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

Authors

DOI:

https://doi.org/10.19053/01211129.v30.n55.2021.12489

Keywords:

Attention, Electroencephalogram, Meditation, Neurofeedback, Relaxation, Training

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

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.

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Published

2021-03-31

How to Cite

Nieto-Vallejo, A. E., Ramírez-Pérez, O. F., Ballesteros-Arroyave, L. E., & Aragón, A. (2021). Design of a Neurofeedback Training System for Meditation Based on EEG Technology. Revista Facultad De Ingeniería, 30(55), e12489. https://doi.org/10.19053/01211129.v30.n55.2021.12489

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