Navigation Assistance Research Articles

Increased accuracy in component positioning using an image-less robotic arm system in primary total knee arthroplasty: a retrospective study.

Robotic-assisted total knee arthroplasty (RTKA) and navigated total knee arthroplasty (NTKA) have shown improved knee alignment and reduced radiographic outliers. Recent studies have proven that conventional mechanical alignment may not be the optimal goal for every patient. The aim of this study was to compare the accuracy of the planned implant positioning of a novel image-less robotic technique with an established navigated technique (NTKA). The study is a retrospective analysis of prospectively collected data that compared the implant positioning and lower-limb alignment of 86 image-less RTKA with 86 image-less NTKA. Radiographic analysis was performed to evaluate the lower-limb overall alignment, femoral and tibial components positioning in the coronal and sagittal planes. Outliers were evaluated with a cutoff of ± 3°. No difference was noted between the two groups for radiographic outliers within ± 3° from neutral (p = 0.098). The mean hip-knee-ankle angle deviation from target was 1.3° in the RTKA group compared to 1.9° in the NTKA (p < 0.001). Femoral sagittal deviation (femoral component flexion) was smaller in the RTKA group (0.9° vs 1.9°; p < 0.001). Similarly, tibial coronal deviation (0.8° vs 1.5°; p < 0.001) and tibial sagittal deviation (tibial slope) were smaller in the RTKA group compared to the NTKA group (0.9° vs 1.7°; p < 0.001). The RTKA group reported a substantial and significant reduced error from the planned target angles for both tibial and femoral components. No difference in terms of radiographic outliers was noted between navigation and robotic assistance.

Real-World Navigation With Application: Characteristics of Gaze Behavior and Associated Factors in Older Adults.

Advancing age might impair real-world navigation ability. The use of mobile devices by older adults has grown rapidly in recent years. Navigation applications (apps) in mobile devices may facilitate the freedom of outings for older adults. Our aim is to investigate age-related differences in real-world app-based navigation walking in terms of accuracy, efficiency, and gaze behavior; and to explore clinical factors associated with navigation walking in older adults. A total of 20 community-dwelling older adults and 16 young adults completed a route navigation task using a navigation app while recording their gaze behavior. Outcomes were compared in both groups and a general linear regression was used to explore clinical factors associated with app-based navigation walk in older adults. Compared with young participants, older participants had more stops and root errors and less fixation time, smaller amplitude of saccades. Additionally, older adults were more likely to glance at their smartphones while app-based navigation walking. Furthermore, gait speed and the following assessment scores were significantly associated with navigation walking in older adults: Mini-Mental State Examination, Life-Space Assessment, and the short version of the Mobile Device Proficiency Questionnaire. For app-based navigation walks, differences in accuracy and gaze behavior were found to exist with age. Additionally, efficient real-world navigation walks in older adults require the extent of life space and proficiency with mobile devices, along with walking speed and cognitive function. It is possible that age-related functional decline, such as the visual field and shifting attention between mobile devices and the real world, may have influenced the results. The study also suggests the need to understand the level of proficiency with mobile devices so that older adults can continue to go out freely. These findings give the basis for providing older adults with appropriate navigation assistance.

Conversational assistants in academic libraries: enhancing reference services through Bing Chat

Purpose This research aims to explore the integration of Bing Chat, an artificial intelligence (AI)-powered conversational assistant, into academic libraries and its potential impact on reference services. Design/methodology/approach This study analyzes existing literature to investigate the integration of Bing Chat in academic libraries. This research focuses on its features, capabilities and implications for enhancing user experiences and addressing information needs. Findings The findings highlight that Bing Chat’s conversational interface facilitates more dynamic and context-aware reference interactions, fostering user empowerment and personalized learning pathways. The integration of Bing Chat with existing library resources enhances resource discovery, navigational assistance and engagement with visual content. However, challenges related to accuracy, privacy and algorithmic bias require careful consideration. Originality/value This research contributes to the literature by providing an in-depth exploration of Bing Chat’s integration into academic libraries, emphasizing its transformative potential for reference services. This study addresses ethical and social dimensions associated with AI-driven tools in library environments, offering insights into ensuring fairness, privacy and user trust.

BeeAR: Augmented Reality Beeline Navigation for Spatial Knowledge Acquisition

Navigation assistance systems have become integral to our daily routines, helping us to find our way through unfamiliar environments. However, their use may come at a price, as empirical evidence suggests a potentially harmful impact of these systems on our spatial abilities, including the acquisition of spatial knowledge. This could be remedied by giving users more freedom and involving them in the decision-making process. Therefore, we present a navigation system that combines augmented reality and Beeline Navigation (BeeAR). Here, the location of the destination is overlaid with a digital landmark and permanently displayed to the user via a visual, translucent AR display (without a map). Since the digital content is integrated into the real world, no mapping between the device and reality is required, potentially lowering the workload. Making one's own decisions along the route is expected to increase engagement with the environment, leading to increased acquisition of spatial knowledge. We compare BeeAR with findings from a previous study comparing Free Choice Navigation (FCN) and Turn-by-Turn (TBT) navigation conducted along the same routes on the outskirts of Vienna, Austria. Although BeeAR and FCN do not provide users with a map, BeeAR users could better retrace the walked route and remembered more points of interest along the route than FCN users. Participants of all three navigation conditions achieved a high configuration similarity between drawn points of interest and their true locations, albeit only one navigation condition included a map.

Integrating navigation assistance for redirecting freehanded spinal instrumentation: experience and technique

Retrospective review of all spinal fusions > 3 levels involving the thoracolumbar and/or sacroiliac at a single institution, by a single surgeon between 3/12/2020 and 8/13/2021 were reviewed. All screws that were secondarily navigated after identified as misdirected on intraoperative CT scan were included. Neuromonitoring reports were culled for mA threshold to triggered EMG response for all redirected screws. Intraoperative, post-de novo screw placement images (fluoroscopy scout and intraoperative CT) and post-redirection intraoperative scoliosis films and post-operative scoliosis films were independently reviewed by a senior neuroradiologist. Fifty redirected screws in the thoracic, lumbar, sacral, and ilium were identified as misdirected and redirected via navigation. The new trajectory of all screws was confirmed satisfactory by independent review between a senior neuroradiologist and neurosurgeon. Four screws could not be verified by post-operative imaging (4/50, 8%). All triggered EMG stimulated > 15 mA. No screws required return to the operating room for revision. No patients experienced a post-operative deficit. Redirection of misdirected thoracolumbar and sacroiliac screws can be performed using intraoperative CT and navigation as a means to detect and directly visualize appropriate placement.

Laparoscopic right hemi-hepatectomy plus total caudate lobectomy for perihilar cholangiocarcinoma via anterior approach with augmented reality navigation: a feasibility study.

Right hemi-hepatectomy plus total caudate lobectomy is the appropriate procedure for type IIIa or partial type II pCCA. However, the laparoscopic implementation of this procedure remains technically challenging, especially hilar vascular dissection and en bloc resection of the total caudate lobe. Augmented reality navigation can provide intraoperative navigation to enhance visualization of invisible hilar blood vessels and guide the parenchymal transection plane. Eleven patients who underwent laparoscopic right hemi-hepatectomy plus total caudate lobectomy from January 2021 to January 2023 were enrolled in this study. Augmented reality navigation technology and the anterior approach were utilized in this operation. Routine operative and short-term postoperative outcomes were assessed to evaluate the feasibility of the novel navigation method in this operation. Right hemi-hepatectomy plus total caudate lobectomy was successfully performed in all 11 enrolled patients. Among the 11 patients, the mean operation time was 454.5 ± 25.0min and the mean estimated blood loss was 209.1 ± 56.1ml. Negative surgical margins were achieved in all patients. The postoperative course of all the patients was uneventful, and the mean length of postoperative hospital stay was 10.5 ± 1.2days. Laparoscopic right hemi-hepatectomy plus total caudate lobectomy via the anterior approach may be feasible and safe for pCCA with the assistance of augmented reality navigation.

Assisted navigation for digital architectural walkthroughs in Natural User Interface-based installations

The architectural experience of visiting a virtual building and exploring its contents requires tools to provide visitors with accessible and pleasurable ways to conduct their stroll and facilitate the contemplation and enjoyment of the contents displayed. Natural user interfaces (NUI) are effective and engaging tools for interacting with digital content. In this paper, the authors combine their previous work in the research lines of natural user interfaces and assisted navigation, putting them together on a UX test scenario and studying their combined effect. The testbed consisted of an installation controlled using a depth camera for NUI interaction and applying an attractor-based approach of assisted navigation. The UX experiment consisted of five stages, with three test sets of increasing complexity. The system monitored and recorded the users’ movements on each test during the experiment to extract quantitative data. After each task, users filled out specific questionnaires that provided qualitative information. The study also evaluates the influence of users’ previous expertise on 3D video games in their performance taking the test. The results indicate the benefits of combining both technologies and how they enhance the virtual visit experience. Furthermore, the combined use of natural interaction and assisted navigation facilitates universal access to installations of this kind, frequently found in museums and exhibits, independently of previous user expertise in interactive 3D environments, such as video games.

A Novel Geospatial Assistive Navigation Technology for Seamless Multimodal Mobility of Wheelchair Users.

Mobility is fundamental for social participation of people with disabilities. Unfortunately, traditional design of urban environments, including infrastructure and services are developed based largely on a standard perception of an independent, fully functional citizen without disability which limits the mobility social participation of PWD. This paper presents the design and development of a novel geospatial assistive navigation technology to support multimodal mobility of people with disabilities, especially those using manual wheelchair in urban areas.

BOSS: Bones, organs and skin shape model

A virtual anatomical model of a patient can be a valuable tool for enhancing clinical tasks such as workflow automation, patient-specific X-ray dose optimization, markerless tracking, positioning, and navigation assistance in image-guided interventions. For these tasks, it is highly desirable that the patient’s surface and internal organs are of high quality for any pose and shape estimate. At present, the majority of statistical shape models (SSMs) are restricted to a small number of organs or bones or do not adequately represent the general population. To address this, we propose a deformable human shape and pose model that combines skin, internal organs, and bones, learned from CT images. By modeling the statistical variations in a pose-normalized space using probabilistic PCA while also preserving joint kinematics, our approach offers a holistic representation of the body that can be beneficial for automation in various medical applications. In an interventional setup, our model could, for example, facilitate automatic system/patient positioning, organ-specific iso-centering, automated collimation or collision prediction. We assessed our model’s performance on a registered dataset, utilizing the unified shape space, and noted an average error of 3.6 mm for bones and 8.8 mm for organs. By utilizing solely skin surface data or patient metadata like height and weight, we find that the overall combined error for bone-organ measurement is 8.68 mm and 8.11 mm, respectively. To further verify our findings, we conducted additional tests on publicly available datasets with multi-part segmentations, which confirmed the effectiveness of our model. In the diverse TotalSegmentator dataset, the errors for bones and organs are observed to be 5.10mm and 8.72mm, respectively. Our work shows that anatomically parameterized statistical shape models can be created accurately and in a computationally efficient manner. The proposed approach enables the construction of shape models that can be directly integrated into to various medical applications.

Vision Transformer Customized for Environment Detection and Collision Prediction to Assist the Visually Impaired.

This paper presents a system that utilizes vision transformers and multimodal feedback modules to facilitate navigation and collision avoidance for the visually impaired. By implementing vision transformers, the system achieves accurate object detection, enabling the real-time identification of objects in front of the user. Semantic segmentation and the algorithms developed in this work provide a means to generate a trajectory vector of all identified objects from the vision transformer and to detect objects that are likely to intersect with the user's walking path. Audio and vibrotactile feedback modules are integrated to convey collision warning through multimodal feedback. The dataset used to create the model was captured from both indoor and outdoor settings under different weather conditions at different times across multiple days, resulting in 27,867 photos consisting of 24 different classes. Classification results showed good performance (95% accuracy), supporting the efficacy and reliability of the proposed model. The design and control methods of the multimodal feedback modules for collision warning are also presented, while the experimental validation concerning their usability and efficiency stands as an upcoming endeavor. The demonstrated performance of the vision transformer and the presented algorithms in conjunction with the multimodal feedback modules show promising prospects of its feasibility and applicability for the navigation assistance of individuals with vision impairment.

Does Computer Navigation or Robotic Assistance Affect the Risk of Periprosthetic Joint Infection in Primary Total Knee Arthroplasty? A Propensity Score-Matched Cohort Analysis

BackgroundThe use of technology during total knee arthroplasty (TKA) has been associated with more accurate component position and less blood loss. Yet to date, the risk of developing prosthetic joint infection (PJI) associated with computer navigation (CN) or robotic assistance (RA) has not been thoroughly evaluated. This study used propensity score-matching (PSM) in a large cohort of primary TKA patients to compare the rate of PJI following conventional TKA (TKA) versus CN-TKA and RA-TKA. MethodsWe retrospectively reviewed 13,015 knees in 11,727 patients who underwent primary TKA at a single institution from 2018 to 2021. The cohort was stratified into TKA, CN-TKA, and RA-TKA groups. 1:1 PSM was applied to 11,834 patients. Propensity score-matching was performed using logistic regression accounting for age, sex, body mass index, Charlson Comorbidity Index (CCI) score, CCI components, and smoking status. Univariate and multivariable analyses were performed to evaluate differences in surgical time and PJI rate. ResultsSignificantly longer median operating times were noted in the RA-TKA group (14 minutes) compared to TKA (P < .001). The PJI rates among matched cohorts were similar among RA-TKA (0.3%), CN-TKA (0.3%), and conventional TKA (0.5%). Multivariable logistic regressions demonstrated that the use of robotic assistance (odds ratio (OR) = 0.5, P = .423) or computer navigation (OR = 0.61, P = .128) was not associated with increased risk of PJI when compared to conventional TKA. ConclusionsUse of computer navigation and robotic assistance during primary TKA are associated with longer surgical times, but no difference in PJI frequency within 90 days of surgery.

Comparative Analysis of Regulatory Frameworks Implementation on The Vessel Traffic Service Surabaya to Increase Maritime Regional Safety and Security in The Surabaya West Access Channel

The Surabaya West Access Channel has an average of ship that sails across Madura straits from 2008 - 2013 is 20,582 per year and there is a total of 47 accidents recorded from 2015 – 2018 and piracy crimes occurred for 13 cases from 2013 – 2018. The Vessel Traffic Service (VTS) is established to reduce these risks by performing the function of providing information service, navigational assistance, and traffic organizational service. This study aims to list the requirements of IMO A.857 and IALA V – 128 for the VTS then conduct a comparative analysis and score the level of implementation of regulations in the VTS Surabaya. The final result of scoring is the implementation of rules from IMO A.857 which gains 81%, which is higher than the implementation of IALA V–128 which only gains 67% of compliance. Several recommendations were made directed to the policymakers to elevate the efficiency of work of the VTS Surabaya.

2D/3D Deep Registration Along Trajectories With Spatiotemporal Context: Application to Prostate Biopsy Navigation.

The accuracy of biopsy targeting is a major issue for prostate cancer diagnosis and therapy. However, navigation to biopsy targets remains challenging due to the limitations of transrectal ultrasound (TRUS) guidance added to prostate motion issues. This article describes a rigid 2D/3D deep registration method, which provides a continuous tracking of the biopsy location w.r.t the prostate for enhanced navigation. A spatiotemporal registration network (SpT-Net) is proposed to localize the live 2D US image relatively to a previously aquired US reference volume. The temporal context relies on prior trajectory information based on previous registration results and probe tracking. Different forms of spatial context were compared through inputs (local, partial or global) or using an additional spatial penalty term. The proposed 3D CNN architecture with all combinations of spatial and temporal context was evaluated in an ablation study. For providing a realistic clinical validation, a cumulative error was computed through series of registrations along trajectories, simulating a complete clinical navigation procedure. We also proposed two dataset generation processes with increasing levels of registration complexity and clinical realism. The experiments show that a model using local spatial information combined with temporal information performs better than more complex spatiotemporal combination. The best proposed model demonstrates robust real-time 2D/3D US cumulated registration performance on trajectories. Those results respect clinical requirements, application feasibility, and they outperform similar state-of-the-art methods. Our approach seems promising for clinical prostate biopsy navigation assistance or other US image-guided procedure.

DRISHTI: Visual Navigation Assistant for Visually Impaired

In today’s society, where independent living is becoming increasingly important, it can be extremely constricting for those who are blind. Blind and visually impaired (BVI) people face challenges because they need manual support to prompt information about their environment. In this work, we took our first step towards developing an affordable and high-performing eye wearable assistive device, DRISHTI, to provide visual navigation assistance for BVI people. This system comprises a camera module, ESP32 processor, Bluetooth module, smartphone and speakers. Using artificial intelligence, this system is proposed to detect and understand the nature of the users’ path and obstacles ahead of the user in that path and then inform BVI users about it via audio output to enable them to acquire directions by themselves on their journey. This first step discussed in this paper involves establishing a proof-of-concept of achieving the right balance of affordability and performance by testing an initial software integration of a currency detection algorithm on a low-cost embedded arrangement. This work will lay the foundation for our upcoming works toward achieving the goal of assisting the maximum of BVI people around the globe in moving independently.

Real-Time 3D Object Detection, Recognition and Presentation Using a Mobile Device for Assistive Navigation

Real-Time 3D Object Detection, Recognition and Presentation Using a Mobile Device for Assistive Navigation

An integrated region proposal and spatial information guided convolution network based object recognition for visually impaired persons’ indoor assistive navigation

ABSTRACT Multiple view object recognition is challenged by the impact of various view-angles on intra-class relationships. Visually impaired individuals can benefit from accurate navigation services with a navigation system that enables them to avoid obstacles to their destination. An indoor object detection framework called RSIGConv, based on an integrated Region proposal and Spatial Information Guided Convolution network, is proposed in this paper for visually impaired people. To obtain mutual complementarity (MC) features, the RGB and HHA feature maps are fused using the Information Translation Module (ITM). The hyper-parameters are optimized using the Bayesian optimization Algorithm (BOA) to reduce train error and the gap between train error and validation error. The proposed object detection framework is evaluated using the publicly available SUN RGB-D dataset and compared with previous prediction models. The simulation outputs demonstrate that the model overtakes existing approaches, achieving an accuracy of 97.77%.

Carie - The Space Pet

Robotics is the fusion of science, engineering, and technology that creates robots, or machines, that mimic or take the place of human beings in performing tasks. Multiple sorts of robotics are possible. It is also possible to use robotics for space research. Physically and mentally challenging situations might arise for humans during space travel. The use of technology can help us to some extent get past the mental challenges as the physical challenges are unavoidable. We employ robotics in order to get over mental obstacles. To reach the objective of promoting astronaut wellness in space, we combine robotics with a number of other technologies. This project is aimed at developing an autonomous robot companion for astronauts during space missions. The objective is to provide real time monitoring, forecasting capability and navigation assistance in order to ensure the safety, efficiency and well-being of astronauts. The robot companion is capable of monitoring astronaut's health conditions and detecting potential problems at an early stage by integrating high resolution sensors and sophisticated algorithms. The robot aims to improve the overall experience and performance of astronauts in space by applying predictive analytical tools and advanced navigation systems.

Trails, rails, and over-reliance: How navigation assistance affects route-finding and spatial learning in virtual environments

Many novices struggle with navigation in 3D virtual environments — they frequently get lost and are unable to find objects and locations. In some virtual environments, novices are provided with navigation assistance (e.g., mini-maps, directional markers, or glowing trails) that help them move around in the world. However, it is possible that providing navigation assistance could lead to over-reliance, where the novice’s dependence on the assist means that they never develop a mental model of the environment that would allow them to navigate on their own. To investigate both the benefits and potential risks of navigation assistance in virtual environments, we carried out two online studies in which participants carried out route-finding tasks with different types of navigation assistance. Participants completed training trials, in which they practised a set of routes with the assist, and transfer trials, in which they had to navigate without the assist. The studies focus on two questions: whether assistance improves performance and user experience when it is present, and whether assistance leads to over-reliance and a drop in performance when the assist is removed. For the first question, both studies found that navigation assistance substantially improved performance and subjective experience while it was present — clearly showing that assistance can improve virtual environments for novices. For the second question, we found mixed evidence regarding the problem of over-reliance: the first study showed no performance differences between the highest and lowest levels of navigation assistance when the assist was turned off; the second study showed that there was a performance reduction when the assist was removed, but that the size of the reduction was much smaller than the improvement provided during training. We found that even when the navigation assist was extreme (e.g., pressing a button to be automatically taken in the correct direction), participants were still able to navigate the trained routes, suggesting that incidental learning does successfully occur in virtual environments. Our studies suggest that designers of virtual environments should strongly consider providing navigation assistance: assists can improve a novice user’s performance and experience by reducing navigation problems, and the risks of over-reliance appear to be small in comparison to the benefits for inexperienced users.

The use of computer navigation in reverse shoulder arthroplasty revision: a case report.

Revision shoulder surgery is always a challenge, especially in the management of periprosthetic joint infection. Staged surgery with antibiotic-loaded cement spacer, seems to yield satisfactory and encouraging results. New technologies such as computer navigation are additional tools that could aid surgeons in particular conditions where the native anatomy is distorted. This study presents the unique experience of revision shoulder surgery with computer navigation assistance. Benefits related to this approach could lead to better prosthesis longevity and survivorship.

Turn Left Turn Right - Delving type and modality of instructions in navigation assistant systems for people with visual impairments

Receiving navigation directions and relevant information through appropriate channels is crucial for individuals with visual impairments when they use navigation assistant systems. Various navigation assistant systems have implemented diverse methods and modalities to provide navigation instructions to users. Moreover, several studies have examined the preferences of individuals with visual impairments regarding modalities. These studies have primarily relied on surveys or interviews to report their findings. In this study, we extensively investigated the type of navigation information individuals with visual impairments would prefer to receive. To achieve this, we employed a mixed-method design comprising an experiment, a questionnaire, and interviews conducted with participants with visual impairments and individuals with 20/20 vision who were blindfolded. We tested unimodal instruction modes (audio only) and multimodal instruction modes (audio and vibration), along with two types of audio instructions: short and descriptive. To evaluate the participants’ navigation performance, we measured the time taken and errors made during navigation using different instruction types and modes. The findings of this study suggest that the instruction mode does not have any significant effect on the time taken or errors made to complete the trials. Additionally, no evidence was found to support the preference for descriptive instructions over short instructions among the participants. Furthermore, the study did not find evidence to suggest that participants prefer receiving detailed instructions about the environment and obstacles during navigation. It became evident that participants had varying preferences for instruction modes, highlighting the importance of customized functionalities in navigation assistant systems. Moreover, our study validated that participants with visual impairments spent less time and made fewer errors during navigation compared to blindfolded participants with 20/20 vision. We believe that the results of this study will contribute to expanding the understanding of user preferences regarding the type and modality of instructions in the domain of assistive navigation technology.