METODOLOGÍA PARA EL ESTUDIO DE SEÑALES SINÁPTICAS MEDIANTE UN SISTEMA DE EEG PORTÁTIL (METHODOLOGY FOR STUDYING SYNAPTIC SIGNALS USING A PORTABLE EEG SYSTEM)
Resumen
El EMOTIV EPOC+ es un sistema de electroencefalograma (EEG) portátil de alta resolución frecuentemente utilizado para sistemas BCI que es una interfaz de computadora con el cerebro. La interfaz cerebro-computadora (BCI) a través de la electroencefalografía (EEG) atrae la atención de la comunidad científica gracias a sus últimas mejoras en términos de rendimiento y aplicaciones. Mediante el software EmotivPRO se adquieren las señales EEG del EPOC + a través de conexión Bluetooth entre el auricular y la computadora. El análisis en frecuencia permite la detección y el estudio de trastornos psicológicos, el software EmotivPro permite obtener las frecuencias fundamentales derivadas del cálculo de la Transformada Rápida de Fourier. Esta información ha sido utilizada por diversos autores para el análisis de patologías psicológicas. El presente estudio se centra en el uso del Emotiv Epoc utilizando el software EmotivPro para obtener las señales alpha, beta, theta y gamma ya que estas son los marcadores que diferencian entre una persona sana y una persona con algún tipo de trastorno psicológico.
Palabras Clave: Electroencefalograma, Emotiv, trastorno psicológico.
Abstract
The EMOTIV EPOC + is a high resolution portable electroencephalogram (EEG) system frequently used for BCI systems that is a computer interface to the brain. The brain-computer interface (BCI) through electroencephalography (EEG) attracts the attention of the scientific community thanks to its latest improvements in terms of performance and applications. Through the EmotivPRO software, the EEG signals of the EPOC + are acquired through a Bluetooth connection between the headset and the computer. The frequency analysis allows the detection and study of psychological disorders, the EmotivPro software allows obtaining the fundamental frequencies derived from the calculation of the Fast Fourier Transform. This information has been used by various authors for the analysis of psychological pathologies. The present study focuses on the use of the Emotiv Epoc using the EmotivPro software to obtain the alpha, beta, theta and gamma signals since these are the markers that differentiate between a healthy person and a person with some type of psychological disorder.
Keywords: Electroencephalogram, Emotiv, psychological disorder.
Texto completo:
504-512 PDFReferencias
Acar, D., Miman, M., & Akirmak, O. (2014). Treatment of anxiety. European Social Sciences Research, 18-27.
Alaa, A., Elsharnouby, E., Shirmohammadi, M., ShervinEddin, & Nour, A. (2017). Feasibility of Detecting ADHD Patients Attention Levels by Classifying Their EEG Signals. IEEE Instrumentation and Measurement Society.
Benedetti, F., Volpi, N. C., Parisi, L., & Sartori, G. (2014). Attention Training with an Easy–to–Use Brain Computer Interface. Springer International Publishing Switzerland.
Benítez, D., Toscano, S., & Silva, A. (2016). On the Use of the Emotiv EPOC Neuroheadset as a Low Cost Alternative for EEG Signal Acquisition.
Chowdhury, P., Shakim, S. S., Karim, M. R., & Rhaman, M. K. (2014). Cognitive Efficiency in Robot Control by Emotiv EPOC. 3rd INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS & VISION.
Duvinage, M., Castermans, T., & Dutoit, T. (2012). A P300-based Quantitative Comparison between the Emotiv Epoc Headset and a Medical EEG Device. BioMedical Engineering OnLine.
Eddin, A., Shervin, A., Fellow, S., Nour, A., & Elsharnouby, M. (2018). FOCUS: Detecting ADHD Patients by an EEG-Based Serious Game. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 67(7).
Holewa, K., & Nawrocka, A. (2014). Emotiv EPOC neuroheadset in Brain – Computer Interface. 15th International Carpathian Control Conference (ICCC).
Mercado-Aguirre, I., Gutierrez-Ruiz, K., & Contreras-Ortiz, S. (2019). Acquisition and Analysis of Cognitive Evoked Potentials using an Emotiv Headset for ADHD Evaluation in Children. XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA).
Nazari, M. A., Wallois, F., Aarabi, A., & Aarabi, A. (2011). Dynamic changes in quantitative electroencephalogram during continuous performance test in children with attention-deficit/hyperactivity disorder. International Journal of Psychophysiology, 230-236.
Ogrim, G., Kropotov, J., & Hestad, K. (2011). The quantitative EEG theta/beta ratio in attention deficit/hyperactivity disorder and normal controls: Sensitivity, specificity, and behavioral correlates. Psychiatry Research.
Strmiskaa, M., & Koudelkova, Z. (2018). Analysis of Performance Metrics Using Emotiv EPOC+. 22nd International Conference on Circuits, Systems, Communications and Computers.
URL de la licencia: https://creativecommons.org/licenses/by/3.0/deed.es
Pistas Educativas está bajo la Licencia Creative Commons Atribución 3.0 No portada.
TECNOLÓGICO NACIONAL DE MÉXICO / INSTITUTO TECNOLÓGICO DE CELAYA
Antonio García Cubas Pte #600 esq. Av. Tecnológico, Celaya, Gto. México
Tel. 461 61 17575 Ext 5450 y 5146
pistaseducativas@itcelaya.edu.mx