Change in physiological signals during mindfulness meditation

Abstract

Mindfulness meditation (MM) is an inward mental practice, in which a resting but alert state of mind is maintained. MM intervention was performed for a population of older people with high stress levels. This study assessed signal processing methodologies of electroencephalographic (EEG) and respiration signals during meditation and control condition to aid in quantification of the meditative state. EEG and respiration data were collected and analyzed on 34 novice meditators after a 6-week meditation intervention. Collected data were analyzed with spectral analysis and support vector machine classification to evaluate an objective marker for meditation. We observed meditation and control condition differences in the alpha, beta and theta frequency bands. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy at discriminating between meditation and control conditions than one using the EEG signal only. EEG and respiration based classifier is a viable objective marker for meditation ability. Future studies should quantify different levels of meditation depth and meditation experience using this classifier. Development of an objective physiological meditation marker will allow the mind-body medicine field to advance by strengthening rigor of methods.

Fig. 1

(a) Electrodes divided into six regions over scalp as frontal, central, parietal, occipital, right temporal and left temporal.

Fig. 2

PSD estimation of EEG signal over Alpha, Beta and Theta bands at different location over scalp for meditation and control conditions averaged across subjects (N=34).

Fig. 3

Time frequency Analysis of respiration signal shows more activity in lower frequencies during meditation. The figure shows the Stockwell coefficients amplitude averaged across subjects (N=34) in meditation and control conditions.

Fig. 4

SVM classification accuracy using EEG, Respiration and joint (N=29).