Abstract Meditation is a self-regulatory process practiced primarily to reduce stress, manage emotions and mental health. The objective was to study the information exchange between symmetric electrodes across the hemispheres during meditation using functional connectivity (FC) measures. We investigate the changes in the coherence between EEG electrode pairs during the meditation practiced by...
This study proposes an approach to classify the EEG into meditation and non-meditation segments using a long short-term memory (LSTM) based deep neural network (DNN) framework. Inter-subject classification performance is assessed on EEG recorded from fourteen long-term Rajayoga meditators. Common spatial pattern is used for feature extraction, and linear discriminant analysis is used for...