Common spatial pattern for classification of loving kindness meditation EEG for single and multiple sessions
Brain Informatics September 9, 2023 Nalinda D. Liyanagedera, Ali Abdul Hussain, Amardeep Singh et al. 4 citations
Classifying loving kindness meditation (LKM) from non-meditation using electroencephalography (EEG) data is possible for both single and multiple sessions. For a single session with 32 participants, classification accuracy reached about 99.5% for distinguishing meditation from pre-resting states. For 15 participants across five sessions, accuracy was about 83.6%. Common Spatial Patterns, a feature extraction method typically used in motor imagery brain-computer interfaces, was applied to meditation EEG data for the first time. Comparisons among four mind tasks—pre-resting, post-resting, LKM directed toward self, and LKM directed toward others—showed that pre-resting states were more easily distinguished from the other three, suggesting pre-resting has distinct neural features.