Meditation styles are highly discriminable from EEG at the subject level with limited generalization across the population: a machine-learning study

Meditation has been associated with improvements in attention, emotional regulation, and mental wellbeing, motivating increasing interest in objective methods for assessing meditative states. In this study, we investigate whether EEG-based machine learning can reliably distinguish between multiple meditation styles and mind-wandering states. EEG data were recorded from experienced meditators performing three meditation styles, Shamatha, Vipassana, and Metta, together with an eyes-closed mind-wan

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ethics.ai (14 August 2026), “Meditation styles are highly discriminable from EEG at the subject level with limited generalization across the population: a machine-learning study,” evidence record 19553, https://ethics.ai/record/19553 (originally published by Frontiers in Artificial Intelligence).

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