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126 results for “virtual environment”
Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 4. Iteration of the 3D modeling of the virtual faculty building (3D modeling by Marius Hodea)
<p>For our research, several iterations and methods were employed for the 3D design of an online campus. Different virtual models of a faculty building (see Figures 4,5) were designed and finally a virtual model of a 3D campus comprising a simplified 3-story faculty building (Figure 6) was created. The objective was the optimization of the 3D model and the demonstration of the desired functionalities. For these purposes two 3D modeling and post-processing software were used, i.e. 3DSMax and Trimble Sketchup. The model of the building resulted in 5962 vertices and 4528 faces. The textures and illumination were applied using OpenSim’s in-world tools. Furniture objects (tables, chair, computer monitors) were taken from the Google 3D Warehouse, distributed and shared under Trimble General Model License.</p>
Database of movement behavior and EEG in virtual audiovisual everyday-life environments for hearing aid research
<p>This database contains movement behavior (head, eye, torso) and EEG signals of 21 young normal-hearing (11 male, 11 female, mean age 25 +/- 3.6 years) and 19 elderly normal-hearing subjects (9 male, 12 female, mean age 69 +/- 5.4 years) measured in virtual audiovisual listening environments in the laboratory. The virtual audiovisual environments that were used are: a living room, a lecture hall, a cafeteria, a street and a train station. The video and audio material for the environments is also available (see Related identifiers). The methods and an analysis of the movement behavior are described in Hendrikse et al. (2019). The supplementary materials to this paper that are published here include plots of the gaze trajectories of the subjects in all environments, plotted separately for the young and elderly subjects so that they can be compared, and histograms of the head-, eye- and torso-rotation for the environments that were not included in the paper.</p>
An Exploratory Study on the Effect of Virtual Environments on Cognitive Performances and Psychophysiological Responses
<p>This is the dataset of the following study: </p> <p>Frigione, I., Massetti, G., Girondini, M., Etzi, R., Scurati, G. W., Ferrise, F., Chirico, A., Gaggioli, A., & Gallace, A. (2022). An Exploratory Study on the Effect of Virtual Environments on Cognitive Performances and Psychophysiological Responses. <em>Cyberpsychology, behavior and social networking</em>, <em>25</em>(10), 666–671. https://doi.org/10.1089/cyber.2021.0162</p> <p>Abstract: Research shows that reduced exposure to natural contexts is associated with an increase in psychophysical disorders. Recent evidence suggests that even a brief experience in natural scenarios can positively affect people's health and well-being. However, natural contexts are not always easily accessible. This study investigates the effects of natural and indoor virtual environments (VREs) on psychophysiological and cognitive responses. Following a within-subject design, 34 healthy participants were exposed to two VREs (i.e., a forest and a living room) in a counterbalanced order through a head-mounted display (Oculus Rift). Participants were asked to explore the scenarios and execute a modified version of the Paced Auditory Serial Addition Test. Physiological parameters (heart rate, skin conductance level [SCL], and respiration rate) were recorded during the whole session. After the exposure to VREs, participants filled a set of visual analog scales to rate their subjective experience of presence, relaxation, and stress. Participants reported a higher perceived sense of relaxation in the virtual forest. Moreover, their SCLs were significantly higher in this environment, showing that the forest elicited higher physiological arousal than the living room. Furthermore, their SCLs were significantly higher during the attentional task in the virtual living room. The results suggest that a natural virtual environment can make people feel more relaxed and physiologically engaged than an indoor scenario. The latter instead can be linked to a performing venue, as reported for real contexts. However, these changes were not related to modulations of attentional performance.</p>
Dataset and figures for "Sex in a virtual reality: experimental evidence for sexual isolation due to variation in perception of the environment"
<p>We quantified the strength of assortative mating when variation in the perception of the environment was manipulated experimentally. We manipulated the olfactory neurons of two groups of <em>Drosophila melanogaster </em>which changed their perception of their environment. In response to light (invisible to the flies), one group was designed to smell food (a positive stimulus), while the other group was designed to smell a dangerously high concentration of CO<sub>2</sub> (a negative stimulus). We combined both groups of flies, exposed them to a lit habitat and another habitat that was not, and allowed them to choose between these. We then measured the degree of assortative mating between the two types of flies due to any spatial population structure induced by the flies themselves. To control for any assortative mating due to other reasons, we also measured assortative mating when the heterogeneity of the environment could not be perceived by the flies, and when the environment was actually homogeneous.</p>
Context-dependent memory recall in HMD-based immersive virtual environments
<p>Data represent result of an original VR-based experimental research, which studied human memory recollection in different visual environments. 92 students of psychology using head-mounted VR displays were introduced into a computer-generated virtual environment and asked to memorize presented lists of words. Afterwards, the number of accurate and false memory recollections were measured when participants were placed in the same, respectively different virtual environment. </p> <p> </p>
Bilateral hearing impaired children assessment of horizontal auditory localization accuracy in a virtual visual environment with free head movement
<p>Twenty-two hearing-impaired children (13 males and 9 females, mean age: 10.45 years, standard deviation 3.13 years) participated in an auditory localization experiment in a virtual visual environment. We investigated the contribution of head movements to localization along the interaural plane in absence of motor constraints and visual cues on a virtual scene, experienced by individuals wearing a head-mounted display while listening to stimuli coming from a circular loudspeaker array. Each session included multiple test conditions. In each condition, the stimulus was presented from loudspeaker positions that were randomly balanced across a sequence of 13 x 5 = 65 trials. Each participant performed the task first with both devices turned on ("On-On"), then with one device (either the left or right one) turned on and one off ("On-Off"), and finally with both devices turned off ("Off-Off"). The On-On condition was presented first during each test session because it provided an everyday listening context participants were accustomed to, and consequently confident with. The third condition was omitted if a patient's pure tone average threshold was above the stimulus level used for the test in the frequency range [0.5-4] kHz. Depending on this threshold, nine Bi HA listeners attended also the Off-Off condition. Two Bi HA listeners were unable to attend the On-Off test condition either, since their session had to be stopped as early as they reported annoyance or fatigue to the experimenter. Children were affected by non-syndromic hearing loss ("GEN NO SDR") in 8 cases (6 GJB2 gene mutations, 2 other gene mutations), syndromic hearing loss ("SDR") in 4 (2 Usher syndromes, 1 chromosomal instability, 1 Waardenburg syndrome), and 1 enlarged vestibular aqueduct (inner ear malformation, "IEM"). Other causes of hearing loss ("Other") were congenital cytomegalovirus infection in 2 cases, chemotherapy with platinum derivatives for neuroblastoma in 2, preterm delivery in 1, and prolonged neonatal intensive care unit stay in 1 case. The cause was not identified ("ND") in 3 cases. All participants were right-handed and had no diagnosis of motor impairment. Reported are: the participant's anonymous id ("Participant"), the age ("Age"), the cause of hearing impairment ("MacroCause"), the years of experience with each device ("Experience DX", "Experience SX"), the left and right pure-tone individual hearing thresholds at 500 Hz, 1000 Hz, 2000 Hz, and 4000 Hz, without and with devices ("Threshold w/o 500 DX" is the right threshold at 500 Hz without devices, and the others are named accordingly), the group ("Group", an example is "Bi CI On-Off" identifying the group of listeners with two cochlear implants, one turned on and the other turned off, and the others are named accordingly), the test condition ("Condition", an example is "NOICSX_ICDX", identifying the listening condition with the left cochlear implant turned off and the right cochlear implant turned on, and the others are named accordingly), the target ("Target", angle in sexagesimal degrees), the signed error ("Signed_error", the difference between the target angle and the pointed angle in sexagesimal degrees), the unsigned error ("Unsigned_error", the absolute difference between the target angle and the pointed angle in sexagesimal degrees), the difference between the target and head orientation angle in the moment when the target was hit ("Head_rotation", in sexagesimal degrees), the head covered distance during a single trial ("Head_distance", in meters). Here are presented only sessions including the complete set of 65 trials, except seven sessions attended by Bi-CI listeners, each missing one trial (six in the On-Off condition and one in the On-On condition) that was not recorded due to a technical problem.</p>
Chalara: Ash Die-back Virtual Woodland Environment
<p>Chalara dieback of ash (Fraxinus excelsior) is a disease of ash trees caused by the fungus Chalara fraxinea. The disease causes leaf loss and crown dieback, usually leading to tree death. First found in the UK in February 2012, local spread is by wind and by movement of diseased plants over longer distances.</p> <p>Woodlands in Scotland are infected, the distribution of sites of which is reported by the Forestry Commission, and can be viewed on the interactive <a href="https://secure.fera.defra.gov.uk/chalaramap/">Chalara (Hymenoscyphus fraxineus) infection map</a>. Background information on the disease, its origins, symptoms and precautions to reduce risks of spread are available from the Forestry Commission <a href="https://www.forestresearch.gov.uk/tools-and-resources/pest-and-disease-resources/ash-dieback-hymenoscyphus-fraxineus/">here</a>.</p> <p>The <a href="http://www.hutton.ac.uk">James Hutton Institute</a> has developed a Virtual Reality model to present information about the symptoms and different stages and spread of infection of Chalara ash dieback on woodlands. The model was designed to represent characteristics of the vegetation and topography of a site in north-west Scotland.</p> <p>Interactive functions have been included which enable the presentation of a narrative about the Chalara Ash Dieback threat to woodlands, including scenarios of spread of infection, symptoms of infection, the death of trees, and the regeneration of woodland. </p> <p>The model can be downloaded and used in a PC or virtual reality environment. Guidelines are provided, and links to the relevant software for its use. </p> <p><strong>Software: </strong>The software required to use the model in Virtual Reality is ‘BS Contact Stereo’. The free to use, demonstration version of the software package can be download from <a href="http://www.bitmanagement.com/en/products/interactive-3d-clients/bs-contact-stereo"><strong>here</strong></a>.</p> <p>The 3D model can be used through <a href="http://www.bitmanagement.com/en/products/interactive-3d-clients/bs-contact-stereo#:~:text=BS%20Contact%20Stereo,and%20up%20to%20CAVE%20solutions.">BS Contact Stereo</a> for a Virtual Reality headset (e.g. <a href="https://www.oculus.com/rift/?locale=en_GB">Oculus Rift</a>).</p> <p>[Note: Users may notice a ‘blue dot’ floating across the screen when they are exploring the Virtual Reality model. That has no effect or role in the model. It is a feature of the demonstration free-to-use package.]</p> <p><strong>Start model: </strong>To start the model, users should load and play the file: AshDieback_Main.wrl.</p> <p><strong>Navigation: </strong>Navigation of the 3D environment of the woodland can be by use of a keyboard or Xbox controller.</p> <p>More information about the model and disease are is available at: <a href="https://www.hutton.ac.uk/research/departments/information-and-computational-sciences/chalara-ash-die-back-virtual-woodland-environment">Chalara: Ash Die-back Virtual Woodland Environment</a>. </p> <p>Photographs can be accessed of the Virtual Reality model in use with an Oculus Rift headset, and in the <a href="https://www.hutton.ac.uk/learning/image-galleries/gallery-vlt-events-vltjohn-hope-gateway-rbge">Virtual Landscape Theatre</a>.</p>
Preliminary Testing of a System for the Multimodal Analysis of Gait Training in a Virtual Reality Environment
<p>The dataset is related to the paper Piazza, C.; Pirovano, I.; Mastropietro, A.; Genova, C.; Gagliardi, C.; Turconi, A.C.; Malerba, G.; Panzeri, D.; Maghini, C.; Reni, G.; Rizzo, G. and Biffi E. Development and Preliminary Testing of a System for the Multimodal Analysis of Gait Training in a Virtual Reality Environment. Electronics 2021, 10, 2838. https://doi.org/10.3390/electronics10222838. </p> <p>It includes multimodal data (EEG, EMG, kinematics and kinetics) of a healthy child (HC) and a child with hemiparesis (CP01) during walking in a virtual environmment (GRAIL, Motek).</p> <p>Data can be opened by using EEGLab and Matlab </p> <p> </p> <p> </p>
Realtime Data Collection and Analysis Framework for Collaboration and Co-presence in a Virtual Reality Environment
<p>Title: Realtime Data Collection and Analysis Framework for Collaboration and Co-presence in a Virtual Reality Environment</p> <p>Abstract:</p> <p>As VR technologies continue to evolve and gain popularity, one of their most notable features is connecting with the virtual presence of a person who is not physically present. Understanding the dynamics of user interaction within these environments is crucial, as they can be utilized in various ways, including collaboration, communication, social interactions, or games and entertainment. This paper presents a method for measuring collaboration and co-presence factors of users by developing a real-time data collection and analysis framework. The designed framework focuses on different collaboration and co-presence scenarios and evaluates a comprehensive system for monitoring and analyzing user interactions in VR, employing both physiological sensors and subjective feedback to assess the sense of presence, co-presence, and collaboration quality. Through an extensive literature review, the paper studies how various factors, including avatar realism and communication modalities, influence user engagement and interaction efficacy. The experiment framework’s capability to integrate qualitative and quantitative data provides a deeper understanding of the immersive experience and its impact on collaborative tasks. The results highlight the importance of design choices in VR environments and their implications for human-computer interaction, user performance, and satisfaction. The findings offer practical guidance for developing more effective VR systems for collaborative work and social interaction.</p> <p>Data Description:</p> <p>1. User Interaction Logs:</p> <p><span> </span>- Data Type: Quantitative</p> <p><span> </span>- Description: Timestamped logs of user actions and interactions within the VR environment, including movement data, interaction with objects, and communication instances.</p> <p><span> </span>- Format: CSV</p> <p><span> </span>- Variables: User ID, Timestamp, Action Type, Object Interacted, Coordinates, Duration</p> <p>2. Physiological Sensor Data:</p> <p><span> </span>- Data Type: Quantitative</p> <p><span> </span>- Description: Real-time physiological data collected from users during VR sessions, including heart rate, skin conductance, and EEG data.</p> <p><span> </span>- Format: CSV,</p> <p><span> </span>- Variables: User ID, Timestamp, Heart Rate, Skin Conductance, EEG Channels</p> <p>3. Avatar Realism and Communication Modalities Data:</p> <p><span> </span>- Data Type: Quantitative</p> <p><span> </span>- Description: Data evaluating the impact of avatar realism and communication methods (e.g., voice chat, text chat) on user engagement and interaction efficacy.</p> <p><span> </span>- Format: CSV, Text</p> <p><span> </span>- Variables: User ID, Avatar Type, Communication Modality, Engagement Score, Interaction Quality Feedback</p> <p>4. Collaboration and Co-presence Metrics:</p> <p><span> </span>- Data Type: Quantitative</p> <p><span> </span>- Description: Calculated metrics for collaboration efficiency and co-presence, derived from interaction logs and physiological data.</p> <p><span> </span>- Format: CSV</p> <p><span> </span>- Variables: User ID, Collaboration Efficiency Score, Co-presence Score, Task Performance</p> <p> </p> <p> </p>
Biographische Informationssysteme (DPBs, Digital Knowledge Databases, Virtual Research Environments)
<p>The table is an overview of database and online systems to manage/publish prosopographical and biographical data. </p>
Virtual acoustic street environment
<p><strong>Virtual acoustic street environment</strong></p> <p>This dataset contains files needed to render a virtual acoustic street environment in TASCAR (version 0.228 or newer). See Street_Environment_Description.pdf for details.</p> <p><strong>Authors:</strong></p> <p>Giso Grimm (session file)</p> <p>This file can be used and distributed according to following license conditions:</p> <p><strong>Licenses:</strong></p> <p><a href="https://creativecommons.org/licenses/by/3.0/">CC BY 3.0</a> (76804__audible-edge__ae0090-volvo-740-gle-handbrake-turn-01.wav)<br> <a href="https://creativecommons.org/licenses/by-nc-sa/3.0/">CC BY-NC-SA 3.0</a> (Story6.flac, baby_talks.wav)<br> <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">CC BY-NC-SA 4.0</a> (coke_can_2wheels_pram.flac)<br> <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">CC BY-NC-SA 4.0</a> (session file)<br> <a href="https://creativecommons.org/licenses/by-sa/3.0/">CC BY-SA 3.0</a> (la_le_lu.flac, pramwheels.wav, redcar_loop1.wav, whitevan_loop1.wav)<br> <a href="https://creativecommons.org/share-your-work/public-domain/cc0/">CC0</a> (apts.wav, bike_bell.wav, bus.flac, footsteps.wav, martin.wav, train_ax1.wav, train_ax2.wav, train_ax3.wav, train_ax4.wav, train_ax5.wav, train_engine.wav, truckbeep.flac)</p> <p><strong>Attributions:</strong></p> <p>Giso Grimm (baby_talks.wav, pramwheels.wav, redcar_loop1.wav, session file, whitevan_loop1.wav)<br> Maartje Hendrikse (Story6.flac)<br> Sabine Hochmut (la_le_lu.flac)<br> Theda Eichler, Giso Grimm (coke_can_2wheels_pram.flac)<br> audible-edge / freesound.org (76804__audible-edge__ae0090-volvo-740-gle-handbrake-turn-01.wav)</p> <p><strong>Acknowledgements:</strong></p> <p>Thanks to Marie Hartwig for her support in the preparation of this upload.</p> <p><strong>Bibliography:</strong></p> <p>Grimm, Giso; Luberadzka, Joanna; Hohmann, Volker. <em>A Toolbox for Rendering Virtual Acoustic Environments in the Context of Audiology.</em> Acta Acustica united with Acustica, Volume 105, Number 3, May/June 2019, pp. 566-578(13), <a href="https://doi.org/10.3813/AAA.919337">https://doi.org/10.3813/AAA.919337</a></p> <p>Hendrikse, M. M., Llorach, G., Hohmann, V., & Grimm, G. (2019). <em>Movement and gaze behavior in virtual audiovisual listening environments resembling everyday life.</em> Trends in Hearing, 23, <a href="https://doi.org/10.1177/2331216519872362">https://doi.org/10.1177/2331216519872362</a></p> <p>Grimm, Giso, & Hohmann, Volker. (2019). <em>First Order Ambisonics field recordings for use in virtual acoustic environments in the context of audiology.</em> Zenodo. <a href="https://doi.org/10.5281/zenodo.3588303">https://doi.org/10.5281/zenodo.3588303</a></p> <p>Hendrikse, Maartje M. E., Dingemanse, Gertjan, Grimm, Giso, Hohmann, Volker, & Goedegebure, André. (2022, September 19). Virtual audiovisual scenes for hearing device fine-tuning. Zenodo. <a href="https://doi.org/10.5281/zenodo.7092790">https://doi.org/10.5281/zenodo.7092790</a></p>
SIMCor - R-Statistical Environment embedded in the SIMCor Virtual Research Environment
<p>Using RStudio, the capabilities of running statistical evaluations in a standardised manner directly on the SIMCor Virtual Research Environment (VRE) has been realised. Via a web frontend, scripts written in the R programming language can be directly evaluated on the data, such as the virtual cohorts, available at the VRE.</p>
Supporting data for: Immersive information seeking - a scoping review of information seeking in virtual reality environments
<p>Dataset that contains of all reviewed research items obtained for the Scoping Literature Review <em>Immersive information seeking - a scoping review of information seeking in virtual reality environments</em>.</p>
Studying the Impact of Product Packaging in a Virtual Store Environment
ClinicalTrials.gov study NCT04381481. IPD Sharing: NO. Countries: 1. Publications: 2.
Virtual Environments for Vestibular Rehabilitation
ClinicalTrials.gov study NCT04268745. IPD Sharing: NO. Countries: 1. Publications: 2.
Assessing a Novel Virtual Environment That Assists With Activities of Daily Living
ClinicalTrials.gov study NCT05418296. IPD Sharing: NO. Countries: 1. Publications: 3.
Interaction Framework within Collaborative Virtual Environments for Multiple Users each interacting with Multiple Degrees-Of-Freedom Controllers
<p>Collaboration is a process in which two or more agents work together to achieve shared goals. However, many existing platforms cannot generate a collaborative environment to engage multiple users with multiple controllers in a seamless manner. To address this need, this video and work in progress will describe LISU (Library for Interactive Settings and User-modes) an input management computing framework that enables collaboration across multiple input controllers as its default. Within the system team members cohabit any real-time simulation environments simultaneously and are then able to jointly control visualisation software across multiple controllers while being continually monitored and evaluated at a low level, allowing research questions to be answered.</p>
Development and evaluation of a test setup to investigate distance differences in immersive virtual environments
<p>Nowadays, with recent advances in virtual reality technology, it is easily possible to integrate real objects into<br> virtual environments by creating an exact virtual replication and enabling interaction with them by mapping the obtained tracking<br> data of the real to the virtual objects. The primary goal of our study is to develop a system to investigate distance differences for<br> near-field interaction in immersive virtual environments. In this context, the term distance difference refers to the shift between<br> a real object and the respective replication of the real object in the virtual environment of the same size. This could occur<br> for a number of reasons e.g. due to errors in motion tracking or mistakes in designing the virtual environment. Our virtual<br> environment is developed using the Unity3D game engine, while the immersive contents were displayed on an HTC Vive Pro headmounted display. The virtual room shown to the user includes a replication of the real testing lab environment, while one of<br> the two real objects is tracked and mirrored to the virtual world using an HTC Vive Tracker. Both objects are present<br> in the real as well as in the virtual world. To find perceivable distance differences in the near-field, the actual task in the<br> subjective test was to pick up one object and place it into another object. The position of the static object in the virtual<br> world is shifted by values between 0 and 4 cm, while the position of the real object is kept constant. The system is evaluated by<br> conducting a subjective proof-of-concept test with 18 test subjects. The distance difference is evaluated by the subjects through<br> estimating perceived confusion on a modified 5-point absolute category rating scale. The study provides quantitative insights<br> into allowable real-world vs. virtual-world mismatch boundaries for near-field interactions, with a threshold value of around 1 cm.</p>
Characterizing long-range search behavior in Diptera using complex 3D virtual environments
<p>The exemplary search capabilities of flying insects have established them as one of the most diverse taxa on Earth. However, we still lack the fundamental ability to quantify, represent, and predict trajectories under natural contexts to understand search and its applications. For example, flying insects have evolved in complex multimodal 3D environments, but we do not yet understand which features of the natural world are used to locate distant objects. Here, we independently and dynamically manipulate 3D objects, airflow fields, and odor plumes in virtual reality over large spatial and temporal scales. We demonstrate that that flies make use of features such as foreground segmentation, perspective, motion parallax, and integration of multiple modalities to navigate to objects in a complex 3D landscape while in flight. We first show that tethered flying insects of multiple species navigate to virtual 3D objects. Using the apple fly, <i>Rhagoletis pomonella</i>, we then measure their reactive distance to objects and show that these flies<i> </i>use perspective and local parallax cues to distinguish and navigate to virtual objects of different sizes and distances. We also show that apple flies can orient in the absence of optic flow by using only directional airflow cues, and require simultaneous odor and directional airflow input for plume following to a host volatile blend. The elucidation of these features unlocks the opportunity to quantify parameters underlying insect behavior such as reactive space, optimal foraging, and dispersal, as well as develop strategies for pest management, pollination, robotics and search algorithms.</p>
Use of Machine Learning in virtual learning environments: a bibliometric review
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.