. Several systematic reviews have previously been conducted, but much of the extant literature is focused on rehabilitation or other institutional settings, and little is known about the effectiveness of VR apps using immersive headsets to target health outcomes among community-dwelling older adults.ObjectiveThe objective of this review was to evaluate the effectiveness of VR apps delivered using commercially available immersive headsets to improve physical, mental, or psychosocial health outcomes in community-dwelling older adults.MethodsPeer-reviewed publications that included community-dwelling older adults aged ≥60 years residing in residential aged care settings and nursing homes were included. This systematic review was conducted in accordance with the Joanna Briggs Institute (JBI) methodology for systematic reviews of effectiveness evidence. The title of this review was registered with JBI, and the systematic review protocol was registered with the International Prospective Register of Systematic Reviews.ResultsIn total, 7 studies that specifically included community-dwelling older adults were included in this review. VR apps using a head-mounted display led to improvements in a number of health outcomes, including pain management, posture, cognitive functioning specifically related to Alzheimer disease, and a decreased risk of falls. A total of 6 studies reported a statistically significant difference post VR intervention, and 1 study reported an improvement in cognitive function to reduce navigational errors. Only one study reported on the usability and acceptability of the interventions delivered through VR. While one study used a distraction mechanism for pain management, none of the studies used gaming technology to promote enjoyment.ConclusionsInterventions to improve health outcomes through VR have demonstrated potential; however, the ability to synthesize findings by primary outcome for the older adult population is not possible. A number of factors, especially related to frailty, usability, and acceptability, also need to be explored before more substantial recommendations on the effectiveness of VR interventions for older adults can be made.Trial RegistrationPROSPERO CRD42019143504; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=143504

Leveraging spatial uncertainty for online error compensation in EMT

PurposeElectromagnetic tracking (EMT) can potentially complement fluoroscopic navigation, reducing radiation exposure in a hybrid setting. Due to the susceptibility to external distortions, systematic error in EMT needs to be compensated algorithmically. Compensation algorithms for EMT in guidewire procedures are only practical in an online setting.MethodsWe collect positional data and train a symmetric artificial neural network (ANN) architecture for compensating navigation error. The results are evaluated in both online and offline scenarios and are compared to polynomial fits. We assess spatial uncertainty of the compensation proposed by the ANN. Simulations based on real data show how this uncertainty measure can be utilized to improve accuracy and limit radiation exposure in hybrid navigation.ResultsANNs compensate unseen distortions by more than 70%, outperforming polynomial regression. Working on known distortions, ANNs outperform polynomials as well. We empirically demonstrate a linear relationship between tracking accuracy and model uncertainty. The effectiveness of hybrid tracking is shown in a simulation experiment.ConclusionANNs are suitable for EMT error compensation and can generalize across unseen distortions. Model uncertainty needs to be assessed when spatial error compensation algorithms are developed, so that training data collection can be optimized. Finally, we find that error compensation in EMT reduces the need for X-ray images in hybrid navigation.

Robust Stereo Visual Inertial Navigation System Based on Multi-Stage Outlier Removal in Dynamic Environments.

Robotic mapping and odometry are the primary competencies of a navigation system for an autonomous mobile robot. However, the state estimation of the robot typically mixes with a drift over time, and its accuracy is degraded critically when using only proprioceptive sensors in indoor environments. Besides, the accuracy of an ego-motion estimated state is severely diminished in dynamic environments because of the influences of both the dynamic objects and light reflection. To this end, the multi-sensor fusion technique is employed to bound the navigation error by adopting the complementary nature of the Inertial Measurement Unit (IMU) and the bearing information of the camera. In this paper, we propose a robust tightly-coupled Visual-Inertial Navigation System (VINS) based on multi-stage outlier removal using the Multi-State Constraint Kalman Filter (MSCKF) framework. First, an efficient and lightweight VINS algorithm is developed for the robust state estimation of a mobile robot by practicing a stereo camera and an IMU towards dynamic indoor environments. Furthermore, we propose strategies to deal with the impacts of dynamic objects by using multi-stage outlier removal based on the feedback information of estimated states. The proposed VINS is implemented and validated through public datasets. In addition, we develop a sensor system and evaluate the VINS algorithm in the dynamic indoor environment with different scenarios. The experimental results show better performance in terms of robustness and accuracy with low computation complexity as compared to state-of-the-art approaches.

Are safety and performance affected by navigation system display size, environmental illumination, and gender when driving in both urban and rural areas?

Driving with the aid of a navigation system could distract drivers. A high level of distraction influences driver performance and safety, leading to a possible increase in road crashes. The illumination level and size of the GPS display may influence the duration and frequency of a driver’s glances, which in turn may affect driver distraction. In a simulated driving experiment requiring the use of a GPS, the GPS’s display size and illumination level were examined, in light of the driver’s experience and gender, to understand their effects on the performance and safety of young drivers on roads in urban and rural areas. Twenty young subjects, male and female between the ages of 18 and 29 years, participated in this experiment. Driving safety was evaluated by lateral control (number of pavement and lane line crossings), number of crashes, number of near misses, and the total time out of the lane. Driving performance was evaluated by the number of navigational errors, the total time making navigational errors, number of times the speed limit was exceeded and total amount of time speeding. These measures were analyzed using a repeated measures analysis of variance (ANOVA) model. Furthermore, the effects of the GPS display, considering the driving experience, were investigated with a simple linear regression. Findings suggest that driving with a small GPS display in an urban area leads to more navigational errors than driving with a large GPS display. Furthermore, more speed limit violations tend to occur in rural areas in the daytime than at night. Moreover, in urban areas, male drivers tend to have the highest number of crashes during the daytime. Furthermore, in rural areas, males tend to violate the speed limit more often and for longer periods of time during the daytime than at night and more than females do. Additionally, when navigating with a GPS system, young experienced drivers drive safer than inexperience drivers. The findings are of interest to designers and transportation researchers concerned with improving GPSs to enhance driving safety and performance.

Specifying advantages of multi-modal cueing: Quantifying improvements with augmented tactile information

This work examines how tactile cues, encoded with azimuth and distance information, compare with visual and speech cues on performance and mental workload in a target detection task. Two experiments are reported using a simulated environment in which targets were presented at varying azimuth and distance locations. In the first experiment, participants engaged targets both while stationary and while in motion using tactile, visual, or speech cues. A no cueing control was included. In the second multi-modal experiment, participants completed the same task using cue pairings. Performance metrics consisted of hits, misses due to non-detection, misses due to inaccurate engagement, false alarms, response time, navigation errors as well as subjective ratings of mental workload scores were also collected. Results demonstrate the superiority of tactile cues as a means to communicate target location information either as a single modality or when paired with the two other cue types.

The Application of O-arm and Navigation System in Precise Localization of Spinal Cord lesions: a Case Series study

ObjectiveTo study on the clinical efficacy of precise localization of O-arm and navigation system in spinal cord lesions. MethodsFrom Augst 2015 to September 2019, 22 patients with spinal cord lesions were arranged in the group.The intraoperative cross-sectional images were acquired by O-arm image system, which were transferred to the Stealth navigation system, and fused with pre-opreative MRI images. The image fusion was completed by the Medtronic Synergy Cranial software. The fused images were used to locate spinal cord lesions, assisted by the navigation system. The navigation errors were evaluated by measuring the maximum distance between the end of the lesion in MRI and its real position. ResultsThe image fusion were completed in all patients, and we successfully completed the image-guided surgeries of the spinal cord lesions. The time of image processing was between 7 min and 19 min, and the mean value was 15.1 ± 2.2 min. The navigation error was between 0.9 mm and 5.3 mm, the mean value was 1.6 ± 0.9 mm. ConclusionThe application of precise localization of O-arm and navigation system in spinal cord lesions is clinically reliable and feasible.