Phase space in EEG signals of women refferred to meditation clinic

Poincaré plots, a tool for analyzing non-linear patterns in biological signals, can detect changes in brain activity during meditation. In sixteen healthy women, the width of Poincaré plots of EEG signals increased as the time lag between data points grew from one to six, indicating that meditation alters short-term variability in brain signals. This method offers a simple, quantitative way to evaluate EEG data collected over short periods and adapts well to the chaotic nature of such signals.

Study at a glance

Abstract

Poincare plots are commonly used to study the non-linear behavior of physiological signals. In the time series analysis, the width of Poincare plots can be considered as a criterion of short-term variability in signals. The hypothesis that Poincare plot indexes of electroencephalogram (EEG) signals can detect dy-namic changes during meditation was examined in sixteen healthy women. Therefore, the aim of this study is to evaluate the effect of different lags on the width of the Poincare plots in EEG signals during meditation. Poincare plots with six different lag (1-6) were constructed for two sets of data and the width of the Poincare plot for each lag was calculated. The results show that during meditation the width of Poincare plots tended to increase as the lag increased. The Poincare plot is a quantitative visual tool which can be applied to the analysis of EEG data gathered over relatively short time periods. The simplicity of the width of Poincare plot calculation and its' adap-tation to the chaotic nature of the biological signals could be useful to evaluate EEG signals during me-ditation.