Memorias de investigación
Artículos en revistas:
Two Different Approaches of Feature Extraction for Classifying the EEG Signals
Año:2011
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
The electroencephalograph (EEG) signal is one of the most widely used signals in the biomedicine field due to its rich information about human tasks. This research study describes a new approach based on i) build reference models from a set of time series, based on the analysis of the events that they contain, is suitable for domains where the relevant information is concentrated in specific regions of the time series, known as events. In order to deal with events, each event is characterized by a set of attributes. ii) Discrete wavelet transform to the EEG data in order to extract temporal information in the form of changes in the frequency domain over time- that is they are able to extract non-stationary signals embedded in the noisy background of the human brain. The performance of the model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed scheme has potential in classifying the EEG signals.
Internacional
Si
JCR del ISI
No
Título de la revista
IFIP Advances in Information and Communication Technology. Engineering Applications of Neural Networks. Iliadis, L. et al. (Eds.)
ISSN
1868-4238
Factor de impacto JCR
0
Información de impacto
Volumen
363
DOI
10.1007/978-3-642-23957-1
Número de revista
Desde la página
229
Hasta la página
239
Mes
SEPTIEMBRE
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Investigación en Tecnología Informática y de las Comunicaciones: CETTICO