Advances in Human–Computer Intelligent Interaction

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (15 February 2026) | Viewed by 2150

Special Issue Editors


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Guest Editor
Computer Architecture Department, Polytechnic University of Catalonia, 08860 Barcelona, Spain
Interests: human–computer interaction; autonomous vehicles

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Guest Editor
Faculty of Telematics, University of Colima, Colima 28040, Mexico
Interests: autonomous vehicles; network management; human–computer interaction

Special Issue Information

Dear Colleagues,

The field of Human–Computer Intelligent Interaction (HCII) has emerged as a cornerstone in advancing seamless collaboration between humans and machines. Driven by breakthroughs in artificial intelligence, machine learning, natural language processing, and cognitive computing, this area seeks to bridge the gap between human intuition and computational efficiency. As intelligent systems become pervasive in domains such as healthcare, education, robotics, and smart environments, the need for innovative interaction methods is paramount. These advances not only enhance usability and accessibility but also redefine how humans and systems collaborate to solve complex problems. 

This Special Issue, “Advances in Human–Computer Intelligent Interaction”, aims to showcase cutting-edge research and applications that push the boundaries of human–computer synergy. The issue seeks to highlight research that is shaping the future of intelligent systems and their impact on society. 

Contributions are invited in, but not limited to, the following areas: 

  • Adaptive Interfaces: Innovations in dynamic interfaces that adjust to user preferences and contexts, exploring speech, gesture, haptic, and other input modalities for enriched experiences. 
  • Cognitive Computing: Systems that understand, reason, and learn in interaction settings. 
  • AI for Accessibility: Solutions enhancing usability for individuals with diverse needs. 
  • Trust and Ethics: Investigating transparency, trust, and ethical implications in HCII. 
  • Emotion Recognition and Response: Integrating affective computing to improve interaction quality. 
  • Human–Robot Collaboration: Advances in cooperative and assistive robotics. 
  • Applications in Critical Domains: HCII in healthcare, smart cities, education, and industrial automation. 

We encourage contributions that introduce novel methodologies, theoretical frameworks, and real-world applications. Research that integrates interdisciplinary approaches is particularly appreciated. 

We look forward to hearing from you.   

Dr. Angélica Reyes
Dr. Juan Antonio Guerrero-Ibañez
Guest Editors

Manuscript Submission Information

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Keywords

  • human–computer interaction (HCI)
  • intelligent systems
  • artificial intelligence (AI)
  • cognitive computing
  • adaptive interfaces
  • human–robot collaboration

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Published Papers (1 paper)

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Research

26 pages, 1635 KB  
Article
Evaluating Player Stress and Motivation Through Biofeedback-Controlled Dynamic Difficulty Adjustment
by Atalay Oner and Enver Kucukkulahli
Electronics 2025, 14(19), 3870; https://doi.org/10.3390/electronics14193870 - 29 Sep 2025
Viewed by 1881
Abstract
This study researches the effects of a biofeedback-based Dynamic Difficulty Adjustment (DDA) system on player stress management in a survival-horror video game. For this purpose, a game titled Code: Terror was developed, in which players’ psychophysiological data—such as heart rate, stress level, and [...] Read more.
This study researches the effects of a biofeedback-based Dynamic Difficulty Adjustment (DDA) system on player stress management in a survival-horror video game. For this purpose, a game titled Code: Terror was developed, in which players’ psychophysiological data—such as heart rate, stress level, and voice level—were collected in real time through a smartwatch. Based on these data, game parameters were dynamically adjusted. The adaptation process was guided by the “Relax-to-win” model, which aims to make the game easier as players remain calm, using their level of relaxation as a baseline. A total of 40 participants were recruited and divided into two reciprocal groups: one group experienced the game solely with the DDA system activated, while the other played first with the DDA system disabled and then with it enabled. Player experience was evaluated using the Intrinsic Motivation Inventory (IMI) and the Challenge Originating from Recent Gameplay Interaction Scale (CORGIS). Results showed that the dynamic biofeedback system significantly enhanced intrinsic motivation and perceived challenge, while also reducing physiological arousal, indicating its effectiveness in promoting emotional regulation—the inclusion of both gameplay conditions for participants allowed for the collection of more consistent and meaningful data. The results suggest that biofeedback-driven DDA systems have the potential to enrich player experience both emotionally and motivationally. Furthermore, the findings highlight the potential of such adaptive biofeedback mechanisms to serve as intelligent medical decision support tools for stress management, mental health monitoring, and personalized intervention strategies. Full article
(This article belongs to the Special Issue Advances in Human–Computer Intelligent Interaction)
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