Modeling of Brain Cortical Activity during Relaxation and Mental Workload Tasks Based on EEG Signal Collection

Coronavirus disease 2019 (COVID-19) has caused everything from daily hassles, relationship issues, and work pressures to health concerns debilitating phobias. Relaxation techniques are one example of the many methods used address stress, they have been investigated for decades. In this study, we aimed check whether there differences in brain cortical activity participants during relaxation or mental workload tasks, as observed using dense array electroencephalography, these can be modeled then classified a machine learning classifier. guided imagery technique was randomized trial design. Two groups thirty randomly selected underwent session; other performed task. Participants were recruited among male computer science students. During session, electroencephalographic each student’s recorded amplifier. This compared with that group another 30 students who Power maps generated participant, examples presented discussed some extent. These types cannot easily interpreted by therapists due their complexity fact vary over time. However, signal general linear models. The classification results well discussion prospective applications presented.