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Advances in Human–Computer Interaction and Intelligent Interface Design
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Advances in Human–Computer Interaction and Intelligent Interface Design

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 September 2026 | Viewed by 2696

Editor

Dr. Tanjila Kanij

E-Mail Website
Guest Editor
School of Science, Computing and Emerging Technologies, Swinburne University of Technology, Hawthorn, Australia
Interests: human computer interactions; software engineering

Special Issue Information

Dear Colleagues,

Human–computer interaction (HCI) and intelligent interface design have become central to the way humans engage with technology. The rapid growth of artificial intelligence, multimodal interaction, and immersive technologies such as AR/VR is reshaping how people communicate, learn, work, and live. As computing systems evolve, there is a pressing need for interfaces that are not only efficient and adaptive but also inclusive, accessible, and human-centered.

This Special Issue will bring together cutting-edge research, innovative applications, and critical reflections regarding the design, development, and evaluation of intelligent interaction systems. We invite scholars, practitioners, and industry experts to contribute original research articles, case studies, and reviews that advance the frontiers of HCI and interface design.

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

  • Intelligent and adaptive interfaces;
  • Human–AI collaboration and co-creativity;
  • Natural language, gesture, and multimodal interaction;
  • Augmented reality (AR), virtual reality (VR), and mixed-reality interfaces;
  • Accessibility, inclusivity, and universal design in intelligent systems;
  • Cognitive models and user experience (UX) in adaptive systems;
  • Trust, transparency, and ethics in intelligent interaction;
  • Brain–computer interfaces and neural interaction design;
  • Emotion-aware and affective computing in HCI;
  • Cross-cultural perspectives in interface design;
  • Evaluation methods for and usability studies on intelligent systems.

Dr. Tanjila Kanij
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences 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 (HCI)
  • intelligent interfaces
  • adaptive systems
  • human–AI collaboration
  • user experience (UX)
  • multimodal interaction
  • virtual reality (VR)
  • augmented reality (AR)
  • mixed reality (MR)
  • accessibility
  • universal design
  • affective computing
  • brain–computer interface (BCI)
  • cognitive models
  • trust and transparency in AI
  • inclusive design

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

22 pages, 1218 KB  
Article
A Two-Stage Study of Menu Configuration and Vibration Feedback in Older Adults’ Smartphone-Based Product Search: From Commercial Age-Friendly Modes to Testable Interface Components
by Jiabao Hu, Haoqi Xue, Xiaorong Cheng, Zhao Fan and Xianfeng Ding
Appl. Sci. 2026, 16(14), 6946; https://doi.org/10.3390/app16146946 - 10 Jul 2026
Viewed by 217
Abstract
Commercial age-friendly modes are increasingly embedded in smartphone applications, yet their task-performance implications for older adults remain uncertain. This two-stage study used a cognitively informed ecological-to-controlled strategy linking evaluation of commercial age-friendly versions with controlled testing of specified interface components while modeling older [...] Read more.
Commercial age-friendly modes are increasingly embedded in smartphone applications, yet their task-performance implications for older adults remain uncertain. This two-stage study used a cognitively informed ecological-to-controlled strategy linking evaluation of commercial age-friendly versions with controlled testing of specified interface components while modeling older adults’ task-relevant cognitive ability. In Experiment 1 (n = 22), older adults completed ten tasks in standard and age-friendly versions of WeChat and Pinduoduo. The age-friendly versions showed no overall advantage in clicks, completion time, or erroneous clicks (all ps ≥ 0.548). Activity Theory-informed video coding identified recurrent task-to-interface mismatches, including insufficiently salient feedback. The exploratory Task 8 product-search observations, together with these coded interaction problems, indicated that product search was a relevant context in which menu configuration, action confirmation, and cognitive demands could be examined together. Because the commercial app versions differed across content and interface features, Experiment 2 (n = 30) used a custom Android product-search task to manipulate menu configuration and vibration feedback while modeling delayed recall continuously as an indicator of task-relevant cognitive ability. Relative to the flat configuration, the two-level menu was associated with 56.7% fewer clicks and 30.7% shorter completion time, whereas vibration feedback was associated with 20.2% fewer ineffective clicks. Delayed recall was associated with completion time in the primary model, but this association was attenuated after adjustment for age and sex. Together, the findings show that a commercial age-friendly label should not be treated as evidence of performance benefit. By separating ecological diagnosis from controlled component testing, the study provides an evidence pathway for translating real-world human–computer interaction problems into testable, task-specific interface components and supports a cognitively informed, information-structure-prioritized, and multisensory approach to smartphone-based product-search design for older adults. Full article
(This article belongs to the Special Issue Advances in Human–Computer Interaction and Intelligent Interface Design)
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28 pages, 11241 KB  
Article
A Dual-Channel Feedback Framework for Anthropomorphic Uncertainty Communication in Behavior Change Systems
by Yiduan Hu, Bipin Indurkhya and Kaori Fujinami
Appl. Sci. 2026, 16(13), 6396; https://doi.org/10.3390/app16136396 - 26 Jun 2026
Viewed by 280
Abstract
Behavior change technologies are increasingly deployed in everyday contexts where perception errors are difficult to avoid. Such errors can undermine user trust and long-term engagement, while purely technical approaches to error elimination are often impractical in open-world environments. This study proposes a fault-tolerant [...] Read more.
Behavior change technologies are increasingly deployed in everyday contexts where perception errors are difficult to avoid. Such errors can undermine user trust and long-term engagement, while purely technical approaches to error elimination are often impractical in open-world environments. This study proposes a fault-tolerant design that translates algorithmic uncertainty into anthropomorphic expressions of vulnerability. By decoupling task-outcome feedback from internal confidence states, an embodied agent communicates uncertainty through a five-level nonverbal framework comprising posture, facial expression, and motion intensity. The approach was implemented in an interactive waste-sorting system and examined through a three-week field study in a semi-public university corridor. Three feedback strategies were compared: an outcome-only baseline, a persistently confident agent, and an adaptive agent whose vulnerability expression varied according to a transformed confidence signal. The findings suggest differences in user behavior across conditions. Under the adaptive condition, user sorting accuracy exhibited a fluctuation–recovery pattern during the final deployment phase, whereas accuracy under the confident-agent condition showed a declining trend. Correct-trial stay durations were shorter under the adaptive condition, consistent with the formation of a more streamlined interaction routine. In contrast, observations from error cases were limited by the small number of misclassification events. Due to the exploratory nature of the study, the small sample size of the questionnaire and the sequential deployment structure, the results should be considered preliminary evidence. Nevertheless, the findings suggest that expressing vulnerability in an anthropomorphic way may be a promising approach for communicating uncertainty in behavior change systems. Full article
(This article belongs to the Special Issue Advances in Human–Computer Interaction and Intelligent Interface Design)
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16 pages, 1715 KB  
Article
A Human–System Coupling Framework for Collective Synchronization Through Computational Interpretation of Bodily Energy
by Hsuan-Cheng Lin
Appl. Sci. 2026, 16(7), 3516; https://doi.org/10.3390/app16073516 - 3 Apr 2026
Viewed by 360
Abstract
This paper proposes a human–system coupling framework for understanding interactive environments in which embodied human activity is continuously translated into perceptual feedback through computational systems. Rather than conceptualizing interaction as a sequence of discrete commands, the framework interprets interactive systems as perceptual mediation [...] Read more.
This paper proposes a human–system coupling framework for understanding interactive environments in which embodied human activity is continuously translated into perceptual feedback through computational systems. Rather than conceptualizing interaction as a sequence of discrete commands, the framework interprets interactive systems as perceptual mediation environments linking bodily action, computational interpretation, and perceptual response. The framework is illustrated through the EchoCycle installation, which converts mechanical energy generated by cycling into real-time audiovisual feedback. Observations from the installation suggest that participants initially engage in exploratory behavior and gradually develop more stable activity patterns as they adapt to the feedback provided by the system. In shared interaction contexts, the perceptual environment reflects collective activity, creating conditions under which behavioral alignment among participants may emerge. By framing interactive systems as continuous perception–action loops, this study highlights how computational mediation can shape both individual adaptation and collective interaction dynamics. The proposed framework contributes to human–computer interaction and interactive system design by offering an integrated perspective on embodied action, perceptual feedback, and responsive environments. Full article
(This article belongs to the Special Issue Advances in Human–Computer Interaction and Intelligent Interface Design)
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14 pages, 1046 KB  
Article
High-Performance WebGL-Based Visual Analytics Framework for Large-Scale Behavioral Embeddings: System Architecture and Rendering Optimization
by Junghee Jo and Junho Choi
Appl. Sci. 2026, 16(7), 3307; https://doi.org/10.3390/app16073307 - 29 Mar 2026
Viewed by 1165
Abstract
As high-dimensional behavioral datasets grow, interactive 3D visualization is increasingly limited by rendering and annotation bottlenecks rather than data availability. Existing web-based tools often degrade sharply under large node counts, making real-time exploration impractical. We propose a web-based 3D point-cloud visualization system optimized [...] Read more.
As high-dimensional behavioral datasets grow, interactive 3D visualization is increasingly limited by rendering and annotation bottlenecks rather than data availability. Existing web-based tools often degrade sharply under large node counts, making real-time exploration impractical. We propose a web-based 3D point-cloud visualization system optimized for rendering performance under condition-locked experimental settings (load × guidance). To enable reproducible evaluation without proprietary data, the system uses a synthetic surrogate dataset with clustered structure and three node types (user/attribute/action) and provides guided/free exploration workflows with interaction logging. We report a technical benchmark across two load scales (N = 500 vs. N = 5000) and two modes (guided vs. free). Under the high-load setting (N = 5000), the system maintains real-time rendering performance while supporting interactive selection (point/cluster), tooltips/inspector, and session logging. We discuss practical strategies for controlling on-screen annotations under overload conditions and outline limitations and future work for validating the approach on real-world embeddings. Full article
(This article belongs to the Special Issue Advances in Human–Computer Interaction and Intelligent Interface Design)
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