AI-Based Interactive and Immersive Systems

Topic Information

Dear Colleagues,

This Topic explores the growing impact of artificial intelligence (AI) and immersive interactive systems on human experience, society, and diverse domains such as culture, education, healthcare, art, science, creative practices, and the environment, among others. It examines how emerging technologies transform production, participation, and exchange across different fields while enabling new forms of knowledge, communication, and collective engagement. Our focus is on interactive and immersive systems that reshape human–computer collaboration and address pressing social, ecological, and domain-specific challenges. The collection highlights how human-centered perspectives can guide system design, enrich user experience, and foster inclusive and sustainable innovation.

The scope of this collection encompasses both theoretical and practice-based research. We welcome contributions on topics such as human–AI interaction and collaboration, AI-assisted creativity, generative and adaptive systems, immersive installations, multisensory environments, interactive performances, and virtual or hybrid worlds that challenge traditional notions of embodiment and participation. Submissions that address ethical, ecological, and cultural dimensions of AI and immersive technologies or introduce new transdisciplinary frameworks are particularly encouraged.

While the existing literature on human–computer interaction, computational creativity, and digital media has provided valuable technical insights, much of it remains discipline-specific or focused on performance and efficiency. This Special Issue aims to broaden the discussion by integrating human-centered perspectives into the study and development of AI-based interactive and immersive systems.

Topics of interest include, but are not limited to, the following:

• Human–AI interaction and collaboration;
• Machine learning algorithms and techniques;
• Natural language processing and generation;
• AI-assisted creativity and generative models in art and design;
• Creativity-driven innovation through the intersection of CCI and AI;
• AI for narrative design and storytelling;
• AI and big data in environmental sustainability and climate change research;
• The ethics of AI and big data;
• Participatory and creative approaches for public space design and/or public engagement;
• Interactive and adaptive systems for creative expression;
• Immersive installations, digital performance, and experiential environments in cultural contexts;
• Virtual, augmented, and mixed reality for design, prototyping, and artistic practices;
• Multisensory and embodied experiences in immersive media;
• Practice-based research and transdisciplinary methodologies;
• Case studies of art–technology intersections and hybrid practices in creative industries.

Dr. Sotiris Diplaris
Dr. Nefeli Georgakopoulou
Dr. Stefanos Vrochidis
Dr. Giuseppe Amato
Prof. Dr. Maurice Benayoun
Prof. Dr. Beatrice De Gelder
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
AI ai	5.0	6.9	2020	19.2 Days	CHF 1800	Submit
Applied Sciences applsci	2.5	5.5	2011	16 Days	CHF 2400	Submit
Big Data and Cognitive Computing BDCC	4.4	9.8	2017	23.1 Days	CHF 1800	Submit
Electronics electronics	2.6	6.1	2012	16.4 Days	CHF 2400	Submit
Multimodal Technologies and Interaction mti	2.4	5.8	2017	21.7 Days	CHF 1800	Submit
Virtual Worlds virtualworlds	-	-	2022	18.1 Days	CHF 1200	Submit

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Published Papers (4 papers)

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All Electronics MTI BDCC AI Virtual Worlds Applied Sciences

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28 pages, 2070 KB  

Open AccessArticle

Cognitive Load During Student-Created Virtual Worlds: A NASA-TLX Assessment Using Spatial.io

by Dimitrios Magetos, Sarandis Mitropoulos and Christos Douligeris

Virtual Worlds 2026, 5(2), 22; https://doi.org/10.3390/virtualworlds5020022 - 11 May 2026

Viewed by 352

Abstract

Despite the increasing adoption of metaverse technologies, particularly in educational contexts, the cognitive impacts of students designing their own immersive experiences remain underexplored. This study addresses that gap by providing empirical baseline data on the cognitive load of students designing virtual worlds. All [...] Read more.

Despite the increasing adoption of metaverse technologies, particularly in educational contexts, the cognitive impacts of students designing their own immersive experiences remain underexplored. This study addresses that gap by providing empirical baseline data on the cognitive load of students designing virtual worlds. All 100 participants were second-year undergraduate computer science students, aged 20 to 22, who completed a five-week virtual world development project using the Spatial.io platform. Cognitive load was assessed using the NASA Task Load Index (NASA-TLX), which is a measure of six dimensions: Mental Demand, Physical Demand, Temporal Demand, Performance, Effort, and Frustration. The total weighted NASA-TLX showed moderate cognitive load (M = 48.42, SD = 12.18, 95% CI [45.99, 50.85]), with a percentage of 9% of respondents indicating high cognitive load (scores > 60). Temporal Demand was the highest-rated dimension (M = 14.32, SD = 3.84), followed by Mental Demand (M = 13.68, SD = 3.52), while Physical Demand was the lowest (M = 5.23, SD = 2.94). The Spearman correlation analysis indicated that there were strong correlations between Temporal Demand and Effort (ρ = 0.62, p < 0.001) and Temporal Demand and Mental Demand (ρ = 0.58, p < 0.001) with Frustration demonstrating moderate correlations with most cognitive dimensions. In this sample, the NASA-TLX showed a good internal consistency (0.82). No statistically significant difference was found in the overall workload scores or in individual subscales (p > 0.05), indicating that the cognitive load experienced by male and female participants in the development of a virtual world was similar, but the small sub-sample of female participants (n = 25) reduces the statistical power of the comparison. These results provide a descriptive baseline for cognitive workload in virtual world creation led by students and provide evidence-based guidance into how educators can develop immersive development programs. Full article

(This article belongs to the Topic AI-Based Interactive and Immersive Systems)

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26 pages, 6177 KB  

Open AccessArticle

Multimodal Assistance in Rehabilitation: User Experience of Embodied and Non-Embodied Agents for Collecting Patient-Reported Outcome Measures

by Navid Ashrafi, Philipp Graf, Manuela Marquardt, Philipp Harnisch, Stefan Hillmann, Nico Ploner, Diego Compagna, Eren Cirit, Lilia Papst and Jan-Niklas Voigt-Antons

Virtual Worlds 2026, 5(1), 15; https://doi.org/10.3390/virtualworlds5010015 - 19 Mar 2026

Viewed by 613

Abstract

The collection of patient-reported outcome measures (PROMs) is a key measurement tool for patient-centred care. At the same time, collecting these measures poses obstacles for many patients, leading to these groups being underrepresented in the data. We have therefore developed a multimodal, AI-driven [...] Read more.

The collection of patient-reported outcome measures (PROMs) is a key measurement tool for patient-centred care. At the same time, collecting these measures poses obstacles for many patients, leading to these groups being underrepresented in the data. We have therefore developed a multimodal, AI-driven assistance system to support patients in collecting these data. The interface of the system comprised a digital tablet containing the PROM questionnaire items and the assistant in three forms of embodiment: A virtual avatar, a physical avatar, and a voice-only agent. To evaluate the users’ experience and ratings of the system, two separate studies were implemented in two rehabilitation centers with 195 patients. A mixed within–between RCT was conducted at an outpatient clinic, where patients completed PROMs both with and without an assistant, and a between-subject design at an inpatient clinic comparing routine PC-based care with avatar- and robot-assisted PROM administration. Our results suggest a preference for the non-assisted tablet-only condition in Clinic A, whereas, in Clinic B, both agent conditions were preferred over routine care. We have further analyzed aspects such as trust and social presence in this study to gain a more thorough understanding of the users’ experience. Our analysis shows a higher trust rating for the voice-only assistant, whereas the robot, virtual avatar, and the voice-only conditions were perceived as more socially present. The impact of demographic factors and affinity for technology on the user ratings was also thoroughly studied. Our findings shed light on the role of agent embodiment in PROM assistance and contribute to the future design and evaluation of effective, engaging, and trustworthy systems for data collection in healthcare settings. Full article

(This article belongs to the Topic AI-Based Interactive and Immersive Systems)

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31 pages, 28657 KB  

Open AccessArticle

Agent-Based Paradigm for the Self-Configuration of a Conceptual Mechanical Assembly Modeling Application in Virtual Reality

by Julian Conesa, Francisco José Mula and Manuel Contero

Multimodal Technol. Interact. 2026, 10(2), 21; https://doi.org/10.3390/mti10020021 - 22 Feb 2026

Viewed by 646

Abstract

The immersive, multisensory experiences offered by virtual reality have been transformative across multiple disciplines, enhancing practical and theoretical skills while increasing user motivation and learning. On the other hand, multi-agent systems have proven to be effective in facilitating the expansion and modularity of [...] Read more.

The immersive, multisensory experiences offered by virtual reality have been transformative across multiple disciplines, enhancing practical and theoretical skills while increasing user motivation and learning. On the other hand, multi-agent systems have proven to be effective in facilitating the expansion and modularity of computer systems. This paper presents an application developed in a virtual reality environment based on multi-agent systems for the conceptual design of mechanical assemblies from primitives. As a main novelty, the primitives can be defined by the user of the application from a set of models and images, and an Excel document, without the need for programming knowledge, taking advantage of the possibilities offered by multi-agent systems. In addition, for each primitive, it is possible to define a set of geometric and dimensional modifications, as well as a set of position relations with respect to other primitives to generate mechanical assemblies. Full article

(This article belongs to the Topic AI-Based Interactive and Immersive Systems)

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30 pages, 19886 KB  

Open AccessArticle

MoodScape: Emotion-Informed Terrain Synthesis for Virtual Reality System

by Rahul Kumar Rai, Reshu Bansal and Shashi Shekhar Jha

Multimodal Technol. Interact. 2026, 10(2), 19; https://doi.org/10.3390/mti10020019 - 11 Feb 2026

Viewed by 729

Abstract

(1) Background: Virtual environments (VEs) significantly influence human emotions through various elements such as lighting, color, and terrain. While the effects of lighting and color on emotions within VEs have been extensively studied, the impact of the terrain remains underexplored. This paper addresses [...] Read more.

(1) Background: Virtual environments (VEs) significantly influence human emotions through various elements such as lighting, color, and terrain. While the effects of lighting and color on emotions within VEs have been extensively studied, the impact of the terrain remains underexplored. This paper addresses this gap by investigating the correlation between terrain characteristics in VEs and users’ emotional states. (2) Methods: We conducted a user study in which participants were exposed to various 3D terrains and used the Self-Assessment Manikin (SAM) to rate their emotional responses (valence, arousal, and dominance). Building on these insights, we propose MoodScape, an automated framework for emotion-informed terrain generation that significantly reduces the need for extensive expertise and manual effort. In the current implementation, continuous SAM valence–arousal targets are discretised into four quadrant-based affect/terrain classes, and this discrete class label conditions DH-CVAE-GAN terrain synthesis. MoodScape designs a generative adversarial network (GAN) architecture called DH-CVAE-GAN, which integrates a dual-head conditional variational autoencoder as the generator alongside a discriminator network to ensure effective and realistic terrain generation. The DH-CVAE-GAN is trained on a satellite-derived digital elevation model (DEM) dataset, which helps the generated terrains reflect realistic geographic patterns. (3) Results: Quantitative and qualitative evaluations on our study sample suggest that MoodScape can generate terrains whose perceived affective tone is broadly consistent with the specified affect-class inputs, indicating potential applications in gaming and exploratory therapeutic Virtual Reality, while formal clinical efficacy remains in future work. Full article

(This article belongs to the Topic AI-Based Interactive and Immersive Systems)

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