Impact Study of Traditional Meditation Practices Using PSD Assessment of EEG Signals

Meditation is a practice that involves training the mind to achieve focused attention, tranquillity, and enhanced self-awareness. Different meditation techniques have distinct effects on the mind. Electroencephalogram (EEG) signals provide valuable insights into the brain's functioning during meditation. The purpose of this study is to examine the effects of three traditional meditation practices on EEG signals: Himalayan Yoga (HP), Isha Shoonya (SNY), and Vipassana (VIP). Fast Fourier transformations with a Hanning window of size 256 are used in this study to decompose the input EEG data into distinct frequency bands. The influence of meditation is then assessed using power spectral density (PSD) for each band. For each participant, four statistical parameters are computed: mean, median, variance, and standard deviation. The findings show that SNY and VIP practitioners have higher gamma amplitude (60–110 Hz) in the parieto-occipital area than the control group. Furthermore, VIP and SNY practitioners have a bigger variance in the mean value of gamma band activity, whereas HP practitioners have a lower variation. These findings show that attaining a state of calm can help people assess the effectiveness of their meditation practice. As a result, these findings are useful for increasing meditation practice and expanding our understanding of brain systems.