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

Deadline for manuscript submissions: 30 March 2026 | Viewed by 5226

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Dr. Maura Mengoni

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Guest Editor

Department of Industrial Engineering and Mathematical Science (DIISM), Università Politecnica delle Marche, Piazza Roma, 22, 60121 Ancona, Italy
Interests: design theory; extended reality technologies; user experience; affective computing; human–machine interaction
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Special Issue Information

Dear Colleagues,

Human–machine interfaces are evolving into tools that facilitate more natural communications between humans and machines. Advances in extended-reality technologies and immersive wearable devices are enhancing the way we interact with computers, creating new dimensions for human–computer interaction (HCI).

In this Special Issue, we aim to provide a platform for researchers to share their latest findings in HCI, with a focus on the impact of XR technologies, including virtual, augmented, and mixed-reality applications. These technologies have the potential to significantly alter human perceptions of and interactions with systems across various societal domains.

Topics of interest for this Special Issue include, but are not limited to, the following:

Design for accessibility and inclusion in digital environments;
Innovative human–machine interaction for Industry 4.0;
Preservation and presentation of cultural heritage using XRT;
Development of methods and tools for user experience (UX) assessment;
New approaches to support UX design in digital spaces;
Design of intelligent and emotion-aware interfaces;
Multimodal and immersive interface design;
Haptics interfaces and their role in human–computer interaction.

Prof. Dr. Maura Mengoni
Guest Editor

Manuscript Submission Information

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Keywords

augmented reality
virtual reality
user-centered design
Industry 4.0
interaction design

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Published Papers (6 papers)

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Research

18 pages, 8897 KB

Open AccessArticle

Exploring User Engagement and Purchase Intentions in T-Shirt Retail Through Augmented Reality and Instagram Filters

by Christopher Girsang and Chin-Hung Teng

Appl. Sci. 2025, 15(18), 10161; https://doi.org/10.3390/app151810161 - 18 Sep 2025

Viewed by 777

Abstract

Augmented reality (AR) technologies—such as Instagram filters—bridge the digital and physical worlds by allowing users to virtually try on clothing, thereby reducing the risk of virus transmission. In the T-shirt retail industry, AR enables product personalization, decreases the need for physical production, minimizes textile waste, and lowers carbon emissions. It also benefits individuals with limited mobility or those who prefer shopping online. This study tested several hypotheses on 105 active Instagram filter users using filters from the ’Apprecio’ account on mobile devices. Data analyzed using the partial least squares method revealed that interactivity significantly influences both purchase intention and continued use of digital platforms. While hedonic and vivid features enhance the user experience, they have a limited impact on driving purchases or long-term engagement. Customers’ engagement and buying intent are more strongly shaped by practical and interactive elements. The study recommends that companies invest in developing interactive AR features to boost customer satisfaction and foster trust. Future research should involve larger participant samples and investigate specific interactive elements—such as virtual try-on tools—to better understand their impact on consumer behavior. This study highlights the critical role of interactivity in AR for delivering meaningful and engaging shopping experiences. Full article

(This article belongs to the Special Issue Advances in Human–Machine Interaction)

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18 pages, 3097 KB

Open AccessArticle

Deep Neural Network-Based Alignment of Virtual Reality onto a Haptic Device for Visuo-Haptic Mixed Reality

by Hyeonsu Kim, Hanbit Yong and Myeongjin Kim

Appl. Sci. 2025, 15(18), 10071; https://doi.org/10.3390/app151810071 - 15 Sep 2025

Viewed by 363

Abstract

Precise alignment between virtual reality (VR) and haptic interfaces is essential for delivering an immersive visuo-haptic mixed reality experience. Existing methods typically depend on markers, external trackers, or cameras, which can be intrusive and hinder usability. In addition, previous network-based approaches generally rely on image data for alignment. This paper introduces a deep neural network-based alignment method that eliminates the need for such external components. Unlike existing methods, our approach is designed based on coordinate transformation and leverages a network model for alignment. The proposed method utilizes the head-mounted display (HMD) position, fingertip position obtained via hand tracking, and the six-degrees-of-freedom (6-DOF) pose of a haptic device’s end-effector as inputs to a neural network model. A shared multi-layer perceptron and max pooling layer are employed to extract global feature vectors from the inputs, ensuring permutation invariance. The extracted feature vectors are then processed through fully connected layers to estimate the pose of the haptic device’s base. Experimental results show a mean positional error of 2.718 mm and the mean rotation error of 0.5330°, which equates to 1.3% relative to the haptic device’s maximum length. The proposed method demonstrates robustness against noise, demonstrating its applicability across various domains, including medical simulations, virtual prototyping, and interactive training environments. Full article

(This article belongs to the Special Issue Advances in Human–Machine Interaction)

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28 pages, 4693 KB

Open AccessArticle

Contactless Pulse Rate Assessment: Results and Insights for Application in Driving Simulators

by Đorđe D. Nešković, Kristina Stojmenova Pečečnik, Jaka Sodnik and Nadica Miljković

Appl. Sci. 2025, 15(17), 9512; https://doi.org/10.3390/app15179512 - 29 Aug 2025

Viewed by 489

Abstract

Remote photoplethysmography (rPPG) offers a promising solution for non-contact driver monitoring by detecting subtle blood flow-induced facial color changes from video. However, motion artifacts in dynamic driving environments remain key challenges. This study presents an rPPG framework that combines signal processing techniques before and after applying Eulerian Video Magnification (EVM) for pulse rate (PR) estimation in driving simulators. While not novel, the approach offers insights into the efficiency of the EVM method and its time complexity. We compare results of the proposed rPPG approach against reference Empatica E4 data and also compare it with existing achievements from the literature. Additionally, the possible bias of the Empatica E4 is further assessed using an independent dataset with both the Empatica E4 and the Faros 360 measurements. EVM slightly improves PR estimation, reducing the mean absolute error (MAE) from 6.48 bpm to 5.04 bpm (the lowest MAE (~2 bpm) was achieved under strict conditions) with an additional time required for EVM of about 20 s for 30 s sequence. Furthermore, statistically significant differences are identified between younger and older drivers in both reference and rPPG data. Our findings demonstrate the feasibility of using rPPG-based PR monitoring, encouraging further research in driving simulations. Full article

(This article belongs to the Special Issue Advances in Human–Machine Interaction)

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16 pages, 2647 KB

Open AccessArticle

“Habari, Colleague!”: A Qualitative Exploration of the Perceptions of Primary School Mathematics Teachers in Tanzania Regarding the Use of Social Robots

by Edger P. Rutatola, Koen Stroeken and Tony Belpaeme

Appl. Sci. 2025, 15(15), 8483; https://doi.org/10.3390/app15158483 - 30 Jul 2025

Viewed by 542

Abstract

The education sector in Tanzania faces significant challenges, especially in public primary schools. Unmanageably large classes and critical teacher–pupil ratios hinder the provision of tailored tutoring, impeding pupils’ educational growth. However, artificial intelligence (AI) could provide a way forward. Advances in generative AI can be leveraged to create interactive and effective intelligent tutoring systems, which have recently been built into embodied systems such as social robots. Motivated by the pivotal influence of teachers’ attitudes on the adoption of educational technologies, this study undertakes a qualitative investigation of Tanzanian primary school mathematics teachers’ perceptions of contextualised intelligent social robots. Thirteen teachers from six schools in both rural and urban settings observed pupils learning with a social robot. They reported their views during qualitative interviews. The results, analysed thematically, reveal a generally positive attitude towards using social robots in schools. While commended for their effective teaching and suitability for one-to-one tutoring, concerns were raised about incorrect and inconsistent feedback, language code-switching, response latency, and the lack of support infrastructure. We suggest actionable steps towards adopting tutoring systems and social robots in schools in Tanzania and similar low-resource countries, paving the way for their adoption to redress teachers’ workloads and improve educational outcomes. Full article

(This article belongs to the Special Issue Advances in Human–Machine Interaction)

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20 pages, 2901 KB

Open AccessArticle

Exploring the Use of Eye Tracking to Evaluate Usability Affordances: A Case Study on Assistive Device Design

by Vicente Bayarri-Porcar, Alba Roda-Sales, Joaquín L. Sancho-Bru and Margarita Vergara

Appl. Sci. 2025, 15(15), 8376; https://doi.org/10.3390/app15158376 - 28 Jul 2025

Viewed by 653

Abstract

This study explores the application of Eye-Tracking technology for the ergonomic evaluation of assistive device usability. Sixty-four participants evaluated six jar-opening devices in a two-phase study. First, the participants’ gaze was recorded while they viewed six rendered pictures of assistive devices, each shown in two different versions: with and without rubber in the grip area. Second, the participants physically interacted with the devices in a hands-on usability task. In both phases, participants rated the devices according to six usability affordances: robustness, comfort, easiness to grip, lid slippery, effort level, and easiness to use. Eye-Tracking metrics (fixation duration, number of fixations, and visit duration) correlated with the on-screen ratings, which aligned with ratings after using the physical devices. High ratings in comfort and effort level correlated with more visual attention to the grip area, where the rubber acted as key signifier. Heatmaps revealed the grip area as important for comfort and easiness to use and the lid area for robustness and slipperiness. These findings demonstrate the potential of Eye Tracking in usability studies, providing valuable insights for the ergonomic evaluation of assistive devices. Moreover, they highlight the suitability of Eye Tracking for early-stage design evaluation, offering objective metrics to guide design decisions and improve user experience. Full article

(This article belongs to the Special Issue Advances in Human–Machine Interaction)

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28 pages, 5802 KB

Open AccessArticle

A Seamless Technology Integration Framework for Elderly-Centered Interactive Systems: Design, Implementation, and Validation Through the Pillow Fight System

by Chor-Kheng Lim, Hung-Yu Chen and Xuan-Yu Chen

Appl. Sci. 2024, 14(23), 11306; https://doi.org/10.3390/app142311306 - 4 Dec 2024

Cited by 1 | Viewed by 1484

Abstract

The rapid aging of the global population has highlighted the urgent need for age-friendly technological solutions. However, our review of the existing studies revealed significant gaps between elderly users’ needs and the current smart technology products. While previous research has explored various aspects of elderly technology design, our systematic analysis indicated limitations, in terms of integrated frameworks, empirically validated interaction models, and long-term effectiveness evaluation. This study proposes a seamless technology framework for the development of elderly-centered interactive systems—named Pillow Fight—which we validated through a mixed-methods study of an innovative intergenerational gaming system. This research was conducted in two phases across 34 sites, with 1997 participants. Phase one (n = 659) established the framework’s effectiveness through systematic field testing, while phase two (n = 1338) validated its scalability and long-term benefits. The results highlight significant improvements in system usability scores (SUS), from individual use (77.85) to group activities (85.32), with intergenerational interaction achieving the highest scores (92.12). The integration of health monitoring features further enhanced learnability (94.12) usability (82.15). This study contributes to the design of technology for the elderly through (1) establishing an integrated theoretical framework for seamless technology integration, (2) developing and validating innovative intergenerational interaction models, and (3) providing empirical evidence through systematic field studies. These contributions could advance both theoretical understanding and practical applications while maintaining high user-friendliness. Full article

(This article belongs to the Special Issue Advances in Human–Machine Interaction)

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