  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. 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 computed to
calculate the Beta-to-Alpha ratio (BAR). In this article, BAR is used to denote
mental stress. Subjects are chosen based on various factors such as gender,
gameplay experience, age, and 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 the use of 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 hour 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.

Signal Processing;Human-Computer Interaction