EEG based stress analysis using rhythm specific spectral feature for video game play

• Published in: Computers in biology and medicine Vol. 148; p. 105849
• Main Authors: Roy, Shidhartho, Islam, Monira, Yusuf, Md. Salah Uddin, Jahan, Nushrat
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.09.2022; Elsevier Limited
• Subjects: Beta–Alpha ratio; Body mass index; Body size; Brain; Brain architecture; Computation; Computational neuroscience; Computer & video games; COVID-19; EEG; Electroencephalography; Frequency; Frontal lobe; Internal Medicine; Magnetic resonance imaging; Mathematical models; Music; Neuroimaging; Other; Parameters; Power spectral density; Psychological stress; Regression analysis; Relaxation therapy; Residual stress; Stress analysis; Stress relaxation; Stress-relaxation modeling; Topography; Video gameplay; Stress-relaxation modeling; Beta–Alpha ratio; Video gameplay; EEG; Topography; Beta-Alpha ratio; Stress - relaxation modeling
• ISSN: 0010-4825; 1879-0534; 1879-0534
• DOI: 10.1016/j.compbiomed.2022.105849

For the emerging significance of mental stress, various research directives have been established over time to understand better the causes of stress and how to deal with it. In recent years, the rise of video gameplay has been 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 mainly focused on the “gameplay stress” based on physical syndromes. Some studies have analyzed the effects of video gameplay with Electroencephalogram (EEG), Magnetic resonance imaging (MRI), etc., without concentrating on the relaxation procedure after video gameplay. This paper presents an end-to-end stress analysis for video gaming stimuli using EEG. The power spectral density (PSD) of the Alpha and Beta bands is computed to calculate the Beta-to-Alpha ratio (BAR). The Alpha and Beta band power is computed, and the Beta-to-Alpha band power ratio (BAR) has been determined. In this article, BAR is used to denote mental stress. Subjects are chosen based on various factors such as gender, gameplay experience, age, and Body mass index (BMI). EEG is recorded using Scan SynAmps2 Express equipment. There are three types of video gameplay: strategic, puzzle, and combinational. Relaxation is accomplished in this study by using music of various pitches. Two types of regression analysis are done to mathematically model stress and relaxation curve. Brain topography is rendered to indicate the stressed and relaxed region of the brain. In the relaxed state, the subjects have BAR 0.701, which is considered the baseline value. Non-gamer subjects have an average BAR of 2.403 for 1 h of strategic video gameplay, whereas gamers have 2.218 BAR concurrently. After 12 minutes of listening to low-pitch music, gamers achieved 0.709 BAR, which is nearly the baseline value. In comparison to Quartic regression, the 4PL symmetrical sigmoid function performs regression analysis with fewer parameters and computational power. Non-gamers experience more stress than gamers, whereas strategic games stress the human brain more. During gameplay, the beta band in the frontal region is mostly activated. For relaxation, low pitch music is the most useful medium. Residual stress is evident in the frontal lobe when the subjects have listened to high pitch music. Quartic regression and 4PL symmetrical sigmoid function have been employed to find the model parameters of the relaxation curve. Among them, quartic regression performs better in terms of Akaike information criterion (AIC) and R2 measure. [Display omitted] •Stress is identified for different types of video game play for expert or non-expert players.•The activated brain region is identified due to high level of stress.•Music therapy is adopted to mitigate stress and enhance relaxation.•Frequency domain EEG features are the parameters of detecting stress and relax state of brain.•Stress-relaxation modeling is performed with regression analysis and adjusted R2 validate the performance of the model.