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ARTÍCULO
TITULO

Cognitive Assessment Based on Electroencephalography Analysis in Virtual and Augmented Reality Environments, Using Head Mounted Displays: A Systematic Review

Foteini Gramouseni    
Katerina D. Tzimourta    
Pantelis Angelidis    
Nikolaos Giannakeas and Markos G. Tsipouras    

Resumen

The objective of this systematic review centers on cognitive assessment based on electroencephalography (EEG) analysis in Virtual Reality (VR), Augmented Reality (AR) and Mixed Reality (MR) environments, projected on Head Mounted Displays (HMD), in healthy individuals. A range of electronic databases were searched (Scopus, ScienceDirect, IEEE Explore and PubMed), using PRISMA research method and 82 experimental studies were included in the final report. Specific aspects of cognitive function were evaluated, including cognitive load, immersion, spatial awareness, interaction with the digital environment and attention. These were analyzed based on various aspects of the analysis, including the number of participants, stimuli, frequency bands range, data preprocessing and data analysis. Based on the analysis conducted, significant findings have emerged both in terms of the experimental structure related to cognitive neuroscience and the key parameters considered in the research. Also, numerous significant avenues and domains requiring more extensive exploration have been identified within neuroscience and cognition research in digital environments. These encompass factors such as the experimental setup, including issues like narrow participant populations and the feasibility of using EEG equipment with a limited number of sensors to overcome the challenges posed by the time-consuming placement of a multi-electrode EEG cap. There is a clear need for more in-depth exploration in signal analysis, especially concerning the a, ß, and ? sub-bands and their role in providing more precise insights for evaluating cognitive states. Finally, further research into augmented and mixed reality environments will enable the extraction of more accurate conclusions regarding their utility in cognitive neuroscience.

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