Análisis de señales EEG: Comportamiento de la actividad cerebral durante la exposición a redes sociales
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Date
2026-04-03
Journal Title
Journal ISSN
Volume Title
Publisher
Universidad Tecnológica Centroamericana UNITEC
Abstract
En un entorno en el que las redes sociales desempeñan un papel cada vez más relevante, surge la interrogante acerca de su influencia en la actividad cerebral de los individuos. En este estudio, se abordó esta cuestión utilizando técnicas avanzadas de procesamiento de señales cerebrales. El punto de partida fue una exhaustiva revisión de la literatura científica relacionada con la interacción en redes sociales y su impacto en la actividad cerebral, estableciendo así una base teórica sólida. Para llevar a cabo esta investigación, se diseñó una metodología que incluyó la interacción planificada con varias plataformas de redes sociales, tales como TikTok, Instagram y X. Se utilizó el sistema EEG Ultracortex Mark IV de OpenBCI para registrar las señales cerebrales de los participantes. Los datos recopilados fueron sometidos a un análisis espectral y estadístico, lo que permitió identificar patrones generales en la actividad cerebral de los participantes. Tras analizar la actividad cerebral en relación con la duración de la exposición a las redes sociales en intervalos de 9, 18 y 27 minutos, se observó un aumento en las bandas Delta, Theta y Beta a medida que transcurría el tiempo. Además, se observaron diferencias significativas entre las distintas redes sociales, en particular entre Instagram y X, en las bandas Beta y Gamma.
In an environment where social networks play an increasingly relevant role, the question arises about their influence on individuals' brain activity. This study addressed this issue using advanced techniques for processing brain signals. The starting point was a thorough review of the scientific literature related to social media interaction and its impact on brain activity, thus establishing a solid theoretical foundation. To carry out this research, a methodology was designed, including planned interaction with various social media platforms such as TikTok, Instagram, and X. The EEG system Ultracortex Mark IV from OpenBCI was used to record participants' brain signals. The collected data underwent spectral and statistical analysis, allowing for the identification of general patterns in participants' brain activity. After analyzing brain activity in relation to the duration of exposure to social networks in intervals of 9, 18, and 27 minutes, an increase in the Delta, Theta, and Beta bands was observed as time passed. Furthermore, significant differences were observed between different social networks, particularly between Instagram and X, in the Beta and Gamma bands.
In an environment where social networks play an increasingly relevant role, the question arises about their influence on individuals' brain activity. This study addressed this issue using advanced techniques for processing brain signals. The starting point was a thorough review of the scientific literature related to social media interaction and its impact on brain activity, thus establishing a solid theoretical foundation. To carry out this research, a methodology was designed, including planned interaction with various social media platforms such as TikTok, Instagram, and X. The EEG system Ultracortex Mark IV from OpenBCI was used to record participants' brain signals. The collected data underwent spectral and statistical analysis, allowing for the identification of general patterns in participants' brain activity. After analyzing brain activity in relation to the duration of exposure to social networks in intervals of 9, 18, and 27 minutes, an increase in the Delta, Theta, and Beta bands was observed as time passed. Furthermore, significant differences were observed between different social networks, particularly between Instagram and X, in the Beta and Gamma bands.
Keywords
Actividad cerebral, Análisis espectral, ANOVA, Estudiantes, FFT, Redes sociales