New Advances of Brain-Computer and Human-Robot Interaction

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: 15 November 2024 | Viewed by 936

Special Issue Editors


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Guest Editor
Departamento de Ingeniería Eléctrica, Electrónica, Automática y Comunicaciones, Universidad de Castilla-La Mancha, 02071 Albacete, Spain
Interests: neurocognitive deficits; brain stimulation; electroencephalography; brain computer interface; machine learning; deep learning; neural networks; signal processing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, 02071 Albacete, Spain
Interests: emotional analysis; brain stimulation; electroencephalography; brain computer interface; machine learning; deep learning; neural networks; signal processing; electrodermal activity

Special Issue Information

Dear Colleagues,

In recent years, remarkable strides have been made in the fields of brain–computer interaction (BCI) and human–robot interaction (HRI), ushering in an era of unprecedented connectivity between humans and technology. BCI has undergone a revolution, opening exciting possibilities for individuals with disabilities and expanding our understanding of the human brain. Brain–computer interfaces allow for direct communication between the human brain and external devices, offering new avenues to enable those with paralysis or neurodegenerative diseases to regain control over their environment. With applications in neurorehabilitation, communication, and entertainment, BCI has unveiled the potential to enhance human capabilities beyond traditional means. Neuroscientists and engineers are constantly refining technology, making it more accessible and user-friendly, which promises to shape the way we interact with the digital world.

Simultaneously, HRIs have evolved to create more intuitive and natural interactions between humans and robots, blurring the lines between man and machine. With the advent of advanced sensors, machine learning algorithms, and artificial intelligence, robots can now perceive and respond to human emotions, gestures, and speech with greater accuracy and empathy. These advancements have engendered the use of HRI in various domains: from healthcare to manufacturing; in making robots—not mere tools, but companions and caregivers; and enhancing our quality of life.

These new advances in BCI and HRI mark a significant leap forward in our relationship with technology, with profound implications for society. As the boundaries between humans and machines continue to blur, it is essential to navigate the ethical and social implications of these technologies while embracing the opportunities they offer for a brighter, more inclusive, and interconnected future.

This Special Issue invites original research papers that report on recent advancements in BCI and HRI across a wide range of investigations and their practical applications. Prospective authors are invited to submit high-quality contributions and reviews.

Dr. Alejandro L. Borja
Dr. Roberto Sanchez-Reolid
Guest Editors

Manuscript Submission Information

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Keywords

  • signal processing
  • electroencephalography
  • brain–computer interface
  • neural signal processing techniques (EEG, MEG, MRI/fMRI, PET, fNIRS)
  • machine learning
  • deep learning
  • neural networks
  • neuroscience

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Published Papers (1 paper)

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Research

19 pages, 5748 KiB  
Article
Research on an Indoor Light Environment Comfort Evaluation Index Based on Electroencephalogram and Pupil Signals
by Peiyuan Tian, Guanghua Xu, Chengcheng Han, Xiaowei Zheng, Kai Zhang, Chenghang Du, Xun Zhang, Fan Wei, Yunhao Ma, Sicong Zhang and Qingqiang Wu
Electronics 2024, 13(17), 3411; https://doi.org/10.3390/electronics13173411 - 27 Aug 2024
Viewed by 493
Abstract
With the development of modern technology, many people work for a long time around various artificial light sources and electronic equipment, causing them to feel discomfort in their eyes and even eye diseases. The industry currently lacks an objective quantitative environmental–visual comfort index [...] Read more.
With the development of modern technology, many people work for a long time around various artificial light sources and electronic equipment, causing them to feel discomfort in their eyes and even eye diseases. The industry currently lacks an objective quantitative environmental–visual comfort index that combines subjective and objective indicators. For this experiment, objective eye movement and electroencephalogram (EEG) signals were collected in combination with a subjective questionnaire survey and a preference inquiry for comprehensive data mining. Finally, the results on a Likert scale show that high screen brightness can reduce the visual fatigue of subjects under high illuminance and high correlated color temperature (CCT). Pupil data show that, under medium and high ambient illuminance, visual perception sensitivity is more likely to be stimulated, and visual fatigue is more likely to deepen. EEG data show that visual fatigue is related to illuminance and screen brightness. On this basis, this study proposes a new evaluation index, the visual comfort level (0.6404 average at a low screen brightness, 0.4218 average at a medium screen brightness, and 0.5139 average at a high screen brightness), where a higher score for the visual comfort level represents a better visual experience. The visual comfort level provides a useful reference for enhancing the processing of multi-dimensional and biomedical signals and protecting the eyes. Full article
(This article belongs to the Special Issue New Advances of Brain-Computer and Human-Robot Interaction)
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