Volume 9, Issue 3 (May & June 2018 2018)
BCN 2018, 9(3): 177-186 |
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Hamed Aliyari1 
, Hedayat Sahraei2 , Mohammad Reza Daliri3 , Behrouz Minaei-Bidgoli4 
, Masoomeh Kazemi * 2, Hassan Agaei2 , Mohammad Sahraei5 , Seyed Mohammad Ali Seyed Hosseini6 , Mohammad Mehdi Hadipour2 , Mohammad Mohammadi7 , Zahra Dehghanimohammadabadi8
, Hedayat Sahraei2 , Mohammad Reza Daliri3 , Behrouz Minaei-Bidgoli4 , Masoomeh Kazemi * 2, Hassan Agaei2 , Mohammad Sahraei5 , Seyed Mohammad Ali Seyed Hosseini6 , Mohammad Mehdi Hadipour2 , Mohammad Mohammadi7 , Zahra Dehghanimohammadabadi8
1- Department of Electrical Engineering, Faculty of Electrical, Biomedical and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2- Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran.
3- Department of Biomedical Engineering, Faculty of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran.
4- Department of Computer Engineering, School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran.
5- Department of Dentistry, Faculty of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
6- Department of Social Sciences, North Tehran Branch, Islamic Azad University, Tehran, Iran.
7- Human Motion Control and Computational Neuroscience Laboratory, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
8- Department of Statistics, Faculty of Mathematical Sciences, Alzahra University, Tehran, Iran.
2- Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran.
3- Department of Biomedical Engineering, Faculty of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran.
4- Department of Computer Engineering, School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran.
5- Department of Dentistry, Faculty of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
6- Department of Social Sciences, North Tehran Branch, Islamic Azad University, Tehran, Iran.
7- Human Motion Control and Computational Neuroscience Laboratory, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
8- Department of Statistics, Faculty of Mathematical Sciences, Alzahra University, Tehran, Iran.
Abstract:
Introduction: Video games are common cultural issues with great influence in all societies. One of the important cognitive effects of video games is on creating stress on video players. The present research objective was to study different types of stress in players based on video game styles.
Methods: A total of 80 players, aged 18 to 30 years, played four types of video games; Runner game, Excitement game, Fear game, and Puzzle game. In the beginning, the players filled in the form of personal information as well as some general and specialized information on the games. Before starting each game, the saliva samples of the players were collected to measure their level of cortisol and α-amylase. At the end of each game, the same samples were collected again. The concentrations of cortisol and α-amylase were measured using a specialized kit and an ELISA device. In addition, the variations of brain waves were recorded by an Emotiv system. Finally, the data were analyzed in SPSS and Matlab system (after and before playing video game).
Results: The research findings revealed that the salivary α-amylase concentration increased significantly after playing the Fear game, Runner game, and Excitement game and decreased significantly after playing the Puzzle game. Moreover, the concentration of salivary cortisol increased significantly after playing the Runner game, Excitement game, and Fear game and decreased significantly after playing the Puzzle game. The brain wave analysis also revealed that the level of stress experienced by playing Fear game was higher than the Excitement game.
Conclusion: According to the research findings, video games can affect the stress system as well as the cognitive system of humans depending on the game style. In addition, the type and level of stress triggered in the players depend on the game style.
Methods: A total of 80 players, aged 18 to 30 years, played four types of video games; Runner game, Excitement game, Fear game, and Puzzle game. In the beginning, the players filled in the form of personal information as well as some general and specialized information on the games. Before starting each game, the saliva samples of the players were collected to measure their level of cortisol and α-amylase. At the end of each game, the same samples were collected again. The concentrations of cortisol and α-amylase were measured using a specialized kit and an ELISA device. In addition, the variations of brain waves were recorded by an Emotiv system. Finally, the data were analyzed in SPSS and Matlab system (after and before playing video game).
Results: The research findings revealed that the salivary α-amylase concentration increased significantly after playing the Fear game, Runner game, and Excitement game and decreased significantly after playing the Puzzle game. Moreover, the concentration of salivary cortisol increased significantly after playing the Runner game, Excitement game, and Fear game and decreased significantly after playing the Puzzle game. The brain wave analysis also revealed that the level of stress experienced by playing Fear game was higher than the Excitement game.
Conclusion: According to the research findings, video games can affect the stress system as well as the cognitive system of humans depending on the game style. In addition, the type and level of stress triggered in the players depend on the game style.
Type of Study: Original |
Subject:
Computational Neuroscience
Received: 2017/11/30 | Accepted: 2018/03/26 | Published: 2018/05/1
Received: 2017/11/30 | Accepted: 2018/03/26 | Published: 2018/05/1
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