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Applied Sciences
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Enhancing User Experience in Virtual Reality Environments: Innovative Interaction Design...
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Enhancing User Experience in Virtual Reality Environments: Innovative Interaction Design Strategies

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 March 2025 | Viewed by 5995

Special Issue Editors

Dr. Dario Maggiorini

E-Mail Website
Guest Editor
Department of Computer Science, University of Milan, 20133 Milan, Italy
Interests: network architectures; distributed systems; multimedia transmission
Special Issues, Collections and Topics in MDPI journals
Dr. Davide Gadia

E-Mail Website
Guest Editor
Department of Computer Science, University of Milan, 20133 Milan, Italy
Interests: computer graphics; video game programming; game engine architectures; procedural content generation; artificial intelligence for video games
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nowadays, with the surge of Virtual Reality (VR) hardware and software, we are witnessing a new dawn for immersive and interactive applications. This new generation of applications calls for new approaches to defining, measuring, and implementing User Experience (UX) and advanced interaction methodologies.

Today, designing a high-resolution, quasi-realistic 3D environment is no longer enough to foster emotions and convey a compelling experience to users. In order to improve the state of the art, a number of additional factors must be taken into account. Coordination is required to enhance the User Experience inside a Virtual Reality environment as well as to provide advanced methods with which to interact with the virtual world in a collaborative manner with other remote participants.

This Special Issue offers an opportunity for researchers to present high-quality, original works on the improvement of UX in VR environments. Contributions focused on the enhancement of perception and involvement of users in VR environments, as well as methodologies for designing extended experience, innovative interaction approaches, and next-generation applications, are particularly welcome. Moreover, papers addressing the difficulties in designing hardware and architecture (both software- and network-oriented) for VR and Augmented Reality (AR) are of interest.

Dr. Dario Maggiorini
Dr. Davide Gadia
Guest Editors

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • virtual reality
  • virtual environments
  • user experience
  • human–computer interaction
  • interaction design
  • augmented reality

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Published Papers (3 papers)

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Research

15 pages, 4269 KiB  
Article
Assessing Ambisonics Sound Source Localization by Means of Virtual Reality and Gamification Tools
by Esaú Medina, Rhoddy Viveros-Muñoz and Felipe Otondo
Appl. Sci. 2024, 14(17), 7986; https://doi.org/10.3390/app14177986 - 6 Sep 2024
Viewed by 1435
Abstract
Sound localization is a key area of interest in auditory research, especially in complex acoustic environments. This study evaluates the impact of incorporating higher-order Ambisonics (HOA) with virtual reality (VR) and gamification tools on sound source localization. The research addresses the current limitations [...] Read more.
Sound localization is a key area of interest in auditory research, especially in complex acoustic environments. This study evaluates the impact of incorporating higher-order Ambisonics (HOA) with virtual reality (VR) and gamification tools on sound source localization. The research addresses the current limitations in VR audio systems, particularly the lack of native support for HOA in game engines like Unreal Engine (UE). A novel framework was developed, combining UE for VR graphics rendering and Max for HOA audio processing. Participants performed sound source localization tasks in two VR environments using a head-mounted display (HMD). The assessment included both horizontal and vertical plane localization. Gamification elements were introduced to improve engagement and task comprehension. Results showed significant improvements in horizontal localization accuracy, although challenges remained in back localization. The findings underscore the potential of VR and gamification to enhance auditory tests, reducing test duration and participant fatigue. This research contributes to the development of immersive and interactive audio experiences, highlighting the broader applications of VR beyond entertainment. Full article
(This article belongs to the Special Issue Enhancing User Experience in Virtual Reality Environments: Innovative Interaction Design Strategies)
►▼ Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) VR environment as a replica of the LATe lab at Universidad Austral de Chile. (<b>b</b>) VR environment of a wetland in the city of Valdivia, Chile.</p> Full article ">Figure 1 Cont.
<p>(<b>a</b>) VR environment as a replica of the LATe lab at Universidad Austral de Chile. (<b>b</b>) VR environment of a wetland in the city of Valdivia, Chile.</p> Full article ">Figure 2
<p>Spatial representations of the loudspeakers, arranged according to the virtual source distribution. (<b>a</b>) Horizontal distribution at 0° elevation. (<b>b</b>) Horizontal distribution at 0° and 35° elevation.</p> Full article ">Figure 3
<p>User interface for stimulus control within the VR environment.</p> Full article ">Figure 4
<p>Spectrogram of the auditory stimulus used in this study: call of the bird Vanellus chilensis, showing frequency content of the call, emphasizing the spectral range with significant components relevant for vertical and front/back localization.</p> Full article ">Figure 5
<p>Flow in Max/<span class="html-italic">Spat</span> used for sound localization experiments with two-way OSC communication with UE.</p> Full article ">Figure 6
<p>Violin plot of sound localization perception in the first round. The distribution of localization responses is shown as a function of the azimuth. The violin plot illustrates the spread of responses per angle, with the shape representing a sideways histogram.</p> Full article ">Figure 7
<p>Violin plot of sound localization perception in the second round. The distribution of localization responses is shown as a function of the azimuth. It presents the cases with both elevations of 0° and 35°. The violin plot illustrates the spread of responses per angle, with the shape representing a sideways histogram.</p> Full article ">
23 pages, 2980 KiB  
Article
Comparative Analysis of SAAS Model and NPC Integration for Enhancing VR Shopping Experiences
by Surasachai Doungtap, Jenq-Haur Wang and Varinya Phanichraksaphong
Appl. Sci. 2024, 14(15), 6573; https://doi.org/10.3390/app14156573 - 27 Jul 2024
Viewed by 1400
Abstract
This article examines the incorporation of the Shopping Assistance Automatic Suggestion (SAAS) model into Virtual Reality (VR) environments in order to improve the online shopping experience. The SAAS model employs sophisticated deep learning methods to offer customized product recommendations, which are conveyed by [...] Read more.
This article examines the incorporation of the Shopping Assistance Automatic Suggestion (SAAS) model into Virtual Reality (VR) environments in order to improve the online shopping experience. The SAAS model employs sophisticated deep learning methods to offer customized product recommendations, which are conveyed by non-player characters (NPCs) via voice-based interactions. Our goal is to develop an interactive shopping experience that replicates real-life interactions by integrating AI-powered recommendations with immersive VR technology. We gather and standardize data from several open commerce databases, such as Amazon Product and Customer Reviews. The SAAS model, in conjunction with GPT-3, BERT, and T5, undergoes training and testing to evaluate its effectiveness across multiple criteria. The results demonstrate that the SAAS model surpasses other models in delivering contextually aware and pertinent recommendations. The integration process outlines the specific steps involved in capturing, processing, and transforming user interactions in virtual reality (VR) into vocal suggestions provided by non-player characters (NPCs). This strategy improves customization and utilizes the immersive features of virtual reality to effectively engage people. The results of our research establish a higher standard for e-commerce, with the goal of enhancing the user experience of online purchasing by making it more instinctive, engaging, and pleasurable. Full article
(This article belongs to the Special Issue Enhancing User Experience in Virtual Reality Environments: Innovative Interaction Design Strategies)
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Figure 1

Figure 1
<p>Flowchart of the Data Normalization Process.</p> Full article ">Figure 2
<p>The sequence prediction process used by the GPT-3 Model.</p> Full article ">Figure 3
<p>The sequence prediction process used by the BERT Model.</p> Full article ">Figure 4
<p>The sequence prediction process used by the T5 Model.</p> Full article ">Figure 5
<p>Flowchart of the SAAS Model.</p> Full article ">Figure 6
<p>Comparison of Model Performance Metrics.</p> Full article ">Figure 7
<p>The Workflow of the Suggestion System.</p> Full article ">Figure 8
<p>Qualitative Comparison of Models.</p> Full article ">Figure 9
<p>The NPC Integrating with the SAAS model.</p> Full article ">Figure 10
<p>The integration workflow of The SAAS model with VR NPC.</p> Full article ">
27 pages, 1982 KiB  
Article
Current Perceptions of Virtual Reality Technology
by Rebecca L. Hornsey and Paul B. Hibbard
Appl. Sci. 2024, 14(10), 4222; https://doi.org/10.3390/app14104222 - 16 May 2024
Cited by 7 | Viewed by 1865
Abstract
User experience is a key predictor of future use of goods and services. The presented study collected a combination of qualitative and quantitative data from both experienced users and novices about their perceptions of virtual reality (VR) equipment, any concerns surrounding the data [...] Read more.
User experience is a key predictor of future use of goods and services. The presented study collected a combination of qualitative and quantitative data from both experienced users and novices about their perceptions of virtual reality (VR) equipment, any concerns surrounding the data collected by the equipment, and facets that needed to be taken into consideration for future developments. The purpose of this research was to understand the current user experience of VR and ways in which it can be improved. The findings indicated that the majority of people have used VR, albeit infrequently, and that the most common use for it was for entertainment purposes. The most important characteristics of VR systems were judged to be the available content and price. While it was reported to be enjoyable to use, the ways in which it was suggested to be improved were through a reduction in size and weight of the headsets, and incorporating wireless capabilities. Concerns about the use of VR were the potential for sickness, discomfort, and eye strain, the disconnect from the real world and the subsequent risks that this poses, as well as the use and privacy of user data. The findings from this research can be used as a stepping stone toward the advancement of VR technologies. Full article
(This article belongs to the Special Issue Enhancing User Experience in Virtual Reality Environments: Innovative Interaction Design Strategies)
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Figure 1

Figure 1
<p>Acceptance models for behaviour: (<b>a</b>) The Theory of Reasoned Action [<a href="#B67-applsci-14-04222" class="html-bibr">67</a>]; (<b>b</b>) The Technology Acceptance Model [<a href="#B68-applsci-14-04222" class="html-bibr">68</a>]; (<b>c</b>) The Theory of Planned Behaviour [<a href="#B77-applsci-14-04222" class="html-bibr">77</a>].</p> Full article ">Figure 2
<p>The Virtual Reality Hardware Acceptance Model [<a href="#B78-applsci-14-04222" class="html-bibr">78</a>].</p> Full article ">Figure 3
<p>Word cloud for the free-text responses to the question ‘For what reason(s) have you not tried VR before?’. Larger words indicate a higher frequency.</p> Full article ">Figure 4
<p>(<b>a</b>) Frequency of how often participants use VR. (<b>b</b>) Frequency of the reported uses of VR equipment.</p> Full article ">Figure 5
<p>Frequency of the last time participants used VR.</p> Full article ">Figure 6
<p>Frequency of the option chosen to be the most important feature for VR.</p> Full article ">Figure 7
<p>Frequency of the ranked appropriateness of different descriptions of VR devices.</p> Full article ">Figure 8
<p>Frequency of the sensory factor rated most and least important for a VR device.</p> Full article ">Figure 9
<p>Sentiment analysis conducted on the free-text responses to the question ‘what are your thoughts on VR becoming a daily commodity?’. Larger words indicate a higher frequency, sorted into positive and negative categories.</p> Full article ">Figure 10
<p>Ranked level for how appropriate each type of data collection is perceived to be, for both mobile and VR devices.</p> Full article ">Figure 11
<p>Topical analysis showing four themes detected by the CTM algorithm and the beta weighting of the 10 most frequent terms in response to the question ‘what precautions do you think need to be taken when using VR?’. Topic <span class="html-italic">1</span> was interpreted to surround physiological risks; <span class="html-italic">2</span> privacy; <span class="html-italic">3</span> disconnect of virtual aspects from physical space; <span class="html-italic">4</span> secure environment.</p> Full article ">Figure 12
<p>Word cloud for the free-text responses to the question ‘what precautions do you think need to be taken when…’; (<b>a</b>) prompt ‘using VR?’; (<b>b</b>) prompt: ‘creating a new VR headset?’. Larger words indicate a higher frequency.</p> Full article ">Figure 13
<p>Sentiment analysis clouds for the free-text responses to the question ‘Do you have any opinions on the data that is collected on you, from…?’; (<b>a</b>) prompt: your mobile phone; (<b>b</b>) prompt: a VR headset. Larger words indicate a higher frequency, sorted into positive and negative categories.</p> Full article ">Figure 14
<p>Sentiment analysis conducted on the free-text responses to the question ‘what do you associate VR with?’. Larger words indicate a higher frequency, sorted into positive and negative categories.</p> Full article ">
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