Processing technique for detecting indices that indicate the MU wave presence in EEG signal

Descripción del Articulo

Modern studies have shown that mirrow neurons are involved in the development of social empathy and language. Consequently, deficiency in mirror neural networks response could be one of the dysfunctions present in autistic spectrum disorder (ASD), as a phenotypic functional expression of channelopat...

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Detalles Bibliográficos
Autores: Alvarez, Antonio, Alvarado, Negman, Reynoso, Sebastián, Gai, Sofia, Cassia, Jorge, Pérez, Santiago, Dugarte, Edinson, Balacco, José, Abraham, Jorge, Molina, Alejandra, Dugarte, Nelson
Formato: artículo
Fecha de Publicación:2019
Institución:Universidad Nacional Hermilio Valdizan
Repositorio:Revistas - Universidad Nacional Hermilio Valdizán
Lenguaje:español
OAI Identifier:oai:revistas.unheval.edu.pe:article/331
Enlace del recurso:http://revistas.unheval.edu.pe/index.php/repis/article/view/331
Nivel de acceso:acceso abierto
Materia:Procesamiento de señales
Detección de la onda MU
Neuronas espejo
Análisis del electroencefalograma
Signal processing
MU wave detection
Mirror neurons
Electroencephalogram analysis
Descripción
Sumario:Modern studies have shown that mirrow neurons are involved in the development of social empathy and language. Consequently, deficiency in mirror neural networks response could be one of the dysfunctions present in autistic spectrum disorder (ASD), as a phenotypic functional expression of channelopathies in some brain regions.Early detection of deficiencies in mirror neural network systems could allow more efficient applications of behavioral therapies in patients with ASD. The detection of MU waves in the electroencephalogram (EEG) could be an interesting technique that refers to the functioning of these neural networks.In this article we present a simple technique, developed with the purpose of identifying the presence of MU waves in the EEG record. It consists of a processing that analyzes each one of the derivations of the EEG, with the implementation of a mathematical method. The signal analysis looks for the changes in the frequency patterns related to the MU waves, discriminating the presence of alpha waves by the association to the patient's response to a conditioned visual stimulus.The preliminary results prove the efficiency of the system. The analysis emphasized frequency alterations in the range of 9 to 12 Hz. The most important responses were obtained with the processing of leads C3, Cz and C4.
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