Artificial Intelligence Applied to Brain-Computer Interfacing with Eye-Tracking for Computer-Aided Conceptual Architectural Design in Virtual Reality Using Neurofeedback

Author(s):  
Claudiu Barsan-Pipu
2020 ◽  
Author(s):  
David Harris ◽  
Mark Wilson ◽  
Tim Holmes ◽  
Toby de Burgh ◽  
Samuel James Vine

Head-mounted eye tracking has been fundamental for developing an understanding of sporting expertise, as the way in which performers sample visual information from the environment is a major determinant of successful performance. There is, however, a long running tension between the desire to study realistic, in-situ gaze behaviour and the difficulties of acquiring accurate ocular measurements in dynamic and fast-moving sporting tasks. Here, we describe how immersive technologies, such as virtual reality, offer an increasingly compelling approach for conducting eye movement research in sport. The possibility of studying gaze behaviour in representative and realistic environments, but with high levels of experimental control, could enable significant strides forward for eye tracking in sport and improve understanding of how eye movements underpin sporting skills. By providing a rationale for virtual reality as an optimal environment for eye tracking research, as well as outlining practical considerations related to hardware, software and data analysis, we hope to guide researchers and practitioners in the use of this approach.


2018 ◽  
Vol 15 (1) ◽  
pp. 6-28 ◽  
Author(s):  
Javier Pérez-Sianes ◽  
Horacio Pérez-Sánchez ◽  
Fernando Díaz

Background: Automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the number of new drugs that was expected. Computer- aided compounds search, known as Virtual Screening, has shown the benefits to this field as a complement or even alternative to the robotic drug discovery. There are different methods and approaches to address this problem and most of them are often included in one of the main screening strategies. Machine learning, however, has established itself as a virtual screening methodology in its own right and it may grow in popularity with the new trends on artificial intelligence. Objective: This paper will attempt to provide a comprehensive and structured review that collects the most important proposals made so far in this area of research. Particular attention is given to some recent developments carried out in the machine learning field: the deep learning approach, which is pointed out as a future key player in the virtual screening landscape.


2021 ◽  
Vol 27 (4) ◽  
Author(s):  
Francisco Lara

AbstractCan Artificial Intelligence (AI) be more effective than human instruction for the moral enhancement of people? The author argues that it only would be if the use of this technology were aimed at increasing the individual's capacity to reflectively decide for themselves, rather than at directly influencing behaviour. To support this, it is shown how a disregard for personal autonomy, in particular, invalidates the main proposals for applying new technologies, both biomedical and AI-based, to moral enhancement. As an alternative to these proposals, this article proposes a virtual assistant that, through dialogue, neutrality and virtual reality technologies, can teach users to make better moral decisions on their own. The author concludes that, as long as certain precautions are taken in its design, such an assistant could do this better than a human instructor adopting the same educational methodology.


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