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Emerging Technologies in Innovative Human–Computer Interactions

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 December 2025 | Viewed by 968

Special Issue Editor


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Guest Editor
Department of Mechanical Engineering, National Taiwan University, Taipei 10617, Taiwan
Interests: human–computer interaction; virtual reality; augmented reality; haptic technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Human–computer interactions (HCIs) stand out as a multidisciplinary field dedicated to the design and utilization of computer technology, facilitating interactions with digital content. The continuous advancement of information technologies has propelled HCIs into a new dimension, urging the need to embrace cutting-edge technologies and foster innovation.

The focus of this Special Issue is to explore the application of emerging technologies in developing innovative HCI solutions. The topics covered include, but are not limited to, innovative interfaces in extended reality (VR, AR, and MR), tactile and haptic feedback systems in HCIs, brain–computer interfaces, wearable technologies, conversational artificial intelligence (AI), and machine learning (ML) in HCIs. Additionally, we explore the cognitive and emotional aspects of HCIs. This Special Issue welcomes comprehensive reviews and survey papers in addition to original research contributions.

Prof. Dr. Shana Smith
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 100 words) can be sent to the Editorial Office for announcement on this website.

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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
  • extended reality
  • brain-computer interface
  • wearable technologies
  • conversational artificial intelligence

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Published Papers (1 paper)

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Research

14 pages, 2643 KiB  
Article
A Novel Approach for Acute Mental Stress Mitigation Through Adapted Binaural Beats: A Pilot Study
by Matteo Raggi, Stefania Chiri, Silvestro Roatta, Rosita Rabbito and Luca Mesin
Appl. Sci. 2025, 15(10), 5742; https://doi.org/10.3390/app15105742 - 21 May 2025
Viewed by 7
Abstract
Stress significantly impacts our society, making strategies for its mitigation necessary. A possible approach may involve binaural beats (BBs), i.e., an auditory stimulation obtained by presenting pure tones with slightly different frequencies to the user’s ears, resulting in a third phantom beat [...] Read more.
Stress significantly impacts our society, making strategies for its mitigation necessary. A possible approach may involve binaural beats (BBs), i.e., an auditory stimulation obtained by presenting pure tones with slightly different frequencies to the user’s ears, resulting in a third phantom beat (fBB). While studies in the literature investigate the effects of BBs at a constant stimulation frequency, with this pilot study, we present an innovative approach that adapts the beat frequency in real time within the theta range (4.0–8.0 Hz) to reduce acute mental stress. A stress index, obtained from the predictions of a random forest regressor, was considered to adjust the stimulation. The regressor considered features from an electrocardiogram (ECG) and the ECG-derived respiratory signal. Thirteen healthy subjects underwent a stressful protocol involving multiple mental arithmetic tasks during which constant (CBB) or adapted (ABB) stimulation occurred. Task performances like accuracy and reaction times were recorded. The results show that ABBs significantly lowered the average stress index (p<0.05) and heart rate (p<0.05) compared to CBBs. No statistically significant differences were detected in task performance. The results support the importance of adaptive and personalized approaches for mitigating stress. Future research is necessary to assess the goodness of our proposal, considering a larger sample, different stressors, and an objective and external assessment of stress (e.g., cortisol levels). Full article
(This article belongs to the Special Issue Emerging Technologies in Innovative Human–Computer Interactions)
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