Automated Classification of Listening Phases During Mantra Meditation from EEG using empirical Fourier-Bessel Decomposition
Ashok Mahato, Ram Bilas Pachori, Vikram M. Gadre, Dipika Mahapatra
Study at a glance
AI-extracted from the abstract| Characteristics | Observational study |
|---|---|
| Sample size | 28 |
| Population | Subjects listening to Rudram Mantra |
| Topics | Meditation |
| Key findings | The EFBD-based TFR framework achieved 77.5% average accuracy in classifying EEG signals during mantra listening, with consistent cross-subject performance. |
Abstract
Mantra meditation (MM) is known to influence cognitive and emotional processes, and electroencephalogram (EEG) has been widely used to study meditation-related neural activity. However, automated identification of distinct auditory listening phases during MM remains challenging due to the non-stationary nature of EEG signals. This shows the need for physiologically interpretable analysis of meditative states while listening mantra. This study utilizes an empirical Fourier–Bessel decomposition (EFBD)-based time–frequency representation (TFR) framework for automated classification of EEG signals recorded during Rudram Mantra listening. Multichannel EEG data from 28 subjects were preprocessed, segmented into fixed-length epochs, and decomposed using EFBD to obtain oscillatory mode components. The Hilbert transform is applied to derive TFR, from which discriminative features are extracted and selected using a minimum redundancy–maximum relevance algorithm. Classification is performed using machine learning models under subject-dependent and leave-one-subject-out validation schemes. The proposed framework achieved an average accuracy of 77.5%, with stable cross-subject performance. Channel-wise and rhythm-wise analyses highlighted consistent phase-dependent variations, particularly in frontal and temporal regions. These results demonstrated that the proposed EFBD-based TFR framework has been proven effective in monitoring meditative states of subject while listening mantra.
Comparable studies
Other observational and cohort studies on meditation, most cited first.
| Study | Year | Design | Participants |
|---|---|---|---|
| Using Self-Report Assessment Methods to Explore Facets of Mindfulness Undergraduate students | 2006 | Observational cohort | |
| Effectiveness of a meditation-based stress reduction program in the treatment of anxiety disorders Patients with generalized anxiety disorder or panic disorder with or without agoraphobia | 1992 | Observational cohort | n = 22 |
| Meditation experience is associated with increased cortical thickness Participants with extensive Insight meditation experience and matched controls | 2005 | Observational cohort | n = 20 |
| Meditation experience is associated with differences in default mode network activity and connectivity Experienced meditators and matched meditation-naive controls | 2011 | Observational cohort | |
| Long-term meditators self-induce high-amplitude gamma synchrony during mental practice Long-term Buddhist practitioners and controls | 2004 | Observational cohort |
Citations in the library
Cites 9
- Regular, brief mindfulness meditation practice improves electrophysiological markers of attentional control Frontiers in Human Neuroscience 2012
- EEG-based investigation of effects of mindfulness meditation training on state and trait by deep learning and traditional machine learning Frontiers in Human Neuroscience August 31, 2023
- Effect of Mantra Chanting on Power Spectral Density Indian Journal of Science and Technology January 15, 2025
- Decoding Cognitive Load Changes Induced by Mantra Meditation From Physiological Signals Using Deep Neural Networks IEEE Sensors Journal November 14, 2025
- Effectiveness of mantra meditation as a neurophysiological phenomenon for stress management in undergraduate medical students National Journal of Physiology, Pharmacy and Pharmacology April 2, 2026
and 4 more in the library