Investigation on Spatiotemporal Characteristics of Zen-Meditation EEG Rhythms

抄録

This paper reports a unique interpreter that combines a multi-resolution scheme with autoregressive modeling to identify the EEG (electroencephalograph) patterns including the flat wave (φ), δ, θ, χ, α, and β activities as well as such artifacts as the baseline drift and EMG (electromyograph) interference. With the merits of high computational efficiency and easy hardware realization, the method proposed is feasible for long-term EEG monitoring and online EEG processing. It also allows a quick overview of an enormous amount of EEG data. Moreover, results of applying the proposed scheme to an experimental group (Zen meditation practitioners) and a control group (normal, healthy subjects) reveal significant distinction in spatiotemporal characteristics of EEG rhythmic patterns, especially the spatial propagation of the β rhythm during meditation sessions.