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Electronics
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Emerging Trends in Multimodal Human-Computer Interaction
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Emerging Trends in Multimodal Human-Computer Interaction

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: 15 May 2025 | Viewed by 2789

Special Issue Editors

Dr. Sónia Sousa

E-Mail Website
Guest Editor
School of Digital Technologies, Tallinn University, 10120 Tallinn, Estonia
Interests: trust in technology; interaction design; technology education; human-computer interaction
Dr. Olga Dunajeva

E-Mail Website
Guest Editor
School of Engineering, Tallinn University of Technology, 19086 Tallinn, Estonia
Interests: machine learning; emotion recognition
Prof. Dr. Jüri Majak

E-Mail Website
Guest Editor
Department of Mechanical and Industrial Engineering, Tallinn University of Technology, 19086 Tallinn, Estonia
Interests: design optimization; numerical methods; haar wavelet methods; composite structures; fractional differential equations; nanocomposites; graphene structures; nonlocal elasticity theories; laminated glass panels; solar panels
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Industry 5.0 has highlighted the need for new human-centered practices in human-robot and human-computer interactions. This approach focuses on enhancing people’s well-being and promoting social inclusion by adopting technologies that complement human abilities. This digital revolution transforms how we communicate, collaborate, and interact with machines. As a result, recent research has shifted towards developing human-centered methods to ensure that applications of intelligent autonomous systems are trusted, safe, secure, flexible, ethical, and reliable. This Special Issue on Electronics invites submissions on the following topics, among others:

  • Trust in human-AI interaction;
  • HCI and trustworthy AI;
  • Trustworthy large language models (LLMs);
  • Trustworthiness of AI-powered applications;
  • Transparency and explainability;
  • Bias detection and mitigation;
  • Privacy and security in HCI;
  • Robustness and reliability;
  • Ethical AI development;
  • Multimodal interactions in HCI;
  • Robotics and AI;
  • Physiological data preprocessing in HCI;
  • Emotion and mood analysis;
  • Embodied and wearable computing.

Dr. Sónia Sousa
Dr. Olga Dunajeva
Prof. Dr. Jüri Majak
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

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

  • human-computer interaction
  • trustworthy AI
  • multimodal interactions
  • human-AI interaction

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Published Papers (3 papers)

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Research

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27 pages, 4463 KiB  
Article
Combining Design Neurocognition Technologies and Neural Networks to Evaluate and Predict New Product Designs: A Multimodal Human–Computer Interaction Study
by Jun Wu, Xiangyi Lyu, Yi Wang, Tao Liu, Shinan Zhao and Lirui Xue
Electronics 2025, 14(6), 1128; https://doi.org/10.3390/electronics14061128 - 13 Mar 2025
Viewed by 468
Abstract
The multimodal data collection that includes physiological and psychological data, combined with data processing using artificial intelligence technology, has become a research trend in human–computer interaction. In the stage of new product design, it is necessary to consider user experience for the evaluation [...] Read more.
The multimodal data collection that includes physiological and psychological data, combined with data processing using artificial intelligence technology, has become a research trend in human–computer interaction. In the stage of new product design, it is necessary to consider user experience for the evaluation and prediction of new products. The paper presents a human–computer interaction study on new product design with user participation. This research adopts a combination of design neurocognition and genetic algorithms in design optimization to evaluate the usability of engineering control interfaces using eye-tracking and facial expression data. Eye-tracking and neural network technology are used to predict the appearance of humanoid robots. The paper explored the evaluation and prediction of new product design using multimodal physiological and psychological data. The research results indicate that artificial intelligence technologies represented by neural networks can fully exploit biometric data represented by eye-tracking and facial expression, improving the effectiveness of new product evaluation and prediction accuracy. The research results provide a solution based on the combination of design neurocognition and artificial intelligence technology for the evaluation and prediction of new product design in the future. Full article
(This article belongs to the Special Issue Emerging Trends in Multimodal Human-Computer Interaction)
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27 pages, 12488 KiB  
Article
Smart Transparency: A User-Centered Approach to Improving Human–Machine Interaction in High-Risk Supervisory Control Tasks
by Keran Wang, Wenjun Hou, Leyi Hong and Jinyu Guo
Electronics 2025, 14(3), 420; https://doi.org/10.3390/electronics14030420 - 21 Jan 2025
Cited by 1 | Viewed by 1143
Abstract
In supervisory control tasks, particularly in high-risk fields, operators need to collaborate with automated intelligent agents to manage dynamic, time-sensitive, and uncertain information. Effective human–agent collaboration relies on transparent interface communication to align with the operator’s cognition and enhance trust. This paper proposes [...] Read more.
In supervisory control tasks, particularly in high-risk fields, operators need to collaborate with automated intelligent agents to manage dynamic, time-sensitive, and uncertain information. Effective human–agent collaboration relies on transparent interface communication to align with the operator’s cognition and enhance trust. This paper proposes a human-centered adaptive transparency information design framework (ATDF), which dynamically adjusts the display of transparency information based on the operator’s needs and the task type. This ensures that information is accurately conveyed at critical moments, thereby enhancing trust, task performance, and interface usability. Additionally, the paper introduces a novel user research method, Heu–Kano, to explore the prioritization of transparency needs and presents a model based on eye-tracking and machine learning to identify different types of human–agent interactions. This research provides new insights into human-centered explainability in supervisory control tasks. Full article
(This article belongs to the Special Issue Emerging Trends in Multimodal Human-Computer Interaction)
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Other

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22 pages, 1742 KiB  
Systematic Review
Trust and Trustworthiness from Human-Centered Perspective in Human–Robot Interaction (HRI)—A Systematic Literature Review
by Debora Firmino de Souza, Sonia Sousa, Kadri Kristjuhan-Ling, Olga Dunajeva, Mare Roosileht, Avar Pentel, Mati Mõttus, Mustafa Can Özdemir and Žanna Gratšjova
Electronics 2025, 14(8), 1557; https://doi.org/10.3390/electronics14081557 - 11 Apr 2025
Viewed by 450
Abstract
The transition from Industry 4.0 to Industry 5.0 highlights recent European efforts to design intelligent devices, systems, and automation that can work alongside human intelligence and enhance human capabilities. In this vision, human–machine interaction (HMI) goes beyond simply deploying machines, such as autonomous [...] Read more.
The transition from Industry 4.0 to Industry 5.0 highlights recent European efforts to design intelligent devices, systems, and automation that can work alongside human intelligence and enhance human capabilities. In this vision, human–machine interaction (HMI) goes beyond simply deploying machines, such as autonomous robots, for economic advantage. It requires societal and educational shifts toward a human-centric research vision, revising how we perceive technological advancements to improve the benefits and convenience for individuals. Furthermore, it also requires determining which priority is given to user preferences and needs to feel safe while collaborating with autonomous intelligent systems. This proposed human-centric vision aims to enhance human creativity and problem-solving abilities by leveraging machine precision and data processing, all while protecting human agency. Aligned with this perspective, we conducted a systematic literature review focusing on trust and trustworthiness in relation to characteristics of humans and systems in human–robot interaction (HRI). Our research explores the aspects that impact the potential for designing and fostering machine trustworthiness from a human-centered standpoint. A systematic analysis was conducted to review 34 articles in recent HRI-related studies. Then, through a standardized screening, we identified and categorized factors influencing trust in automation that can act as trust barriers and facilitators when implementing autonomous intelligent systems. Our study comments on the application areas in which trust is considered, how it is conceptualized, and how it is evaluated within the field. Our analysis underscores the significance of examining users’ trust and the related factors impacting it as foundational elements for promoting secure and trustworthy HRI. Full article
(This article belongs to the Special Issue Emerging Trends in Multimodal Human-Computer Interaction)
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