MEASUREMENT OF STRESS INTENSITY USING EEG (original) (raw)
Related papers
2013
A better understanding of observable and quantifiable psychophysiological outputs such as electroencephalography (EEG) during computer video gameplay has significant potential to support the development of an automated, emotionally intelligent system. Integrated into a game engine, such a system could facilitate an effective biofeedback loop, accurately interpreting player emotions and adjusting gameplay parameters to respond to players’ emotional states in a way that moves towards exciting ventures in affective interactivity. This paper presents a crucial step to reaching this objective by way of examining the statistical features of EEG that may relate to user experience during audio-centric gameplay. An audio-only test game ensures that game sound is the exclusive stimulus modality with gameplay contextualisation and qualitative data collection enabling the study to focus specifically upon fear. Though requiring of an unambiguous horror-game context, the results documented within this paper identify several statistical features of EEG data that could differentiate fear from calm.
Basic and Clinical Neuroscience Journal, 2022
Introduction: Video games affect the stress system and cognitive abilities in different ways. Here, we evaluated electrophysiological and biochemical indicators of stress and assessed their effects on cognition and behavioral indexes after playing a scary video game. Methods: Thirty volunteers were recruited into two groups as control and experimental. The saliva and blood samples were collected before and after intervention (watching/playing the scary game for control and experimental groups respectively). To measure cortisol and salivary alpha-amylase (sAA) levels, oxytocin (OT), and brain-derived neurotrophic factor (BDNF) plasma levels, dedicated ELISA kits were used. EEG recording was done before and after interventions for electroencephalogram (EEG)-based emotion and stress recognition. Then, the feature extraction (for mental stress, arousal, and valence) was done. Matrix laboratory (MATLAB) software used for processing EEG acquired data. The repeated measures were applied to...
Basic and Clinical Neuroscience, 2023
Introduction: Video games affect the stress system and cognitive abilities in different ways. Here, we evaluated electrophysiological and biochemical indicators of stress and assessed their effects on cognition and behavioral indexes after playing a scary video game. Methods: Thirty volunteers were recruited into two groups as control and experimental. The saliva and blood samples were collected before and after intervention (watching/playing the scary game for control and experimental groups respectively). To measure cortisol and salivary alpha-amylase (sAA) levels, oxytocin (OT), and brain-derived neurotrophic factor (BDNF) plasma levels, dedicated ELISA kits were used. Electroencephalography recording was done before and after interventions for electroencephalogram (EEG)-based emotion and stress recognition. Then, the feature extraction (for mental stress, arousal, and valence) was done. Matrix laboratory (MATLAB) software, version 7.0.1 was used for processing EEG-acquired data. The repeated measures were applied to determine the intragroup significance level of difference. Results: Scary gameplay increases mental stress (P<0.001) and arousal (P<0.001) features and decreases the valence (P<0.001) one. The salivary cortisol and alpha-amylase levels were significantly higher after the gameplay (P<0.001 for both). OT and BDNF plasma levels decreased after playing the scary game (P<0.05 for both). Conclusion: We conclude that perceived stress considerably elevates among players of scary video games, which adversely affects the emotional and cognitive capabilities, possibly via the strength of synaptic connections, and dendritic thorn construction of the brain neurons among players.
EEG based stress analysis using rhythm specific spectral feature for video gameplay
ArXiv, 2021
Background and Objective For the emerging significance of mental stress, various research directives have been established over time to better understand the causes of stress and how to deal with it. In recent years, the rise of video gameplay is unprecedented, further triggered by the lockdown imposed due to the COVID-19 pandemic. Several researchers and organizations have contributed to the practical analysis of the impacts of such extended periods of gameplay, which lacks coordinated studies to underline the outcomes and reflect those in future game designing and public awareness about video gameplay. Investigations have mostly focused on the “gameplay stress” based on physical syndromes only. Some studies have analyzed the effects of video gameplay with EEG, MRI, etc., without concentrating on the relaxation procedure after video gameplay. Methods This paper presents an end-to-end stress analysis for video gaming stimuli using EEG. The PSD value of the Alpha and Beta bands is co...
Signal to Emotion - An Experiment on Player Experience Evaluation with a Consumer-grade EEG Device
2018
While game experience research is gaining more interest, understanding player experience and emotions that are invoked during a play session is not a completely resolved topic. There has been some research into using electroencephalogram (EEG) for player experience evaluation since questionnaires can only provide limited information. However, the complexity of using EEG as an evaluation tool has been an issue. In this study, we explored the potential of a consumer-grade EEG device in player experience evaluation compared to the questionnaire approach. Results show that the device provides somewhat matching data with the questionnaire and potentially further information about the momentary player experience.<br>Signal to Emotion - An Experiment on Player Experience Evaluation with a Consumer-grade EEG Device. In Proceedings of the 29th Australian Conference on Human-Computer Interaction, Brisbane, QLD, Australia, November 2017 (OzCHI 2017)<br><br>
Valence, arousal and dominance in the EEG during game play
International Journal of Autonomous and Adaptive Communications Systems, 2013
In this paper, we describe our investigation of traces of naturally occurring emotions in electrical brain signals, that can be used to build interfaces that respond to our emotional state. This study confirms a number of known affective correlates in a realistic, uncontrolled environment for the emotions of valence (or pleasure), arousal and dominance: (1) a significant decrease in frontal power in the theta range is found for increasingly positive valence, (2) a significant frontal increase in power in the alpha range is associated with increasing emotional arousal, (3) a significant right posterior power increase in the delta range correlates with increasing arousal and (4) asymmetry in power in the lower alpha bands correlates with self-reported valence. Furthermore, asymmetry in the higher alpha bands correlates with self-reported dominance. These last two effects provide a simple measure for subjective feelings of pleasure and feelings of control.
An Analysis of Game-Related Emotions Using EMOTIV EPOC
Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, 2018
Computer games represent a very popular form of entertainment. Therefore, playing games became an object of interest for researchers. The research on the brain activity of players when playing a game is an experimental contribution to the neurophysiology of the central nervous system, and it also supports marketing research. Devices that register electromagnetic waves generated by the brain, e.g. EEG (Electroencephalography) can be used by psychologists studying the impact of games on users when the game. Our goal was to analyze emotion changes while playing video games, based on EEG signal registered with EMOTIV EPOC headset, and identify the strongest emotions accompanying the game. We also wanted to link emotions to particular elements of the game. Game developers, especially educational and therapeutic, can use the outcomes of this work in the practical implementation of the brain-computer interfaces in their products, in order to create better and more engaging games.
Biofeedback Sensors in Electronic Games: A Practical Evaluation
2017
In the electronic games industry, many ways of testing a new game are used in order to determine some aspects of the game, such as fun, replay value and immersion. One way to evaluate these characteristics is through the use of sensors, more specifically the ones that measure player's biophysiological variables, called biofeed-back sensors. The purpose of this study is to perform a practical evaluation of the use of biofeedback sensors, when employed to know the behavior of the player in different genres of games. More precisely, an experiment with three biofeedback sensors (Electro-cardiography, Electrodermal Activity Sensor, and Electromyogra-phy) was conducted to verify the suitability of these sensors in identifying the player's emotions according to the genre of the game. The results showed that intense emotions, like the ones felt in horror or action games, are more detectable in general, but they are more notable when using the Electrocardiography sensor.
Database for an emotion recognition system based on EEG signals and various computer games – GAMEEMO
Biomedical Signal Processing and Control, 2020
In this study, electroencephalography-based data for emotion recognition analysis are introduced. EEG signals were collected from 28 different subjects with a wearable and portable EEG device called the 14-channel EMOTIV EPOC+. Subjects played 4 different computer games that captured emotions (boring, calm, horror and funny) for 5 min, and the EEG data available for each subject consisted of 20 min in total. The subjects rated each computer game based on the scale of arousal and valence by applying the SAM form. We provide both raw and preprocessed EEG data with.csv and. mat format in our data repository. Each subject's rating score and SAM form are also available. With this work, we aim to provide an emotion dataset based on computer games, which is a new method in terms of collecting brain signals. Additionally, we want to determine the success of the portable EEG device and compare the success of this device with classical EEG devices. Finally, we perform pattern recognition and signal-processing methods to observe the performance of our dataset and to classify EEG signals based on the arousalvalence emotion dimension and positive/negative emotions. The database will be publicly available, and researchers can use the dataset for analyzing signals for their own proposed method in the literature.
2021 IEEE Conference on Games (CoG), 2021
The low-cost electroencephalogram (EEG) devices are widely used by researchers in human-computer interaction, video games, and software systems to evaluate the impact of interaction design on user emotions. However, the performance metrics of emotion states provided by a low-cost EEG device suffer several reliability and accuracy issues, which can mislead the design decisions of the developers. In this research, we combined the EEG device with three virtual reality games to investigate the reliability of performance metrics extracted from the EEG data. We conducted the experiment with 14 players using virtual reality games with ranging levels of in-game actions. Our analysis shows that there is a significant difference between performance metrics provided by the EEG device and the actual players' experience. Finally, we used ad-hoc linear models to estimate the level of players' emotion states directly from the raw EEG. We also show the different brain activity maps for individual emotions, which reveal the commonly known relation between brain activity and specific emotions.