Design of a Neurofeedback Training System for Meditation Based on EEG Technology

Diseño de un sistema de retroalimentación neuronal para el entrenamiento de la meditación basado en electroencefalograma

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Andrés Eduardo Nieto-Vallejo, M.Sc.
Omar Fernando Ramírez-Pérez, M.Sc.
Luis Eduardo Ballesteros-Arroyave

Abstract

Meditation is a form of mental training that has therapeutic potential and cognitive benefits that may enhance attention, mental well-being, and neuroplasticity. However, the learning process is not easy because meditators do not receive immediate feedback that lets them know if they are correctly doing the activity. EEG Neurofeedback training is one of the techniques to train brain self-regulation and it has the potential to increase the effectiveness of meditation. However, the benefits greatly differ between subjects with a high percentage of inefficacy. In this work, an EEG Neurofeedback Training System is proposed based on user-centered design methodology to provide real-time performance feedback to meditators to increase levels of attention and relaxation through a visual, sound and smell stimuli interface. Levels of attention and relaxation of nine participants were measured with a mobile Neurosky EEG headset biosensor during meditation practice to analyze the incidence of each type of stimuli during activity. Visual stimuli feedback was able to increase attention levels of 78% of the participants by 11.8% compared to a meditation session without any stimuli. The sound stimuli feedback was able to increase the relaxation levels of 44.4% of the participants by 16% compared to a session without any stimuli. These results might bring new insights for the design of a neurofeedback system interface for meditation. Further research on neurofeedback training interfaces for meditators is suggested to validate these results with more participants.

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Author Biographies (SEE)

Andrés Eduardo Nieto-Vallejo, M.Sc., Pontificia Universidad Javeriana

Roles:  Data curation, Formal Analysis, Methodology, Software, Validation, Writing-Original draft, Writing- review editing.

Omar Fernando Ramírez-Pérez, M.Sc., Pontificia Universidad Javeriana

Roles: Formal Analysis, Data curation, Writing-Original draft, Writing- review editing.

Luis Eduardo Ballesteros-Arroyave, Pontificia Universidad Javeriana

Roles: Conceptualization, Methodology, Data curation Writing-Original draft.

Angela Aragón, Pontificia Universidad Javeriana

Roles: Conceptualization, Methodology, Data curation Writing-Original draft.

References (SEE)

[1] A. Lutz, H. A. Slagter, J. D. Dunne, R. J. Davidson, “Attention regulation and monitoring in meditation,” Trends in Cognitive Sciences, vol. 12, no. 4, pp. 163-169, 2008. https://doi.org/10.1016/j.tics.2008.01.005

[2] A. P. Jha, J. Krompinger, M. J. Baime, “Mindfulness training modifies subsystems of attention,” Cognitive, Affective, & Behavioral Neuroscience, vol. 7, pp. 109-119, 2007. https://doi.org/10.3758/CABN.7.2.109

[3] A. Fingelkurts, A. Fingelkurts, T. Kallio-Tamminen, “EEG-guided meditation: A personalized approach,” Journal of Physiology-Paris, vol. 109, no. 4–6, pp. 180-190, 2015. https://doi.org/10.1016/j.jphysparis.2015.03.001

[4] T. D. Wager, J. K. Rilling, E. E. Smith, A. Sokolik, K. L. Casey, R. J. Davidson, J. D. Cohen, “Placebo-induced changes in FMRI in the anticipation and experience of pain,” Science, vol. 303, no. 5661, pp. 1162-1167, 2004. https://doi.org/10.1126/science.1093065

[5] R. J. Davidson, J. Kabat-Zinn, J. Schumacher, M. Rosenkranz, D. Muller, S. F. Santorelli, J. F. Sheridan, “Alterations in brain and immune function produced by mindfulness meditation,” Psychosomatic medicine, vol. 65, no. 4, pp. 564-570, 2003. https://doi.org/10.1097/01.psy.0000077505.67574.e3

[6] G. N. Levine, R. A. Lange, C. N. Bairey‐Merz, R. J. Davidson, K. Jamerson, P. K. Mehta, T. Shah, “Meditation and cardiovascular risk reduction: a scientific statement from the American Heart Association,” Journal of the American Heart Association, vol. 6, no. 10, e002218, 2017. https://doi.org/10.1161/JAHA.117.002218

[7] R. J. Davidson, A. Lutz, “Buddha's brain: Neuroplasticity and meditation,” IEEE Signal Processing Magazine, vol. 25, no. 1, pp. 176-174, 2008. https://doi.org/10.1109/msp.2008.4431873

[8] B. Ülker, M. B. Tabakcıoğlu, H. Çizmeci, D. Ayberkin, “Relations of attention and meditation level with learning in engineering education,” in 9th International Conference on Electronics, Computers and Artificial Intelligence, 2017, pp. 1-4. https://doi.org/10.1109/ECAI.2017.8166407

[9] R. van Lutterveld, S. D. Houlihan, P. Pal, M. D. Sacchet, C. McFarlane-Blake, P. R. Patel, J. S. Sullivan, A. Ossadtchi, S. Druker, C. Bauer, J. A. Brewer, “Source-space EEG neurofeedback links subjective experience with brain activity during effortless awareness meditation,” NeuroImage, vol. 151, pp. 117-127, 2017. https://doi.org/10.1016/j.neuroimage.2016.02.047

[10] H. Hunkin, D. L. King, I. Zajac, “EEG Neurofeedback During Focused Attention Meditation: Effects on State Mindfulness and Meditation Experiences,” Mindfulness, vol 12, pp. 841-851, 2020. https://doi.org/10.1007/s12671-020-01541-0

[11] M. Navarro Gil, C. Escolano Marco, J. Montero-Marín, J. Minguez Zafra, E. Shonin, J. García Campayo, “Efficacy of Neurofeedback on the Increase of Mindfulness-Related Capacities in Healthy Individuals: a Controlled Trial”, Mindfulness, vol. 9, pp. 303–311, 2018. https://doi.org/10.1007/s12671-017-0775-1

[12] P. Supoo, P. Sittiprapaporn, "Brainwave Activity and Cognitive Performance Investigated by Meditation Yoga," in 16th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, 2019, pp. 482-485. https://doi.org/10.1109/ECTI-CON47248.2019.8955411

[13] P. Stapleton, J. Dispenza, S. McGill, D. Sabot, M. Peach, D. Raynor, “Large effects of brief meditation intervention on EEG spectra in meditation novices,” IBRO Reports, vol. 9, pp. 290-301, 2020. https://doi.org/10.1016/j.ibror.2020.10.006

[14] J. H. Gruzelier, “EEG-neurofeedback for optimising performance. I: A review of cognitive and affective outcome in healthy participants,” Neuroscience & Biobehavioral Reviews, vol. 44, pp. 124-141, 2014. https://doi.org/10.1016/j.neubiorev.2013.09.015

[15] M. Alimardani, L. Kemmeren, K. Okumura, K. Hiraki, "Robot-Assisted Mindfulness Practice: Analysis of Neurophysiological Responses and Affective State Change," in 29th IEEE International Conference on Robot and Human Interactive Communication, 2020, pp. 683-689. https://doi.org/10.1109/RO-MAN47096.2020.9223428

[16] D. Crivelli, G. Fronda, I. Venturella, M. Balconi, “Supporting Mindfulness Practices with Brain-Sensing Devices. Cognitive and Electrophysiological Evidences,” Mindfulness, vol. 10, pp. 301–311, 2019. https://doi.org/10.1007/s12671-018-0975-3

[17] T. Yamsa-ard, Y. Wongsawat, "The relationship between EEG and binaural beat stimulation in meditation," in 7th Biomedical Engineering International Conference, 2014, pp. 1-4. https://doi.org/10.1109/BMEiCON.2014.7017405

[18] A. Choo, A. May, "Virtual mindfulness meditation: Virtual reality and electroencephalography for health gamification," in IEEE Games Media Entertainment, 2014, pp. 1-3. https://doi.org/10.1109/GEM.2014.7048076

[19] C. Chen, Y. Tang, N. Zhang, J. Shin, "Neurofeedback based attention training for children with ADHD," in IEEE 8th International Conference on Awareness Science and Technology, 2017, pp. 93-97. https://doi.org/10.1109/ICAwST.2017.8256530

[20] T. Wei, C. Young, "A mobile approach for neurofeedback cognitive enhancement," in IEEE International Symposium on Medical Measurements and Applications Proceedings, 2015, pp. 191-195. https://doi.org/10.1109/MeMeA.2015.7145197

[21] Y. Liu, O. Sourina, X. Hou, "Neurofeedback Games to Improve Cognitive Abilities," in International Conference on Cyberworlds, Santander, 2014, pp. 161-168. https://doi.org/10.1109/CW.2014.30

[22] W. L. Lim, O. Sourina, L. Wang, "MIND - An EEG Neurofeedback Multitasking Game," in International Conference on Cyberworlds, 2015, pp. 169-172. https://doi.org/10.1109/CW.2015.39

[23] E. E. Schaefer, “Using Neurofeedback and Mindfulness Pedagogies to Teach Open Listening,” Computers and Composition, vol. 50, pp. 78-104, 2018. https://doi.org/10.1016/j.compcom.2018.07.002

[24] W. Jinn-Rong, H. Shulan, “Neurofeedback training improves attention and working memory performance,” Clinical Neurophysiology, vol. 124, no. 12, pp. 2406-2420, 2013. https://doi.org/10.1016/j.clinph.2013.05.020

[25] G. Huang, J. Liu, L. Li, L. Zhang, Y. Zeng, L. Ren, S. Ye, Z. Zhang, “A novel training-free externally-regulated neurofeedback (ER-NF) system using phase-guided visual stimulation for alpha modulation,” NeuroImage, vol. 189, pp. 688-699, 2019. https://doi.org/10.1016/j.neuroimage.2019.01.072

[26] C. Jeunet, B. Glize, A. McGonigal, J.-M. Batail, J.-A. Micoulaud-Franchi, “Using EEG-based brain computer interface and neurofeedback targeting sensorimotor rhythms to improve motor skills: Theoretical background, applications and prospects,” Neurophysiologie Clinique, vol. 49, no. 2, pp. 125-136, 2019. https://doi.org/10.1016/j.neucli.2018.10.068

[27] G. A. Mendes, L. Cunha de Miranda, “The influence of graphical elements on user’s attention and control on a neurofeedback-based game,” Entertainment Computing, vol. 29, pp. 10-19, 2019. https://doi.org/10.1016/j.entcom.2018.10.003

[28] N. M. C. da Costa, E. G. Bicho, N. S. Dias, "Priming with mindfulness affects our capacity to self-regulate brain activity?," in IEEE 8th International Conference on Serious Games and Applications for Health, 2020, pp. 1-8, https://doi.org/10.1109/SeGAH49190.2020.9201841

[29] G. Polich, S. Gray, D. Tran, L. Morales-Quezada, M. Glenn “Comparing focused attention meditation to meditation with mobile neurofeedback for persistent symptoms after mild-moderate traumatic brain injury: a pilot study,” Brain Injury, vol. 34, pp. 1408-1415, 2020. https://doi.org/10.1080/02699052.2020.1802781

[30] O. Alkoby, A. Abu-Rmileh, O. Shriki, D. Todder, “Can We Predict Who Will Respond to Neurofeedback? A Review of the Inefficacy Problem and Existing Predictors for Successful EEG Neurofeedback Learning,” Neuroscience, vol. 378, pp. 155-164, 2018. https://doi.org/10.1016/j.neuroscience.2016.12.050

[31] S. Cook, R. M. Baecker, C. Munteanu, A. Walker, “Towards Technologically Assisted Mindfulness Meditation Practice in Older Adults: An Analysis of Difficulties Faced and Design Suggestions for Neurofeedback," Lecture Notes in Computer Science, vol 10285, pp. 423-442, 2017. https://doi.org/10.1007/978-3-319-58625-0_31

[32] T. Brandmeyer, A. Delorme, “Closed-Loop Frontal Midlineθ Neurofeedback: A Novel Approach for Training Focused-Attention Meditation.” Frontiers in Human Neuroscience, vol 14, pp. 246, 2020. https://www.frontiersin.org/article/10.3389/fnhum.2020.00246

[33] P. Desmet, M. Vastenburg, N. Romero, “Pick-A-Mood; development and application of a pictorial mood-reporting instrument,” in 8th International Conference on Design and Emotion: Out of Control - Proceedings, 2012.

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