Gomez Romero Borquez, Jesus Alberto

Preferred name

Alternative Name

jagomez

Main Affiliation

ORCID

0000-0003-0459-2384

Scopus Author ID

57218312234

Researcher ID

JDU-9385-2023

Now showing 1 - 7 of 7

Some of the metrics are blocked by your
consent settings
Genre-Sensitive Prediction of Emotional Arousal in Virtual Reality: A Neural Modeling Approach Using Skin Conductance Peaks
(Institute of Electrical and Electronics Engineers (IEEE), 2025-12)
;
José Varela-Aldás
;
Demián Velasco Gómez Llanos
;
Santiago Arreola Munguía
;
Marco Antonio Manjarrez Fernandez
Some of the metrics are blocked by your
consent settings
Implications for Serious Game Design: Quantification of Cognitive Stimulation in Virtual Reality Puzzle Games through MSC and SpEn EEG Analysis
(2024)
;
;
;
Castillo-Soria, Francisco R.
;
Maciel-Barboza F.M.
<jats:p>This paper investigates the cognitive stimulation experienced by players engaging in virtual reality (VR) puzzle games through the analysis of electroencephalography (EEG) data. The study employs magnitude-square coherence (MSC) and spectral entropy (SpEn) metrics to quantify neural activity patterns associated with problem-solving processes during gameplay. Results reveal unique coherence and entropy profiles across different VR gaming tasks, with Tetris gameplay eliciting heightened coherence and entropy values compared to other games. Specifically, Tetris demonstrates increased coherence between frontal and temporal brain regions, indicative of enhanced visuospatial processing and decision making. These findings underscore the importance of considering both spectral coherence and entropy when assessing the cognitive effects of video game tasks on brain activity. Insights from this study may inform the design of serious VR games aimed at promoting cognitive development and problem-solving skills in players.</jats:p>
5
Some of the metrics are blocked by your
consent settings
Mapping EEG Alpha Activity: Assessing Concentration Levels during Player Experience in Virtual Reality Video Games
(2023)
;
;
<jats:p>This work presents a study in which the cognitive concentration levels of participants were evaluated using electroencephalogram (EEG) measures while they were playing three different categories of virtual reality (VR) video games: Challenging Puzzlers, Casual Games, and Exergames. Thirty-one voluntary participants between the ages of 17 and 35 were recruited. EEG data were processed to analyze the brain’s electrical activity in the alpha band. The values of power spectral density (PSD) and individual alpha frequency (IAF) of each participant were compared to detect changes that could indicate a state of concentration. Additionally, frontal alpha asymmetry (FAA) between the left and right hemispheres of the brain was compared. The results showed that the Exergame category of video games elicited higher average cognitive concentration in players, as indicated by the IAF and FAA values. These findings contribute to understanding the cognitive effects of VR video games and their implications for designing and developing VR experiences to enhance cognitive abilities.</jats:p>
Scopus© Citations 5 3 2
Some of the metrics are blocked by your
consent settings
Neurogaming in Virtual Reality: A Review of Video Game Genres and Cognitive Impact
(2024)
;
;
;
Ramon A. Briseño
;
José Varela-Aldás
<jats:p>This work marks a significant advancement in the field of cognitive science and gaming technology. It offers an in-depth analysis of the effects of various video game genres on brainwave patterns and concentration levels in virtual reality (VR) settings. The study is groundbreaking in its approach, employing electroencephalograms (EEGs) to explore the neural correlates of gaming, thus bridging the gap between technology, psychology, and neuroscience. This review enriches the dialogue on the potential of video games as a therapeutic tool in mental health. The study’s findings illuminate the capacity of different game genres to elicit varied brainwave responses, paving the way for tailored video game therapies. This review contributes meaningfully to the state of the art by offering empirical insights into the interaction between gaming environments and brain activity, highlighting the potential applications in therapeutic settings, cognitive training, and educational tools. The findings are especially relevant for developing VR gaming content and therapeutic games, enhancing the understanding of cognitive processes, and aiding in mental healthcare strategies.</jats:p>
Scopus© Citations 1 12
Some of the metrics are blocked by your
consent settings
Audio’s Impact on Deep Learning Models: A Comparative Study of EEG-Based Concentration Detection in VR Games
(MDPI AG, 2025-10-29)
;
;
;
;
Francisco R. Castillo-Soria
This study investigates the impact of audio feedback on cognitive performance during VR puzzle games using EEG analysis. Thirty participants played three different VR puzzle games under two conditions (with and without audio) while their brain activity was recorded. To analyze concentration levels and neural engagement patterns, we employed spectral analysis combined with a preprocessing algorithm and an optimized Deep Neural Network (DNN) model. The proposed processing stage integrates feature normalization, automatic labeling based on Principal Component Analysis (PCA), and Gamma band feature extraction, transforming concentration detection into a supervised classification problem. Experimental validation was conducted under the two gaming conditions in order to evaluate the impact of multisensory stimulation on model performance. The results show that the proposed approach significantly outperforms traditional machine learning classifiers (SVM, LR) and baseline deep learning models (DNN, DGCNN), achieving a 97% accuracy in the audio scenario and 83% without audio. These findings confirm that auditory stimulation reinforces neural coherence and improves the discriminability of EEG patterns, while the proposed method maintains a robust performance under less stimulating conditions.
Some of the metrics are blocked by your
consent settings
Electrodermal Response Patterns and Emotional Engagement Under Continuous Algorithmic Video Stimulation: A Multimodal Biometric Analysis
(MDPI AG, 2026-01-18)
;
;
;
David Contreras-Tiscareno
;
Diego Sebastian Montoya-Rodriguez
Excessive use of short-form video platforms such as TikTok has raised growing concerns about digital addiction and its impact on young users’ emotional well-being. This study examines the relationship between continuous TikTok exposure and emotional engagement in young adults aged 20–23 through a multimodal experimental design. The purpose of this research is to determine whether emotional engagement increases, remains stable, or declines during prolonged exposure and to assess the degree of correspondence between facially inferred engagement and physiological arousal. To achieve this, multimodal biometric data were collected using the iMotions platform, integrating galvanic skin response (GSR) sensors and facial expression analysis via Affectiva’s AFFDEX SDK 5.1. Engagement levels were binarized using a logistic transformation, and a binomial test was conducted. GSR analysis, merged with a 50 ms tolerance, revealed no significant differences in skin conductance between engaged and non-engaged states. Findings indicate that although TikTok elicits strong initial emotional engagement, engagement levels significantly decline over time, suggesting habituation and emotional fatigue. The results refine our understanding of how algorithm-driven, short-form content affects users’ affective responses and highlight the limitations of facial metrics as sole indicators of physiological arousal. Implications for theory include advancing multimodal models of emotional engagement that account for divergences between expressivity and autonomic activation. Implications for practice emphasize the need for ethical platform design and improved digital well-being interventions. The originality and value of this study lie in its controlled experimental approach that synchronizes facial and physiological signals, offering objective evidence of the temporal decay of emotional engagement during continuous TikTok use and underscoring the complexity of measuring affect in highly stimulating digital environments.
Some of the metrics are blocked by your
consent settings
Engagement in the Cinematography of Videogames: Proposal of an Algorithm for Colors and Foci of Attention Analysis
(2020)
;
Scopus© Citations 1 10 2

Gomez Romero Borquez, Jesus Alberto

Filters

Settings

Sort By

Results per page