Implications for Serious Game Design: Quantification of Cognitive Stimulation in Virtual Reality Puzzle Games through MSC and SpEn EEG Analysis

Abstract

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.

1. Introduction

Video games, enjoyed across various electronic platforms, have revolutionized digital entertainment and fueled significant growth in the entertainment industry. The foundational skills of coding and problem-solving, cultivated in early video games, have propelled the development of increasingly intricate and sophisticated gaming experiences. This advancement in the industry has led to the emergence of serious games (SGs) as mechanisms for skill development and enhancing learning or cognitive processes [1,2,3].

The earliest video games were crafted to tackle puzzles and other challenges. Further research supports that video games, especially those of challenging genres, can enhance problem-solving and communication skills, which are vital components of effective problem-solving [4]. Moreover, game design is rooted in problem-based learning models, further highlighting the centrality of problem-solving in the game design process. This approach, undertaken by video game designers, ensures that games are engaging and serve as effective learning tools by integrating clear tasks, complex scenarios, and actively constructed learning processes [5,6].

People of all ages and backgrounds widely enjoy video games, which can provide various benefits including relaxation, fun, and social connection [7,8]. The increasing commercial and popular appeal of video games has sparked a surge in research into their impact on a variety of topics, including motivation and emotion [8,9,10,11], the use of video games in education [12,13], and even their potential as tools in rehabilitation [14]. Furthermore, several studies demonstrate that playing video games can enhance visual–spatial skills, executive function, memory, and attention [15,16,17,18].

Electroencephalography (EEG), utilized to classify players’ expertise levels by analyzing brain activity, significantly enhances video game design. The EEG device MUSE 2, employed in various studies [1,2,3,19], records brain waves in specific regions like AF7, AF8, TP9, and TP10, each associated with distinct cognitive functions: AF7 and AF8, located in the frontal and temporal lobes, respectively, are involved in attention, language, and memory processes, while TP9 and TP10, in the parietal region, relate to visuospatial and sensory functions. Concurrently, the study of brain waves and their correlation with mental activities like problem-solving constitutes an active and complex area of research within neuroscience and cognitive neuroscience, wherein the brain engages in multiple cognitive functions such as attention, working memory, decision making, and reasoning.

1.1. Literature Review

In the realm of serious games, their emergence as innovative tools significantly contributes to the development of problem-solving skills across various domains. With clear objectives and interactivity, their design facilitates the acquisition of future skills, including problem-solving.

SGs are emerging as an educational tool of great importance, particularly in the healthcare field. As video games become an increasingly popular pastime transcending age barriers among users, incorporating health-related content becomes feasible. These games can provide a novel approach to health topics and address diverse socioeconomic contexts, as outlined in [20]. Serious games help enhance both technical and nontechnical skills in a safe and controlled environment. This aspect is emphasized in [21], where the authors highlight the role of serious games in surgical training and the medical field in general, underscoring their potential to reduce medical errors and associated healthcare costs. The significance of these games in medical education for training, prevention, rehabilitation, and patient monitoring is studied in [22], utilizing video game technology for practical purposes and adding a playful dimension to the learning process.

Considering the aforementioned, in the medical and rehabilitation domain, fostering collaboration among various experts, such as researchers, clinical professionals, and technological developers, would be highly beneficial. This collaboration would enable the standardization of virtual reality and serious game technologies, thereby facilitating therapists in selecting the most suitable tools for their patients. This approach leads to improved rehabilitation outcomes and more efficient resource utilization [23].

In [24], the introduction of SGs into the educational system is examined, driven by the impact of technology on children’s lives and learning. The work of [25] proposes the design of an SG to teach and assess generic competencies, such as problem-solving and entrepreneurship, using an evaluation model. However, the lack of performance metrics highlights the evaluation challenges.

On the other hand, virtual reality (VR) plays a significant role in enhancing problem-solving skills in various fields. In [26], it is demonstrated that VR effectively improves problem-solving skills by providing immersive environments to understand and solve real-world problems. The integration of VR with eye-tracking technology to model and quantify engineering problem-solving skills in manufacturing systems is discussed in [27].

In the context of leadership training, VR provides a heightened presence, allowing individuals to experience virtual situations similar to real-world scenarios, thereby enhancing learning effects. Moreover, VR enables the development of crucial communication skills for effective leadership, as individuals can practice public speaking in a realistic virtual environment, improving soft skills and receiving real-time feedback [28,29]. These findings underscore the valuable contribution of VR to skill enhancement through immersive and interactive learning experiences. The use of VR in serious games, as discussed in [30], provides immersive experiences that enhance the transfer of knowledge and complex skills. This immersive aspect is critical as it allows practical experience in scenarios where real-world training could be impractical or limited. Furthermore, if gamification is added to the tasks performed in the simulator, it leads to improved learning outcomes, especially for activities requiring greater precision outside the simulated environment [31]. Despite these mentioned benefits, ref. [21] argues that these games still require thorough validation before they can be fully integrated into the educational sector, as it is necessary to ensure that they effectively meet learning objectives.

The study of spectral coherence and spectral entropy in neuroscience provides validated metrics on brain function and cognitive processes. Spectral coherence has been studied in the field of neuroscience to understand the functional organization of the brain and interactions between different brain regions during the performance of various cognitive and perceptual tasks [32,33,34,35]. Spectral coherence provides information about the degree of synchronization between brain signals at different frequencies, indicating the strength and direction of the functional relationship between specific brain areas. This analysis allows for the identification of patterns of neuronal connectivity and understanding how different brain regions integrate to process information and perform complex cognitive functions.

Similarly, spectral entropy has been studied in neuroscience to assess the complexity and variability of brain activity during cognitive tasks [36,37,38,39,40,41,42]. It quantifies the uncertainty of brain signals by analyzing the distribution of spectral power across frequency bands. Calculating spectral entropy helps uncover how the brain responds to stimuli and cognitive demands, revealing the underlying mechanisms of information processing and cognitive function.

1.2. Motivation

The development of video games has evolved significantly in recent decades, becoming a popular form of digital entertainment. However, while many video games are primarily designed for entertainment, there is a growing interest in exploring how video games can be used as tools for cognitive development and improvement of specific skills, such as problem-solving. This research aims to fill a gap in the current understanding of how video games can be designed to promote cognitive development and enhance problem-solving skills in players.

This study examines how three virtual reality puzzle games can activate and stimulate the cognitive problem-solving process in players. To address this issue, we propose using the metrics of magnitude-square coherence (MSC) and spectral entropy (SpEn) to quantify the level of stimulation experienced by players when engaging in these three virtual reality puzzle games. By analyzing these aspects, we aim to identify key features that developers of serious virtual reality games should consider to optimize the development of cognitive processes such as problem-solving.

1.3. Contribution and Article Structure

The results and experiments conducted mainly demonstrate that the described methodology is suitable for EEG data analysis. The contributions of this work can be summarized as follows:

• (i). An appropriate methodology is described for recording EEG data in VR video game players.

• (ii). Algorithms are proposed to compute MSC and SpEn through digital processing of EEG signals in the frequency domain for the 30 video game players, who participated in three virtual reality games.

The remaining sections of the article are structured as follows. Section 2 addresses the materials and methods employed in the study, detailing the metrics of MSC and SpEn, as well as the algorithms proposed for their calculation. Section 3 presents the results of the proposed algorithms and the corresponding statistical outcomes for each evaluated experiment. Subsequently, in Section 4, the implications of the findings are discussed. Finally, Section 5 summarizes the key conclusions derived from this research.

2. Materials and Methods

The research question aims to analyze the influence of video games on human attention and how video games can positively affect human mood conditions, focusing on cognitive processing.

Video games have their roots in solving puzzles and challenges, and their application was originally focused on research and programming to play with machines. Based on the aforementioned, we are looking for this type of video games for our research. Video games focus on problem-solving, creativity, and cognitive skills.

In this study, our main objective was to describe the advantages of a particular video game genre in the classification of challenging puzzlers. This classification of video games is receiving particular attention for its ability to influence mental and emotional regulation. The main aim of the investigation is to understand how these interactive digital experiences can act as powerful amplifiers of cognitive processing, providing valuable insights and providing potential therapeutic or educational applications.

Our research sees a great opportunity to focus on improving problem-solving. This is because users need to think creatively and analytically to find solutions. By providing examples of puzzles, users can be encouraged to foster their creativity and ingenuity to solve them. Additionally, concentration plays a very important role in this type of task. Puzzles also have other advantages. They can also be a great way to relax and reduce stress as they focus on specific tasks. And the feeling of solving puzzles also has a positive perception. Overall, all of these things can improve the mood of players.

2.1. Participants

The study involved 30 cases of young people between 18 and 27 (17 females and 13 males, with an overall average age of 22.07 years) who played three different video games of the type challenging puzzlers. Participants were recruited for the tests via an email invitation, whereby individuals enrolled by accessing a link to designate their preferred time slot for test participation. The participant selection criteria specifically targeted individuals with minimal exposure to virtual reality, stipulating a cap of three prior uses of virtual reality headsets. The research aims to generalize the findings from these 30 cases to demonstrate the broader impact of video games on problem-solving tasks.

2.2. Experimental Procedure

The methodology explained three different video games and provided a video tutorial. Brain brainwave data were recorded using electroencephalography while participants played the three video games during this phase.

This phase is illustrated in Figure 1, where three different video games are explained. The video tutorial covers the gameplay, objectives, mechanics, and progression through the levels of each video game. Once the tutorial is completed, participants put on the virtual reality headset and make the necessary adjustments to ensure a proper fit. After these adjustments, the participants start playing the video games while their brainwave data are recorded using an EEG (MUSE 2). The brainwave data are transmitted to and received by a tablet. It is crucial to emphasize that all examinations were carried out with the subjects positioned in a seated posture.

2.3. Experimental Setup

Participants put the EEG device on their heads, and once the EEG signal is confirmed to be stable and transmitting to the tablet, they proceed to put on the virtual reality headset, which in this case was the Meta Quest 2. Once the player is ready with all the setup, the recording of brainwaves and gameplay time begins; all these steps are shown in Figure 2. In Figure 3, a user is shown playing a VR video game with the Meta Quest 2 and wearing the MUSE 2 EEG.

This experiment investigates the impact of playing three VR games on people aged 18 to 27, regardless of whether they have ever used a VR headset. The games are Cubism, Puzzling Places, and Tetris, all from one specific genre: challenging puzzlers. Challenging puzzlers belong to a category of video games that are purposely crafted to evaluate and improve the sophisticated problem-solving abilities of players. As shown in Table 1, these games frequently present intricate situations and complex tasks that necessitate critical thinking, strategic planning, and a high level of cognitive engagement. These games can be a fun and challenging way to improve problem-solving skills. They can also teach players about logic, spatial reasoning, and creativity.

Cubism is a puzzle game that challenges players to create 3D sculptures. Puzzling Places is a puzzle game where you assemble detailed miniatures of real-world locations. Tetris is like a classic puzzle game but in an immersive world with new visual and audio effects. Cubism is a virtual reality game that a single person developed, Thomas Van Bouwel, and it was released on 17 September 2020 [43]. The main objective is to fit different geometric pieces into a larger shape. Puzzling Places is a game developed by realities.io Inc. (Berlin, Germany), and the release date was 2 September 2021 [44]. In this video game, the user assembles 3D pieces of places worldwide. The third video game, Tetris, is a famous game known by almost everyone worldwide. This game joined as a virtual reality game. Tetris was developed by Monstars Inc. (Southlake, TX, USA), Resonair, and Stage Games and released on 14 May 2020 [45]. Pieces fall randomly from the top of the screen, and the player must move and rotate them to fit them into the game grid. The goal is to form a horizontal line of blocks to score points.

Each game has specific properties, as shown in Table 2. Cubism is characterized by its calm and soothing music and pastel-colored blocks, and the gameplay mechanic of grabbing these blocks can be achieved either with any of the two controllers or through hand tracking. The video game Puzzling Places has ambient sounds and pastel colors; the player has to assemble the pieces to construct the place. Tetris has electronic music, neon, and brilliant colors, and the video gamer’s goal is to form a horizontal row of blocks, moving and rotating the figures that appear in the game.

2.4. Methods

During the problem-solving process, various brain waves and neuroscientific metrics play a crucial role in brain activity and cognitive function. Table 3 provides a summary of the key brain waves for studying this process.

The EEG data were processed to analyze the brain’s electrical activity across different bandwidths, as mentioned in Table 3. The calculation of power spectral density (PSD) was performed using the Welch method [3,46,47]:

(1)$P_{xx}\left(f\right)=\frac{1}{N_{FFT}·\Delta }·\sum _{i=0}^{M-1}\frac{|X_i{\left(f\right)|}^2}{N_{avg}},$

where $P_{xx}\left(f\right)$ is defined as the power spectral density at frequency f. $N_{FFT}$ represents the number of points used in the fast Fourier transform (FFT). $\Delta$ denotes the time interval between overlapping signal segments, while M indicates the total number of signal segments. $X_i\left(f\right)$ represents the Fourier transform of the i-th EEG signal segment, and $N_{avg}$ is the number of segments averaged in the Welch method.

2.4.1. EEG Magnitude-Squared Coherence Analysis

The complex coherence function is the normalized cross-spectral density,

(2)$C_{xy}\left(f\right)=\frac{P_{xy}\left(f\right)}{\sqrt{P_{xx}\left(f\right)P_{yy}\left(f\right)}},$

where $P_{xy}\left(f\right)$ is the cross-spectral density at frequency between $x\left(t\right)$ and $y\left(t\right)$ with auto spectra $P_{xx}\left(f\right)$ and $P_{yy}\left(f\right)$. In particular, the magnitude-squared coherence (MSC):

(3)$|C_{xy}{\left(f\right)|}^2=\frac{|P_{xy}{\left(f\right)|}^2}{P_{xx}\left(f\right)P_{yy}\left(f\right)}.$

In the context of the cognitive process of problem-solving, the values obtained from EEG MSC can offer insights into how different brain regions are synchronized during the execution of specific tasks. For instance, stronger synchronization patterns between certain brain regions may indicate higher efficiency in problem-solving, whereas lower synchronization could suggest difficulties in integrating the necessary information to solve the problem. These findings can aid researchers in gaining a deeper understanding of the underlying mechanisms of the problem-solving process. They may hold significant implications for developing intervention strategies or cognitive training approaches.

In this study, coherence is calculated for all frequency bands described in Table 3, which are associated with different mental states corresponding to brain waves. The inter- and intra-hemispheric electrode combinations, respectively, are shown in Figure 4. For each pair, coherence was computed using the proposed Algorithm 1 across all EEG frequency bands mentioned in Table 3.

Algorithm 1: EEG signal coherence analysis.

2.4.2. EEG Espectral Entropy Analysis

Spectral entropy is defined as the Shannon entropy of the power spectral density (PSD) function:

(4)$SpEn=-\sum _{f}P\left(f\right){log}_{2}P\left(f\right),$

where $P\left(f\right)$ is the normalized power spectral density. To obtain $P\left(f\right)$, the spectrum of the fast Fourier transform (FFT) of the signal is computed and normalized between 0 and 1 by dividing by the maximum power. The proposed Algorithm 2 outlines the EEG processing steps for calculating SpEn.

Algorithm 2: Spectral entropy analysis.

3. Results

For EEG data acquisition, a Muse 2 headband was utilized. The Muse 2 features four channels with electrodes at AF7, AF8, TP9, and TP10. Raw EEG values were processed using Python 3.11 libraries scipy and numpy. Specifically, the power spectral density (PSD) was computed using the pwelch function with a sampling frequency $f_s=500$ Hz, FFT size of 512, and Hamming windows of 4 s duration with a 50% overlap.

3.1. Experiment One

Figure 5 illustrates the MSC values calculated in the Beta band using EEG data recorded from the AF7–AF8 electrode pair. Therefore, these values correspond to MSC from the frontal area of the left (AF7) and right (AF8) hemispheres of the brain. The red signal corresponds to the Tetris video game, exhibiting higher MSC values across all frequencies compared to the signals from the Cubism and Puzzling video games. Above 100 Hz, the red signal from the Tetris video game shows MSC values above 0.9. This suggests a high level of temporal synchronization and coherence in brain activity between electrodes AF7 and AF8. Interpretatively, these results indicate that the signal from the Tetris video game reflects a heightened level of cognitive engagement and concentration compared to the other two video games.

Figure 6 displays the MSC values calculated in the Beta band using EEG data recorded from the TP9–TP10 electrode pair. These values correspond to MSC from the left temporal lobe (TP9) and right temporal lobe (TP10) of the brain, which are associated with functions such as hearing, language processing, and memory. In contrast with Figure 5, the MSC values for the three video games are very close and exhibit high coherence above 0.8 across frequencies ranging from 50 to 220 Hz. This similar behavior in the signals indicates uniform synchronization, likely due to the specific task of fitting pieces present in all three video games.

3.2. Experiment Two

In the second experiment, we computed the MSC within the Gamma band (30–40 Hz). Figure 7 displays the MSC values for the AF7–AF8 electrode pair. The red signal corresponding to the Tetris video game exhibits MSC values exceeding 0.8 in the 120–220 Hz range. In this frequency range, the Tetris video game signal shows significantly higher MSC values compared to the Cubism and Puzzling video game signals, which have average MSC values around 0.65. These findings suggest enhanced temporal synchronization and coherence in brain activity between electrodes AF7 and AF8 during the task of playing Tetris.

The Gamma band is associated with higher cognitive functions such as selective attention, refined sensory perception, and advanced cortical integration. Therefore, these results imply that participants engage in more intensive cognitive processing while tackling Tetris game challenges.

Furthermore, Figure 8 illustrates the MSC values for the TP9–TP10 electrode pair within the Gamma band. Similar to the results observed in Figure 6, the MSC values for Tetris and Puzzling video games are comparable below 220 Hz frequencies; however, above this frequency range, Tetris exhibits a trend of superior MSC values compared to Cubism and Puzzling.

3.3. Experiment Three

In the third analysis, MSC values were calculated for the two signals from the AF7–AF8 electrode pair in the Alpha band. Figure 9 clearly shows that above 150 Hz, the black signal from the Puzzling video game exhibits MSC values averaging around 0.55, which are higher compared to Tetris and Cubism. It is important to highlight that Cubism yielded coherence values below 0.3, indicating lower cognitive activity among players.

Figure 10 illustrates the MSC values obtained from the TP9–TP10 electrode pair in the Alpha band. It is evident that above 150 Hz, the red signal from Tetris demonstrates MSC values close to 0.8. This indicates that Tetris exhibits greater coherence between the TP9–TP10 signals compared to Cubism and Puzzling, which achieved lower MSC values of approximately 0.65 and 0.55, respectively.

3.4. Experiment Four

In the final analysis of channels AF7, AF8, TP9, and TP10 within the Gamma band (30–100 Hz), spectral entropy (SpEn) values were examined for the Cubism, Puzzling, and Tetris video games. Particularly, in channel AF7 (Figure 11a), a mean SpEn of 6.859 was observed for Tetris, which was higher compared to the values obtained for Cubism and Puzzling. These results suggest greater complexity and diversity in brain activity during Tetris gameplay, highlighting the differential influence of this game on neuronal activity in the Gamma band among all analyzed participants.

In channel AF8 (Figure 11b), Tetris exhibited a mean SpEn of 6.856, which was higher compared to the mean SpEn of Cubism (6.845) and Puzzling (6.817) within the same frequency range of the Gamma band. This difference suggests a higher level of variability and neuronal processing associated with Tetris gameplay in channel AF8.

For channel TP9 (Figure 11c), spectral entropy values were comparable among the three video games in the Gamma band, although Tetris showed a slight advantage in terms of mean entropy. This suggests similar but potentially more complex brain activity during Tetris gameplay in TP9 within the Gamma band.

Finally, in channel TP10 (Figure 11d), Tetris exhibited a mean SpEn of 6.861, which was higher compared to Cubism (6.848) and Puzzling (6.852) within the Gamma band. These results indicate greater neuronal activity and cortical variability associated with Tetris gameplay in channel TP10.

In summary, spectral entropy results in the Gamma band suggest that playing Tetris is associated with increased complexity and diversity in brain activity, especially in the analyzed cortical regions (AF7, AF8, and TP10), compared to other evaluated video games (Cubism and Puzzling). These findings support the notion that different gaming tasks can uniquely influence neuronal activity and cortical complexity as measured by spectral entropy in EEG, particularly in the Gamma band.

4. Discussion

The findings of this study offer a comprehensive insight into the neural activity patterns associated with coherence and spectral entropy across various virtual reality (VR) video game tasks. Analyzed across multiple EEG channels (AF7, AF8, TP9, and TP10, depicted in Figure 4) and frequency bands (as outlined in Table 3), interpreting these outcomes alongside prior research and our initial hypotheses allows for a nuanced understanding of the cognitive and neurophysiological ramifications of engaging with distinct VR gaming experiences.

Initially, spectral coherence analyses across channels AF7, AF8, TP9, and TP10 unveiled unique neural synchronization patterns during the execution of Cubism, Puzzling, and Tetris VR games. Particularly in the Gamma band, heightened coherence between AF7 and AF8 electrodes was observed during Tetris gameplay compared to Cubism and Puzzling. This increase in spectral coherence likely signifies enhanced cortical integration and neuronal synchronization, attributes pertinent to the spatial challenges and rapid decision making inherent in Tetris. These findings underscore the differential impact of VR gaming tasks on coherence and synchronization among specific brain regions, potentially pivotal in elucidating the effects of interactive experiences on brain function and neuronal adaptability.

Moreover, Tetris gameplay elicited higher spectral entropy and coherence values in channels AF7, AF8, and TP10 compared to other VR games, indicative of more intricate neural processing and heightened cortical activity during gameplay. These results corroborate prior studies linking Gamma band activity with advanced cognitive processes like selective attention and sensory integration.

Looking ahead, further exploration of the neural mechanisms underlying these disparities in spectral coherence during VR gameplay is imperative for future investigations. Additionally, longitudinal studies hold promise in unraveling the impact of sustained exposure to VR gaming tasks on the brain’s functional organization and subsequent cognitive performance.

5. Conclusions

Based on the conducted tests, it is noteworthy that the distribution of MSC among the analyzed channels may reflect cognitive demands and functional distribution in different brain regions during video game task execution. For example, the higher coherence values in the AF7–AF8 pair recorded during Tetris gameplay indicate increased interaction between the frontal and temporal regions of the brain, implicated in visuospatial processing and decision making in problem-solving tasks. High values were recorded in experiments one, two, and three, as observed in the results of the experiments.

In the analysis of SpEn in channels AF7, AF8, TP9, and TP10 within the Gamma band (30–100 Hz), spectral entropy (SpEn) values were examined for the video games Cubism, Puzzling, and Tetris. Specifically, in channel AF7 (Figure 11a), Tetris exhibited a mean SpEn of 6.859, higher compared to the values obtained for Cubism and Puzzling. Similarly, in channel AF8 (Figure 11b), Tetris displayed a mean SpEn of 6.856, which was higher compared to the mean SpEn of Cubism (6.845) and Puzzling (6.817). This difference suggests a higher level of variability and neuronal processing associated with Tetris gameplay in channel AF8. For channel TP9 (Figure 11c), the SpEn values were comparable among the three video games, although Tetris showed a slight advantage in terms of mean entropy. This suggests similar but potentially more complex brain activity during Tetris gameplay in channel TP9. Finally, in channel TP10 (Figure 11d), Tetris exhibited a mean SpEn of 6.861, which was higher compared to Cubism (6.848) and Puzzling (6.852) within the Gamma band. These findings underscore the importance of considering spectral coherence alongside spectral entropy when assessing the effects of video game tasks on brain activity. Such insights may hold significant implications for designing video-game-based interventions aimed at enhancing cognitive function and promoting brain health.

Additionally, it is worth noting that virtual reality games possessing the characteristics described in Tetris (Table 1) stimulate the cognitive problem-solving process more effectively. These features should be taken into account in the design of serious video games aimed at developing this cognitive process in players.

6. Ethics Approval

Integrity Code of the Universidad Panamericana, validated by the Social Affairs Committee and approved by the Governing Council through resolution CR 98-22, on 15 November 2022.

Author Contributions

Conceptualization, J.G.-B., J.A.D.-P.-F., F.R.C.-S., F.M.M.-B. and C.D.-V.-S.; methodology, J.G.-B., J.A.D.-P.-F. and C.D.-V.-S.; software, J.G.-B., J.A.D.-P.-F. and C.D.-V.-S.; validation, F.R.C.-S., F.M.M.-B. and C.D.-V.-S.; formal analysis, J.G.-B., J.A.D.-P.-F., F.R.C.-S., F.M.M.-B. and C.D.-V.-S.; investigation, J.G.-B., J.A.D.-P.-F., F.R.C.-S., F.M.M.-B. and C.D.-V.-S.; resources, J.G.-B., J.A.D.-P.-F., F.R.C.-S., F.M.M.-B. and C.D.-V.-S.; writing—original draft preparation, J.G.-B., J.A.D.-P.-F., F.R.C.-S., F.M.M.-B. and C.D.-V.-S.; writing—review and editing, J.G.-B., J.A.D.-P.-F. and C.D.-V.-S.; supervision, J.G.-B., J.A.D.-P.-F., F.R.C.-S., F.M.M.-B. and C.D.-V.-S.; project administration, J.G.-B., J.A.D.-P.-F., F.R.C.-S., F.M.M.-B. and C.D.-V.-S.; funding acquisition, J.G.-B. All authors read and agreed to the published version of the manuscript.

Data Availability Statement

The data presented in this study are openly available through the following GitHub repository: https://github.com/jesusgrb/PaperElectronics.git (accessed on 17 May 2024).

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1. Explanation of the video games with a video tutorial.

Figure 2. Preparation and adjustments to play video games in virtual reality.

Figure 3. A user with the Meta Quest 2 and the MUSE 2 during a session of play.

Figure 4. Electrode pair configuration used in data analysis.

Figure 5. Analysis of EEG coherence pair AF7–AF8 in the Beta band from 13 to 30 Hz.

Figure 6. Analysis of EEG coherence pair TP9–TP10 in the Beta band from 13 to 30 Hz.

Figure 7. Analysis of EEG coherence pair AF7–AF8 in the Gamma band from 30–40 Hz.

Figure 8. Analysis of EEG coherence pair TP9–TP10 in the Gamma band from 30–40 Hz.

Figure 9. Analysis of EEG coherence pair AF7–AF8 in the Alpha band 8–12 Hz.

Figure 10. Analysis of EEG coherence pair TP9–TP10 in the Alpha band 8–12 Hz.

Figure 11. SpEn extracted from EEG data across all participants in the Gamma band of 30–100 Hz.

Table 1

Features of VR video games.

Cubism	Puzzling Places	Tetris
Calm music	Sounds of nature	Electronic music
Pastel colors	Pastel colors	Neon colors
Use of controls	Use of controls	Use of controls
and hands	and hands
Interaction with	Interaction with	Rotation of figures
objects	hyperrealistic objects

Table 2

Characteristics and objectives of challenging puzzlers games.

	Cubism	Puzzling Places	Tetris
Characteristics	Challenging task	Challenging task	Simple task
	Enjoyable	Immersive experience	Enjoyable
	Block assembly	3D Puzzle assembly	Limited play area
	Relaxed environment	Hyperrealistic models	Visual effects and sounds
Objective	Education	Improve skills	Game skill improvement
	Concentration	Concentration	Concentration
	Puzzle-solving ability	Puzzle-solving ability	Gaming enjoyment
	Training	Relaxation	Relaxation

Table 3

Brain wave bandwidths.

Wave	Bandwidth	Description
Beta	12–30 Hz	Associated with concentration, focus, and higher cognitive processes during problem-solving. Indicates increased cortical activity related to information processing and task focus.
Theta	4–8 Hz	Related to working memory, attention, and strategy planning during problem-solving. Fluctuations in these waves may be linked to information retrieval and solution strategies.
Alpha	8–12 Hz	Indicates relaxation but may decrease in brain areas during concentration on problem-solving, reflecting sustained attention and focus.
Gamma	30–40 Hz	Related to complex cognitive processes, sensory integration, and decision making during problem-solving. Increased observed in brain regions involved in information integration.

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