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Computers
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Innovative Research in Human–Computer Interactions
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Innovative Research in Human–Computer Interactions

A special issue of Computers (ISSN 2073-431X). This special issue belongs to the section "Human–Computer Interactions".

Deadline for manuscript submissions: 30 December 2026 | Viewed by 9253

Editor

Dr. Makuochi Samuel Nkwo

E-Mail Website
Guest Editor
School of Computing and Mathematical Science, Faculty of Engineering and Science, University of Greenwich, London SE10 9LS, UK
Interests: human-computer interaction; responsible AI; trustworthy AI; AI ethics; user experience design; persuasive system design; design thinking; technologies for health & wellness, education, ecommerce, workplace, and environmental sustainability

Special Issue Information

Dear Colleagues,

This Special Issue will showcase innovative contributions that advance developments in research at the intersection of human–computer interactions (HCIs) and other emerging digital technologies. The resurgence and pervasive nature of research in these research domains reflects the need to develop adaptive and context-aware interfaces that collaboratively interact with users’ cognitive, physical, and emotional states across diverse environments, alongside inclusive and intuitive systems that are ethical and enhance user experience and capabilities. The goal is to shape future technologies that are responsible, foster trust, and promote meaningful partnerships between users and evolving autonomous smart systems.

Research in this area has attracted widespread interest from academia, product design, and industry stakeholders. There is a growing need for credible venues to disseminate evidence-based and impactful outputs to a wider audience. This Special Issue bridges this gap by offering a platform that covers recent and relevant advancements in the analyses, design, development, and evaluation of human-centric intelligent systems and their potential applications to our everyday lives. While we welcome submissions that present novel systematic analysis and evaluation, theories and methods, system modelling and designs, and empirical studies and essays on new technology developments, authors are strongly encouraged to demonstrate how their works contribute to the wider concept of human–computer interactions (HCIs) and their applications. Therefore, relevant topics include but are not limited to the following:

  • Human–artificial intelligence (human–AI) interactions and human–machine interfaces;
  • Ubiquitous and pervasive computing;
  • Augmented reality (AR) and virtual reality (VR);
  • Brain–computer interfaces (BCIs) and neurotechnology;
  • Tangible and embodied interfaces;
  • Bio-sensing and wearable technology;
  • Robotics and human–robot interaction;
  • Ethics, trust, safety, and privacy in emerging technology interfaces;
  • Borderless and sociocultural research in HCIs;
  • Future-focused research in HCIs.

All submitted papers will undergo the standard peer-review procedure. Accepted papers will be published in the open access journal Computers and on the website of this Special Issue.

Dr. Makuochi Samuel Nkwo
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. Computers is an international peer-reviewed open access monthly 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 1800 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-artificial intelligence (Human-AI) interaction & human-machine interfaces
  • ubiquitous & Pervasive Computing
  • augmented Reality (AR) & Virtual Reality (VR)
  • brain Computer Interfaces (BCI) & Neurotechnology
  • tangible & embodied interfaces
  • bio-sensing & wearable technology
  • robotics & human-robot interaction
  • ethics, trust, safety and privacy in emerging technology interfaces
  • borderless & Sociocultural Research in HCI
  • future-Focused Research in HCI

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

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

Published Papers (8 papers)

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Research

Jump to: Review, Other

34 pages, 13771 KB  
Article
Rehabilitation Engineering Approach to Frozen Shoulder Treatment: Performance Analysis Using Landmark-Based Motion Detection and Assistive Feedback Systems
by Thanawat Srikaewsiew, Sarunya Kanjanawattana, Nuntawut Kaoungku, Parin Sornlertlamvanich and Komsan Srivisut
Computers 2026, 15(7), 448; https://doi.org/10.3390/computers15070448 - 15 Jul 2026
Viewed by 768
Abstract
This paper presents a preliminary technical feasibility study of a landmark-based motion analysis system designed for potential future application in home-based rehabilitation monitoring for frozen shoulder (adhesive capsulitis), developed using computer vision (CV) and human–computer interaction (HCI) principles. The proposed system utilizes real-time [...] Read more.
This paper presents a preliminary technical feasibility study of a landmark-based motion analysis system designed for potential future application in home-based rehabilitation monitoring for frozen shoulder (adhesive capsulitis), developed using computer vision (CV) and human–computer interaction (HCI) principles. The proposed system utilizes real-time body landmark detection to quantify shoulder joint kinematics and provide rule-based automated feedback on exercise execution. The system combines automated and manual components: while shoulder angle assessment, cosine similarity analysis, and keyframe matching are automated, manual researcher input is required to define keyframes corresponding to movement states (start, midpoint, peak) for each therapeutic pose. The CV-driven perception is translated into HCI output, including quantitative movement scores and rule-based feedback indicators, demonstrating the technical potential for objective evaluation of rehabilitation exercise execution without specialized wearable sensors. Technical validation was conducted with 14 healthy volunteers (not frozen shoulder patients) executing standardized shoulder rehabilitation activities, demonstrating shoulder angle measurement with an overall mean absolute error (MAE) of 7.03° against general goniometry and 6.61° against clinical goniometry (RMSE: 8.50° and 8.79°, respectively). Movement similarity classification achieved F1-scores ranging from 0.870 (flexion) to 1.0 (internal rotation) when compared against expert evaluation, though these results are based on a controlled and largely imbalanced dataset with limited incorrect movement examples. The system additionally incorporates a facial expression recognition (FER) module, previously developed and validated in the authors’ prior work, as a supplementary component to support future integration of pain monitoring; this module was not independently validated in the present study. This preliminary technical feasibility study contributes to rehabilitation engineering by demonstrating the potential of semi-automated CV-based motion analysis and rule-based HCI feedback for shoulder movement assessment. The findings indicate technical feasibility for future investigation in home-based exercise monitoring; however, clinical utility cannot be claimed at this stage, as validation with actual frozen shoulder patient cohorts is required. Full article
(This article belongs to the Special Issue Innovative Research in Human–Computer Interactions)
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19 pages, 3533 KB  
Article
Immersive VR-MoCap for Creative Motion Design in Character Animation Training: A Classroom-Based Comparative Study
by Xinyi Jiang, Muying Luo, Zainuddin Ibrahim, Azlan Abdul Aziz and Azhar Jamil
Computers 2026, 15(5), 284; https://doi.org/10.3390/computers15050284 - 30 Apr 2026
Viewed by 861
Abstract
Although motion capture has become integral to contemporary animation pipelines, university teaching still asks students to learn motion largely through screen-based keyframing. To address this gap, this classroom-based comparative study evaluated one structured motion-design lesson within an immersive MoCap-supported training module. Sixty-eight undergraduates [...] Read more.
Although motion capture has become integral to contemporary animation pipelines, university teaching still asks students to learn motion largely through screen-based keyframing. To address this gap, this classroom-based comparative study evaluated one structured motion-design lesson within an immersive MoCap-supported training module. Sixty-eight undergraduates in a computer animation course completed the same task in either a Keyframe condition (n = 33) or a VR-MoCap condition (n = 35), with instructional delivery mode as the only difference. Creative performance was assessed in originality, fluency, aesthetic quality, clarity, and a composite score. MANOVA revealed a significant multivariate effect of condition (Pillai’s trace = 0.454, F(4, 63) = 13.12, p < 0.001). Relative to keyframe instruction, VR-MoCap produced significantly higher originality, fluency, clarity, and composite performance, whereas aesthetic quality did not differ significantly. Supplementary group-interview responses further indicated that students experienced the immersive condition as more engaging, more intuitive, and better suited to immediate feedback and embodied movement exploration. Immersive VR-MoCap appears most useful in the early phases of motion design and is better understood as complementing, rather than replacing, conventional keyframe training. Full article
(This article belongs to the Special Issue Innovative Research in Human–Computer Interactions)
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28 pages, 1952 KB  
Article
The Art Nouveau Path: Requirements Engineering and Traceability for City-Scale In-the-Wild Mobile Augmented Reality Learning Services
by João Ferreira-Santos and Lúcia Pombo
Computers 2026, 15(4), 243; https://doi.org/10.3390/computers15040243 - 15 Apr 2026
Viewed by 758
Abstract
City-scale augmented reality (AR) learning paths are outdoor, multi-stop educational routes delivered through mobile devices in public space. This paper examines the Art Nouveau Path, a mobile AR game (MARG) route in Aveiro, Portugal, as a deployable learning service. The focus is [...] Read more.
City-scale augmented reality (AR) learning paths are outdoor, multi-stop educational routes delivered through mobile devices in public space. This paper examines the Art Nouveau Path, a mobile AR game (MARG) route in Aveiro, Portugal, as a deployable learning service. The focus is on implementation requirements and traceability rather than learning outcomes. The analysis combined profiling of eight points of interest (POIs) and 36 tasks, group-session logs from 118 sessions, and teacher-facing evidence from a validation workshop (T1-VAL, N = 30) and on-site observation (T2-OBS, N = 24). Open-text responses were segmented into meaning units and coded with an eight-determinant taxonomy, with good intercoder reliability (Krippendorff’s alpha = 0.83). Logs and the post-path questionnaire (S2-POST, N = 439) were used only to describe enactment feasibility and data integrity. The strongest determinants concerned onboarding and legibility, marker robustness and recovery, and curriculum alignment, together with safety and fallback needs. These signals were translated into 18 testable requirements linked to six transfer artefacts for enactment, maintenance, incident handling, and fallback. Overall, the study provides an implementation-oriented specification to support auditability, replication, and transfer in city-scale AR learning services. Full article
(This article belongs to the Special Issue Innovative Research in Human–Computer Interactions)
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13 pages, 1027 KB  
Article
Predicting Cybersickness in Virtual Reality from Head–Torso Kinematics Using a Hybrid Convolutional–Recurrent Network Model
by Ala Hag, Houshyar Asadi, Mohammad Reza Chalak Qazani, Thuong Hoang, Ambarish Kulkarni, Stefan Greuter and Saeid Nahavandi
Computers 2026, 15(3), 193; https://doi.org/10.3390/computers15030193 - 17 Mar 2026
Cited by 1 | Viewed by 1076
Abstract
Motion sickness (MS) is a prevalent condition that can significantly degrade user comfort and immersion, particularly in virtual reality (VR) environments. Accurate prediction models are essential for early detection and mitigation of MS symptoms, thereby improving the overall VR experience. Most existing approaches [...] Read more.
Motion sickness (MS) is a prevalent condition that can significantly degrade user comfort and immersion, particularly in virtual reality (VR) environments. Accurate prediction models are essential for early detection and mitigation of MS symptoms, thereby improving the overall VR experience. Most existing approaches rely on bio-physiological data acquired through body-mounted sensors, which may restrict user mobility and diminish immersion. This study proposes a less intrusive alternative, leveraging head and torso kinematic data for MS prediction. We introduce a hybrid Convolutional–Recurrent Neural Network (C-RNN) designed to capture both spatial and temporal features for enhanced classification accuracy. Using a dataset of 40 participants, the proposed C-RNN outperformed traditional machine learning models—including Support Vector Machines (SVMs), k-Nearest Neighbors (KNN), Decision Trees (DT), and a baseline Recurrent Neural Network (RNN)—across multiple evaluation metrics. The C-RNN achieved 85.63% accuracy, surpassing SVM (60%), KNN (73.75%), DT (74.38%), and RNN (81.88%), with corresponding gains in precision, recall, F1-score, and ROC AUC. These results demonstrate that head–torso motion patterns provide sufficient predictive signal for accurate MS detection, offering a non-intrusive, efficient alternative to physiological sensing that supports improved comfort and sustained immersion in VR. Full article
(This article belongs to the Special Issue Innovative Research in Human–Computer Interactions)
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17 pages, 335 KB  
Article
A Macrocognitive Design Taxonomy for Simulation-Based Training Systems: Bridging Cognitive Theory and Human–Computer Interaction
by Jessica M. Johnson
Computers 2026, 15(2), 110; https://doi.org/10.3390/computers15020110 - 6 Feb 2026
Cited by 1 | Viewed by 911
Abstract
Simulation-based training systems are increasingly deployed to prepare learners for complex, safety-critical, and dynamic work environments. While advances in computing have enabled immersive and data-rich simulations, many systems remain optimized for procedural accuracy and surface-level task performance rather than the macrocognitive processes that [...] Read more.
Simulation-based training systems are increasingly deployed to prepare learners for complex, safety-critical, and dynamic work environments. While advances in computing have enabled immersive and data-rich simulations, many systems remain optimized for procedural accuracy and surface-level task performance rather than the macrocognitive processes that underpin adaptive expertise. Macrocognition encompasses higher-order cognitive processes that are essential for performance transfer beyond controlled training conditions. When these processes are insufficiently supported, training systems risk fostering brittle strategies and negative training effects. This paper introduces a macrocognitive design taxonomy for simulation-based training systems derived from a large-scale meta-analysis examining the transfer of macrocognitive skills from immersive simulations to real-world training environments. Drawing on evidence synthesized from 111 studies spanning healthcare, industrial safety, skilled trades, and defense contexts, the taxonomy links macrocognitive theory to human–computer interaction (HCI) design affordances, computational data traces, and feedback and adaptation mechanisms shown to support transfer. Grounded in joint cognitive systems theory and learning engineering practice, the taxonomy treats macrocognition as a designable and computable system concern informed by empirical transfer effects rather than as an abstract explanatory construct. Full article
(This article belongs to the Special Issue Innovative Research in Human–Computer Interactions)
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Review

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35 pages, 3515 KB  
Review
Human–Computer Interaction in Smart Greenhouses: A Review of Interfaces, Technologies, and User-Centered Approaches
by Patricia Isabela Brăileanu
Computers 2025, 14(12), 553; https://doi.org/10.3390/computers14120553 - 12 Dec 2025
Cited by 4 | Viewed by 2426
Abstract
Human–computer interaction (HCI) is essential for optimizing smart greenhouse management and for fostering efficient and sustainable agricultural practices. A synthesis of recent advancements in diverse interfaces, including digital twins, virtual and augmented reality, mobile applications, and sensor-based controls, alongside the integration of artificial [...] Read more.
Human–computer interaction (HCI) is essential for optimizing smart greenhouse management and for fostering efficient and sustainable agricultural practices. A synthesis of recent advancements in diverse interfaces, including digital twins, virtual and augmented reality, mobile applications, and sensor-based controls, alongside the integration of artificial intelligence (AI), automation, and human–robot collaboration, was examined as part of advanced automation strategies. This study highlights the importance of user-centered and context-aware design to enhance usability, address challenges like simulation sickness, and cater to varied user demographics. Emphasis is placed on responsible, adaptive, and trustworthy interaction, ensuring effective decision support and promoting human–AI synergy. This review offers an integrated perspective on current developments, identifying pathways for future sustainable interaction design in controlled-environment agriculture. Full article
(This article belongs to the Special Issue Innovative Research in Human–Computer Interactions)
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Other

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29 pages, 2901 KB  
Systematic Review
The Use of Music and Virtual Reality in Health Contexts: A Scoping Review
by Anna Kandylidou, Georgios Spanos, Charalampos Karagiannidis, Filippos Vlachos, Alexandros Nizamis and Konstantinos Votis
Computers 2026, 15(8), 491; https://doi.org/10.3390/computers15080491 - 31 Jul 2026
Viewed by 671
Abstract
The integration of virtual reality (VR) and music is gaining attention in therapeutic and rehabilitative fields for its potential role in health-related interventions. This scoping review maps how music and VR have been combined across health contexts. Using databases such as PubMed and [...] Read more.
The integration of virtual reality (VR) and music is gaining attention in therapeutic and rehabilitative fields for its potential role in health-related interventions. This scoping review maps how music and VR have been combined across health contexts. Using databases such as PubMed and Scopus, peer-reviewed studies published between January 2009 and 15 February 2024 were analyzed following established review reporting procedures. Forty-five studies were reviewed, covering diverse patient populations, including those with neurological impairments and emotional disorders. The mapped literature reports outcomes related to patient engagement, motor function, stress reduction, emotional satisfaction, feasibility, and usability. However, because intervention methods and patient needs vary, and because the included studies are heterogeneous in design, population, and outcome measures, the findings should be interpreted as evidence mapping rather than definitive evidence of clinical effectiveness. By mapping the current evidence, this review may support future research and clinical practice by helping to refine VR and music interventions for specific health contexts, patient populations, and therapeutic goals. Full article
(This article belongs to the Special Issue Innovative Research in Human–Computer Interactions)
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34 pages, 1881 KB  
Systematic Review
Immersive Design Primitives and Decision-Making: A Systematic Review of Mechanisms and Outcomes
by Safa Elkefi, Salma Bhar, Achraf Tounsi and Duxiao Hao
Computers 2026, 15(7), 421; https://doi.org/10.3390/computers15070421 - 29 Jun 2026
Viewed by 405
Abstract
Immersive solutions are becoming a trending technology for decision support across fields such as transportation, healthcare, and urban planning. Despite their role, the mechanism by which they affect decision-making is unclear. Our study examines the design primitives in immersive technology that are manipulated [...] Read more.
Immersive solutions are becoming a trending technology for decision support across fields such as transportation, healthcare, and urban planning. Despite their role, the mechanism by which they affect decision-making is unclear. Our study examines the design primitives in immersive technology that are manipulated to influence decision-making and synthesizes how they operate to shape decision outcomes. We follow PRISMA guidelines to search. A total of 198 studies were included. Eight primitive families were identified, including perceptual realism, environmental structure, interactivity, temporal simulation, embodiment, social presence, multisensory integration, and other contextual manipulations. Mechanisms through which they impacted decision-making were classified into cognitive, perceptual, affective, motivational, social-influence, and behavioral-heuristic mechanisms. Perceptual realism, environmental structure, and interactivity emerged as the most frequently investigated primitives, while presence, risk perception, spatial cognition, engagement, and social influence were among the most reported mechanisms. Our results suggest that immersive technologies function as decision-shaping systems that alter how users perceive uncertainty, risks, consequences, and alternatives, highlighting the need for theory-driven research and evaluation in high-stakes decision contexts. Full article
(This article belongs to the Special Issue Innovative Research in Human–Computer Interactions)
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