Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
16
datasets available to search
ShareScore release 0.7.1
Dataset results
16 results for “Human Navigation”
Multitask Human Navigation in VR with Motion Tracking
<p>Data from human subjects in virtual reality performing some combination of collecting targets, avoiding obstacles, and following a path. Raw data has been parsed into 300 ms samples for use in machine learning algorithms. The data includes object positions in the virtual environment, human position tracking, and task instructions. </p> <p> </p>
Bilateral Human-Robot Control for Semi-Autonomous UAV Navigation
<p><strong>This video demonstrates the work towards a novel control architecture for UAV navigation. In general, UAVs are not easy to operate and skilled pilots are required for a good performance in manual flight. However, currently it is impossible to capture every possible situation an UAV could encounter in the autonomous control. To avoid overly complicated control, a semi-autonomous control approach can be used, so the drone is partly autonomously and partly manually piloted. The novelty of the approach presented here is in the way this semi-autonomy is defined. </strong></p> <p><strong>As the UAV regularly operates autonomously, it is not desirable to switch to manual control in dangerous procedures. Instead, a more supervisory method of control can be applied in which the UAV is always controlled by the onboard computer, but the boundaries of control are controlled by the operator. Whenever a situation requires bigger risks, the operator is informed requested by the drone for help, which he\she can offer by softening certain boundaries of the UAV.</strong></p> <p><strong>This video demonstrates the concept.</strong></p>
Navigated ultrasound bronchoscopy with integrated positron emission tomography - A human feasibility study
Open the record for dataset details and reuse information.
Images from Newspaper Navigator predicted as maps, with human corrected labels
<p>The Dataset contains images derived from the Newspaper Navigator (news-navigator.labs.loc.gov/), a dataset of images drawn from the Library of Congress Chronicling America collection (chroniclingamerica.loc.gov/). </p> <blockquote> <p>[The Newspaper Navigator dataset] consists of extracted visual content for 16,358,041 historic newspaper pages in <em>Chronicling America</em>. The visual content was identified using an object detection model trained on annotations of World War 1-era Chronicling America pages, including annotations made by volunteers as part of the <a href="https://labs.loc.gov/work/experiments/beyond-words/">Beyond Words</a> crowdsourcing project.</p> <p>source:<a href="https://news-navigator.labs.loc.gov/"> https://news-navigator.labs.loc.gov/</a></p> </blockquote> <p>One of these categories is 'maps'. In the original training data for Newspaper Navigator, there were relatively few labelled examples of maps. The predictions for maps have an <a href="https://github.com/LibraryOfCongress/newspaper-navigator">Average Precision of 69.5%, and 34 images in the validation data</a>.</p> <p>This dataset contains a sample of these images which have been predicted as 'maps'. It also includes additional labels which indicate whether the predicted map image is a 'map' or 'not a map'. </p> <p>The data is organised as follows:</p> <ul> <li>The images themselves can be found in 'newspaper_maps.zip' </li> <li>`2020_30_10_13_19_228_sample.json` contains metadata about each image drawn from the Newspaper Navigator Dataset.</li> <li>map_labels.csv contains the labels for the images as a CSV file </li> </ul>
Navigation Test in Simulated Environment Rosbag. Human obstacle detection.
<p>This repository contains rosbags (ROS 2 Humble) extracted from a navigation test realized in a simulated environment (Amazon Hospital map) with an RB1 robot. The test consist of a navigation form one point to another with a human obstacle avoidance.</p> <p> </p> <p>This research is part of the project TESCAC, financed by “European Union NextGeneration-EU, the Recovery Plan, Transformation and Resilience, through INCIBE".</p>
Activation of Human Visual Area V6 during Egocentric Navigation with and without visual Experience
<p>V6 is a retinotopic area located in the dorsal visual stream that integrates eye movements with retinal and visuo-motor signals. Despite the known role of V6 in visual motion, it is unknown whether it is involved in navigation and how sensory experiences shape its functional properties. We explored the involvement of V6 in egocentric navigation in sighted and in congenitally blind (CB) participants navigating via an in-house distance-to-sound sensory substitution device (SSD), the EyeCane. We performed two fMRI experiments on two independent datasets. In the first experiment, CB and sighted participants navigated the same mazes. The sighted performed the mazes via vision, while the CB via audition. The CB performed the mazes before and after a training session using the EyeCane SSD. In a second experiment a group of sighted people performed a motor topography task. Our results show that right V6 (rhV6) is selectively involved in egocentric navigation independently of the sensory modality used. Indeed, after training, rhV6 of CB is selectively recruited for auditory navigation, similar to rhV6 in the sighted. Moreover, we found activation for body movement in area V6, that can putatively contribute to its involvement in egocentric navigation. Taken together, our findings suggest that area rhV6 is a unique hub that transforms spatially relevant sensory information into an egocentric representation for navigation. While vision is clearly the dominant modality, rhV6 is in fact a supramodal area that can develop its selectivity for navigation in the absence of visual experience.</p>
The Feasibility of Low Dose Chest CT for Virtual Bronchoscopy Navigation - Human Study.
ClinicalTrials.gov study NCT04230317. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: A multimodal image guiding system for Navigated Ultrasound Bronchoscopy (EBUS): a human feasibility study
Background: Endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) is the endoscopic method of choice for confirming lung cancer metastasis to mediastinal lymph nodes. Precision is crucial for correct staging and clinical decision-making. Navigation and multimodal imaging can potentially improve EBUS-TBNA efficiency. Aims: To demonstrate the feasibility of a multimodal image guiding system using electromagnetic navigation for ultrasound bronchoschopy in humans. Methods: Four patients referred for lung cancer diagnosis and staging with EBUS-TBNA were enrolled in the study. Target lymph nodes were predefined from the preoperative computed tomography (CT) images. A prototype convex probe ultrasound bronchoscope with an attached sensor for position tracking was used for EBUS-TBNA. Electromagnetic tracking of the ultrasound bronchoscope and ultrasound images allowed fusion of preoperative CT and intraoperative ultrasound in the navigation software. Navigated EBUS-TBNA was used to guide target lymph node localization and sampling. Navigation system accuracy was calculated, measured by the deviation between lymph node position in ultrasound and CT in three planes. Procedure time, diagnostic yield and adverse events were recorded. Results: Preoperative CT and real-time ultrasound images were successfully fused and displayed in the navigation software during the procedures. Overall navigation accuracy (11 measurements) was 10.0 ± 3.8 mm, maximum 17.6 mm, minimum 4.5 mm. An adequate sample was obtained in 6/6 (100%) of targeted lymph nodes. No adverse events were registered. Conclusions: Electromagnetic navigated EBUS-TBNA was feasible, safe and easy in this human pilot study. The clinical usefulness was clearly demonstrated. Fusion of real-time ultrasound, preoperative CT and electromagnetic navigational bronchoscopy provided a controlled guiding to level of target, intraoperative overview and procedure documentation.
Data from: A multimodal image guiding system for Navigated Ultrasound Bronchoscopy (EBUS): a human feasibility study
Open the record for dataset details and reuse information.
Navigating human-sloth bear encounters and attacks in Nepal's unprotected forests
<p><span>Human-sloth bear conflict</span><span> is common throughout most areas where sloth bears co-occur with humans. Altercations are more prevalent in multi-use forest landscapes outside protected areas (PAs). Sloth bears are among the key species linked to human-wildlife conflicts in Nepal's southern region, but comprehensive information to guide safety and mitigation efforts remain scarce. We collected questionnaire-based interview data on sloth bear encounters and attacks, available from 1990–2021, around the Trijuga forest, an important sloth bear habitat outside Nepal's PAs. The data were analyzed using descriptive statistics, chi-square tests, and regression analysis. Within this</span> <span>time period, 66 human-sloth bear encounters involving 69 human individuals were recorded, with an annual average of 2.06 (SD = 1.48) encounters and 1.75 (SD = 1.34) attacks. Encounters primarily involved working-age men (25–55 years old), whose primary occupation was farming and who frequented the forest regularly. They typically occurred between 0900 and 1500, inside forests, and in habitats with poor land cover visibility. </span><span>Fifty-six encounters resulted in attacks by bears that injured 59 people, with a fatality rate of 8.47%. Victims of bear attacks frequently had serious injuries, especially to the head and neck areas of the body. Serious injuries were more likely to occur to lone individuals than to people who were in groups of two or more. We suggest the identification of conflict-risk habitats through a participatory mapping approach and outreach programs for local communities to enhance effective human-sloth bear conflict management in Nepal’s unprotected forests. </span></p>
Data and code for "Human neural dynamics of real-world and imagined navigation"
<ul> <li>Please download the zip file</li> <li>Unzip it on your computer</li> <li>Run the plot_FigureX.m scripts in Matlab</li> <li>The scripts generate the panels for the manuscript's figures</li> <li>Figure panels are saved in subfolders for your review</li> </ul>
Neural Correlates of Real World Spatial Navigation in Humans
ClinicalTrials.gov study NCT04874220. IPD Sharing: YES. Countries: 1. Publications: 0.
First-in-human Integrated Endoscopic Ultrasound (EUS) Navigation System Clinical Study
ClinicalTrials.gov study NCT06798545. IPD Sharing: NO. Countries: 1. Publications: 0.
Navigation and Free Recall in Chronically Implanted Humans
ClinicalTrials.gov study NCT02781129. IPD Sharing: NO. Countries: 1. Publications: 0.
Human Factors Study of Ultrasound Navigation Software for Cardiac Imaging
ClinicalTrials.gov study NCT05660044. IPD Sharing: Not stated. Countries: 1. Publications: 0.
First-in-human Navigation Endoscopic Ultrasound (EUS) System Clinical Study
ClinicalTrials.gov study NCT05515705. IPD Sharing: NO. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.