Analysis of EEG Signals and Biomedical Changes Due to Meditation on Brain by Using ICA for Feature Extraction
Kajal S. Korde, P. Paikrao, N. Jadhav
International Conference Intelligent Computing and Control Systems June 1, 2018 DOI: 10.1109/iccons.2018.8663129 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational study Peer reviewed |
|---|---|
| Sample size | 22 |
| Population | 11 subjects with mindfulness meditation practice and 11 non-meditation subjects |
| Intervention | Mindfulness meditation |
| Topics | Meditation |
| Key findings | The work compares EEG features between mindfulness meditators and non-meditators, using wavelet-based statistical features and Fast Independent Component Analysis to categorize the two groups. No outcome of this comparison is reported in the available text. |
Abstract
Meditation imparts relaxation to the human being. Nowadays due to worrying and tense atmosphere, the meditation has become demanding solution to reduce physical and mental stress. The current experimentation aims at investigating the biomedical changes of meditation on the human brain. The term meditation refers to an extremely wide variety of practices. The central goal of these meditation practices is to alter mental states. However, the manner in which this goal is pursued in the variety of practices differs from person to person each so that as of today no clear definition of necessary and sufficient criteria for meditation exists that has achieved universal or widespread acceptance. Meditation can be characterized by concentration of attention on the breath, the recitation of a mantra, the state of calmness, mental freedom and the cultivation of a compassionate state. The major focus of fundamental research on meditation is to observe and analyze the changes in brain activation, functioning and anatomy induced by mental training. In this research work, 11 subjects with Mindfulness meditation practice and 11 subjects of non-meditation group are considered. The EEG signals are obtained by using 14 electrode systems. The pre-processing technique used is Daubechies wavelet transform before calculating the statistical features. The statistical features calculated are variance, kurtosis, energy and entropy. Along with these four features, the three features are calculated by using Fast Independent Component Analysis (fast ICA). These features are averaged and plot in order to categorize between meditational and non-meditational group.
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
Cited by 4
- Meditation and Complexity: a Systematic Review June 28, 2023
- Meditation and complexity: a review and synthesis of evidence. Neuroscience of Consciousness 2025
- Feature Representation for Meditation State Classification in EEG Signal International Conference on Information Technology in Medicine and Education November 1, 2021
- Feature extraction and calibration of EEG signals in sitting and walking meditation International Conferences on Knowledge Innovation and Invention July 1, 2019