ive learning algorithm

Roberto Sepúlveda, Oscar Montiel, Daniel Gutiérrez, Gerardo Díaz, Oscar Castillo

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

Resumen

For the identification of muscular pain caused by a puncture in the right arm and eye blink, electroencephalographic (EEG) signals are analyzed in the frequency and temporal domain. EEG activity was recorded from 15 subjects in range of 23–25 years of age, while pain is induced and during blinking. On the other hand, EEG was converted from time to frequency domain using the Fast Fourier Transform (FFT) for being classified by an Artificial Neural Network (ANN). Experimental results in the frequency and time domain using five adaptation algorithms show that both neural network architecture proposals for classification produce successful results.

Idioma originalInglés
Páginas (desde-hasta)369-380
Número de páginas12
PublicaciónStudies in Computational Intelligence
Volumen547
DOI
EstadoPublicada - 2014

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