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For the emerging significance of mental stress, various research directiveshave been established over time to better understand the causes of stress andhow to deal with it. In recent years, the rise of video gameplay isunprecedented, further triggered by the lockdown imposed due to the COVID-19pandemic. This paper presents an end-to-end stress analysis for video gamingstimuli using EEG. The PSD value of the Alpha and Beta bands is computed tocalculate the Beta-to-Alpha ratio (BAR). In this article, BAR is used to denotemental stress. Subjects are chosen based on various factors such as gender,gameplay experience, age, and BMI. EEG is recorded using Scan SynAmps2 Expressequipment. There are three types of video gameplay: strategic, puzzle, andcombinational. Relaxation is accomplished in this study by the use of music ofvarious pitches. Two types of regression analysis are done to mathematicallymodel stress and relaxation curve. Brain topography is rendered to indicate thestressed and relaxed region of the brain. In the relaxed state, the subjectshave BAR 0.701, which is considered the baseline value. Non-gamer subjects havean average BAR of 2.403 for 1 hour of strategic video gameplay, whereas gamershave 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 toQuartic regression, the 4PL symmetrical sigmoid function performs regressionanalysis with fewer parameters and computational power.

EEG based stress analysis using rhythm specific spectral feature for video gameplay