Simple Neurofeedback via Machine Learning: Challenges in real time multivariate assessment of meditation state
Sruthi Susan Kuriakose, Aishwarya Swamy, Rahul Venugopal, Arun Sasidharan
bioRxiv Preprint Server September 27, 2022 preprint DOI: 10.1101/2022.09.27.509655 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or methodological paper |
|---|---|
| Population | Long-term meditation practitioners |
| Intervention | EEG neurofeedback |
| Topics | Meditation |
| Citations | 2 |
| Key points | Proposes that an autoencoder model trained on EEG features from long-term meditation practitioners can provide real-time neurofeedback parameters for assessing meditation state, but experimental results suggest substantial overlap in multivariate EEG features and prominent temporal dynamics not captured by simple one-class algorithms. |
Abstract
Attaining proficiency in meditation is difficult, especially without feedback since the mind may be easily distracted with thoughts and only long term efforts see any impact. Self-regulation would be much more effective if provided real time assessment and this can be achieved through EEG neurofeedback. Therefore, this work proposes a scheme for assessing meditation-like state in real time from short EEG segments, using low computational settings. Signal processing techniques are used to extract features from long term meditation practitioners’ multichannel EEG data. An autoencoder model is then trained on these features such that the model can be run in real time. Its reconstruction errors or its latent variables are used to provide non typical feedback parameters which are used to establish an objective measure of meditation ability. Our approach is optimised to have lightweight architectures handling small blocks of data and can be conveniently used on low density EEG acquisition systems as it requires only a few channels. However, our experimental results suggest that the meditation state has substantial overlap even in terms of multivariate EEG features and show prominent temporal dynamics, both of which are not captured using simple one class algorithms. Being an extremely flexible one-class model, we have described multiple improvements to the proposed autoencoder model to address the above issues and develop simple yet high precision neurofeedback protocols.
Comparable studies
Other theoretical and historical papers on meditation, most cited first.
| Study | Year | Design | Participants |
|---|---|---|---|
| Mindfulness: A proposed operational definition. | 2004 | Theoretical or philosophical paper | |
| Mechanisms of mindfulness | 2005 | Theoretical or philosophical paper | |
| How Does Mindfulness Meditation Work? Proposing Mechanisms of Action From a Conceptual and Neural Perspective | 2011 | Theoretical or philosophical paper | |
| Mindfulness-based cognitive therapy for depression | 2006 | Theoretical or philosophical paper | |
| Self-awareness, self-regulation, and self-transcendence (S-ART): a framework for understanding the neurobiological mechanisms of mindfulness | 2012 | Theoretical or philosophical paper |
Citations in the library
Cited by 2
- EEG-based meditation decoding: tackling subject variability with spatial and temporal alignment. Journal of Neural Engineering December 22, 2025
- Cross-Subject Mindfulness Meditation EEG Decoding 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering October 25, 2023
Cites 6
- Non-Linear EEG Measures in Meditation Journal of Biomedical Science and Engineering 2014
- Mindfulness induction and cognition: A systematic review and meta-analysis. Consciousness and Cognition July 30, 2020
- The Effects of Different Stages of Mindfulness Meditation Training on Emotion Regulation Frontiers in Human Neuroscience June 27, 2019
- Dissociating meditation proficiency and experience dependent EEG changes during traditional Vipassana meditation practice. Biological Psychology May 1, 2018
- Cost-effectiveness of Mindfulness-based Stress Reduction Versus Cognitive Behavioral Therapy or Usual Care Among Adults With Chronic Low Back Pain. Spine October 15, 2017
and 1 more in the library