Analysis of EEG Signal Components based on Meditation and Mind-Wandering Between Experienced Meditators and Non-Meditators
D Shreya Jingade, R Ashok Kumar, K. Vijayalakshmi, Sri Subhananda
Journal of Network Security Computer Networks November 21, 2022 DOI: 10.46610/jonscn.2022.v08i03.004 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational cohort Peer reviewed |
|---|---|
| Sample size | 10 |
| Population | Five experienced meditators and five meditation novices |
| Intervention | Meditation |
| Topics | Anxiety Meditation |
| Keywords | Electroencephalography Worry Mind-wandering Feeling Audiology Cognitive psychology Cognition |
| Key findings | Meditation experience alters EEG brainwave patterns, with statistically significant differences between meditators and novices. |
Abstract
Through meditation, one can acquire a calm, awake state of mind. It can assist people in becoming more conscious of themselves and their surroundings. Pain, worry, and other undesirable feelings may be significantly reduced with meditation. EEG is now one of the methods widely employed in the field of neuroscience to study how the brain works. Different capabilities of the brain are identified via electroencephalography (EEG), which uses brain data collected through electrodes. In this paper, the behavior of five participants with greater than three years of meditative experience and 5 persons with no meditative background is analyzed in resting and meditative positions. The behavioral changes in the meditators versus novices concerning EEG signal components such as alpha α, beta β, gamma ϒ, delta ẟ, and theta θ are analyzed with the help of changes observed in parameters such as power, mean, and standard deviation (SD). Then finally, the significance of the results obtained is statistically analyzed by finding the p-value using a t-test, with a 95% confidence interval. A p-value less than 0.05 is considered significant.