applsci-logo

Journal Browser

Journal Browser

Future Human–Technology Interactions and Their Intelligent Applications: 2nd Edition

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

Deadline for manuscript submissions: 30 June 2026 | Viewed by 692

Special Issue Editor


E-Mail Website
Guest Editor
School of Science, Loughborough University, Loughborough LE11 3TU, UK
Interests: robotics; pattern recognition; brain-computer interfaces; applied machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The domain of human–technology interaction stands at the forefront of innovation, driving progress in fields such as affective intelligence, applied machine learning, assistive technology, and robotics. This synergy between human and machine holds immense promise for enhancing various aspects of human life, spanning healthcare, education, smart cities, and beyond. Within this dynamic landscape, the exploration of interdisciplinary topics has become imperative, paving the way for groundbreaking research and transformative applications. 

This Special Issue (SI) endeavors to delve into the multifaceted dimensions of human–technology interaction, with a focus on advancing understanding and fostering innovation across diverse domains. Potential themes for original research contributions include, but are not limited to, the following: 

  • Applied machine learning applications in healthcare, education, and smart cities;
  • Human–robot interaction (HRI) and its implications for enhancing human capabilities and experiences;
  • Affective intelligence encompassing affective robotics, affective computing, and emotion recognition;
  • Behavior analysis and its role in understanding human behavior and guiding technological interventions;
  • Social robotics and its potential to augment social interactions and address societal challenges;
  • Assistive technology innovations aimed at improving accessibility and quality of life for individuals with diverse needs;
  • The integration of affective intelligence and machine learning for personalized and adaptive systems;
  • Human–machine interaction modalities, including brain–computer interfaces, speech recognition, and biometrics;
  • Ethical considerations and societal implications of advancing human–technology interactions.

We invite researchers from academia, industry, and beyond to contribute their original research, reviews, and perspectives to this SI, facilitating interdisciplinary discourse and catalyzing impactful advancements at the interface between humans and technology.

Dr. Diego Resende Faria
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-blind 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

  • advancements in affective intelligence
  • applied machine learning
  • assistive technology
  • robotics for health, education, and smart cities

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.

Related Special Issue

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Other

19 pages, 2238 KB  
Systematic Review
Wearable Gait Assessment for Diabetes: A Systematic Survey
by Ahmed Amarak, Maria Valero and Valentina Nino
Appl. Sci. 2026, 16(6), 2956; https://doi.org/10.3390/app16062956 - 19 Mar 2026
Viewed by 475
Abstract
This systematic review examines how gait analysis has been applied to understand, detect, and manage diabetes and its complications, with a focus on wearable sensor technologies and computational methods. A total of 30 studies were identified from IEEE Xplore, Scopus, and Google Scholar [...] Read more.
This systematic review examines how gait analysis has been applied to understand, detect, and manage diabetes and its complications, with a focus on wearable sensor technologies and computational methods. A total of 30 studies were identified from IEEE Xplore, Scopus, and Google Scholar databases using systematic search and screening processes. Data extraction followed a structured framework addressing research questions on gait applications, technologies, and associated parameters. Results indicate that wearable sensor technologies, coupled with advanced computational modeling and machine learning, can capture meaningful gait alterations associated with long-term metabolic dysregulation and neuropathic changes. Applications range from diabetic neuropathy detection and foot ulcer prevention to intervention evaluation and early biomarker identification. The review highlights current progress and outlines future directions toward predictive gait analytics that may serve as indirect, secondary markers of metabolic status and improve diabetes care outcomes. Furthermore, this synthesis provides evidence for integrating wearable gait assessment into diabetes management protocols, potentially enabling early detection of complications, personalized intervention strategies, and non-invasive monitoring approaches that complement traditional glucose measurements. Full article
Show Figures

Graphical abstract

Back to TopTop