Design of a Neurofeedback Training System for Meditation Based on EEG Technology
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 d...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad Pedagógica y Tecnológica de Colombia
- Repositorio:
- RiUPTC: Repositorio Institucional UPTC
- Idioma:
- eng
spa
- OAI Identifier:
- oai:repositorio.uptc.edu.co:001/14305
- Acceso en línea:
- https://revistas.uptc.edu.co/index.php/ingenieria/article/view/12489
https://repositorio.uptc.edu.co/handle/001/14305
- Palabra clave:
- Attention
Electroencephalogram
Meditation
Neurofeedback
Relaxation
Training
Atención
Electroencefalograma
Meditación
Retroalimentación Neuronal
Relajación
Entrenamiento
- Rights
- License
- http://purl.org/coar/access_right/c_abf16
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dc.title.en-US.fl_str_mv |
Design of a Neurofeedback Training System for Meditation Based on EEG Technology |
dc.title.es-ES.fl_str_mv |
Diseño de un sistema de retroalimentación neuronal para el entrenamiento de la meditación basado en electroencefalograma |
title |
Design of a Neurofeedback Training System for Meditation Based on EEG Technology |
spellingShingle |
Design of a Neurofeedback Training System for Meditation Based on EEG Technology Attention Electroencephalogram Meditation Neurofeedback Relaxation Training Atención Electroencefalograma Meditación Retroalimentación Neuronal Relajación Entrenamiento |
title_short |
Design of a Neurofeedback Training System for Meditation Based on EEG Technology |
title_full |
Design of a Neurofeedback Training System for Meditation Based on EEG Technology |
title_fullStr |
Design of a Neurofeedback Training System for Meditation Based on EEG Technology |
title_full_unstemmed |
Design of a Neurofeedback Training System for Meditation Based on EEG Technology |
title_sort |
Design of a Neurofeedback Training System for Meditation Based on EEG Technology |
dc.subject.en-US.fl_str_mv |
Attention Electroencephalogram Meditation Neurofeedback Relaxation Training |
topic |
Attention Electroencephalogram Meditation Neurofeedback Relaxation Training Atención Electroencefalograma Meditación Retroalimentación Neuronal Relajación Entrenamiento |
dc.subject.es-ES.fl_str_mv |
Atención Electroencefalograma Meditación Retroalimentación Neuronal Relajación Entrenamiento |
description |
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. |
publishDate |
2021 |
dc.date.accessioned.none.fl_str_mv |
2024-07-05T19:11:57Z |
dc.date.available.none.fl_str_mv |
2024-07-05T19:11:57Z |
dc.date.none.fl_str_mv |
2021-03-31 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.coarversion.spa.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a99 |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
https://revistas.uptc.edu.co/index.php/ingenieria/article/view/12489 10.19053/01211129.v30.n55.2021.12489 |
dc.identifier.uri.none.fl_str_mv |
https://repositorio.uptc.edu.co/handle/001/14305 |
url |
https://revistas.uptc.edu.co/index.php/ingenieria/article/view/12489 https://repositorio.uptc.edu.co/handle/001/14305 |
identifier_str_mv |
10.19053/01211129.v30.n55.2021.12489 |
dc.language.none.fl_str_mv |
eng spa |
dc.language.iso.spa.fl_str_mv |
eng spa |
language |
eng spa |
dc.relation.none.fl_str_mv |
https://revistas.uptc.edu.co/index.php/ingenieria/article/view/12489/10553 https://revistas.uptc.edu.co/index.php/ingenieria/article/view/12489/10554 https://revistas.uptc.edu.co/index.php/ingenieria/article/view/12489/10788 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.coar.spa.fl_str_mv |
http://purl.org/coar/access_right/c_abf16 |
rights_invalid_str_mv |
http://purl.org/coar/access_right/c_abf16 http://purl.org/coar/access_right/c_abf2 |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/xml |
dc.publisher.en-US.fl_str_mv |
Universidad Pedagógica y Tecnológica de Colombia |
dc.source.en-US.fl_str_mv |
Revista Facultad de Ingeniería; Vol. 30 No. 55 (2021): January-March 2021 (Continuous Publication); e12489 |
dc.source.es-ES.fl_str_mv |
Revista Facultad de Ingeniería; Vol. 30 Núm. 55 (2021): Enero-Marzo 2021 (Publicación Continua); e12489 |
dc.source.none.fl_str_mv |
2357-5328 0121-1129 |
institution |
Universidad Pedagógica y Tecnológica de Colombia |
repository.name.fl_str_mv |
Repositorio Institucional UPTC |
repository.mail.fl_str_mv |
repositorio.uptc@uptc.edu.co |
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1839633781504344064 |
spelling |
2021-03-312024-07-05T19:11:57Z2024-07-05T19:11:57Zhttps://revistas.uptc.edu.co/index.php/ingenieria/article/view/1248910.19053/01211129.v30.n55.2021.12489https://repositorio.uptc.edu.co/handle/001/14305Meditation 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.La meditación es una forma de entrenamiento mental que tiene potencial terapéutico y beneficios cognitivos que pueden mejorar la atención, el bienestar mental y la neuroplasticidad en el cerebro. Sin embargo, el proceso de aprendizaje no es fácil porque los meditadores no reciben una retroalimentación inmediata que les permita saber si están realizando correctamente la actividad. El entrenamiento basado en retroalimentación neuronal es una de las técnicas para entrenar la autorregulación del cerebro y tiene el potencial de aumentar la efectividad de la meditación. Sin embargo, los beneficios difieren mucho entre sujetos con un alto porcentaje de ineficacia. En este trabajo, se propone un Sistema de Entrenamiento de Retroalimentación Neuronal basado en una metodología de diseño centrada en el usuario para proporcionar retroalimentación de desempeño en tiempo real a los meditadores para aumentar los niveles de atención y relajación a través de una interfaz de estímulos visuales, sonoros y olfativos. Los niveles de atención y relajación de nueve participantes se midieron con una diadema Neurosky EEG durante la práctica de meditación para analizar la incidencia de cada tipo de estímulo durante la actividad. La retroalimentación de estímulos visuales pudo aumentar los niveles de atención del 78% de los participantes en un 11,8% en comparación con una sesión de meditación sin ningún estímulo. La retroalimentación de los estímulos sonoros logró aumentar los niveles de relajación del 44,4% de los participantes en un 16% en comparación con una sesión sin ningún estímulo. Estos resultados podrían aportar nuevos conocimientos para el diseño de una interfaz de sistema de retroalimentación neuronal el entrenamiento de la meditación. Se sugiere realizar más investigaciones sobre las interfaces de entrenamiento de retroalimentación neuronal para meditadores con el fin de validar estos resultados con más participantes.application/pdfapplication/pdfapplication/xmlengspaengspaUniversidad Pedagógica y Tecnológica de Colombiahttps://revistas.uptc.edu.co/index.php/ingenieria/article/view/12489/10553https://revistas.uptc.edu.co/index.php/ingenieria/article/view/12489/10554https://revistas.uptc.edu.co/index.php/ingenieria/article/view/12489/10788Copyright (c) 2021 Andrés Eduardo Nieto-Vallejo, M.Sc., Omar Fernando Ramírez-Pérez, M.Sc., Luis Eduardo Ballesteros-Arroyave, Angela Aragónhttp://purl.org/coar/access_right/c_abf16http://purl.org/coar/access_right/c_abf2Revista Facultad de Ingeniería; Vol. 30 No. 55 (2021): January-March 2021 (Continuous Publication); e12489Revista Facultad de Ingeniería; Vol. 30 Núm. 55 (2021): Enero-Marzo 2021 (Publicación Continua); e124892357-53280121-1129AttentionElectroencephalogramMeditationNeurofeedbackRelaxationTrainingAtenciónElectroencefalogramaMeditaciónRetroalimentación NeuronalRelajaciónEntrenamientoDesign of a Neurofeedback Training System for Meditation Based on EEG TechnologyDiseño de un sistema de retroalimentación neuronal para el entrenamiento de la meditación basado en electroencefalogramainfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a99http://purl.org/coar/version/c_970fb48d4fbd8a85Nieto-Vallejo, Andrés EduardoRamírez-Pérez, Omar FernandoBallesteros-Arroyave, Luis EduardoAragón, Angela001/14305oai:repositorio.uptc.edu.co:001/143052025-07-18 11:53:14.306metadata.onlyhttps://repositorio.uptc.edu.coRepositorio Institucional UPTCrepositorio.uptc@uptc.edu.co |