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Towards a highly accurate mental activity detection bay electroencephalography sensor networks

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Towards a highly accurate mental activity detection bay electroencephalography sensor networks

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dc.contributor.advisor Fischione, Carlo es_ES
dc.contributor.author Ruiz Calvo, Félix es_ES
dc.date.accessioned 2013-05-27T07:03:16Z
dc.date.available 2013-05-27T07:03:16Z
dc.date.created 2012-03
dc.date.issued 2013-05-27
dc.identifier.uri http://hdl.handle.net/10251/29143
dc.description.abstract Consulta en la Biblioteca ETSI Industriales (8956) es_ES
dc.description.abstract [eng]The possibility to detect reliably human brain signals by small sensors can have substantial impact in healthcare, training, and rehabilitation. This Master the- sis studies Electroencephalography (EEG) wireless sensors, and the properties of their signals. The main goal is to investigate the problem of data interpre- tation accuracy. The measurements provided by small wireless EEG sensors show high variability and high noises, which makes it di_cult to interpret the brain signals. The analysis is further exacerbated by the di_culty in statistical modeling of these signals. This work presents an attempt to a simple statistical modeling of brain signals. Then, based on such a modeling, an optimal data fusion rule of sensors readings is proposed so to reach a high accuracy in the signal's interpretation. An experimental implementation of the data fusion by real EEG wireless sensors is developed. The experimental results show that the fusion rule provides an error probability of nearly 25% in detecting correctly brain signals. It is concluded that substantial improvements have still to be done to understand the statistical properties of signals and develop optimal decision rules for the detection. es_ES
dc.language Inglés es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Consulta en la Biblioteca ETSI Industriales es_ES
dc.subject Electroencefalografía es_ES
dc.subject.classification ELECTRONICA es_ES
dc.subject.other Ingeniero Industrial-Enginyer Industrial es_ES
dc.title Towards a highly accurate mental activity detection bay electroencephalography sensor networks es_ES
dc.type Proyecto/Trabajo fin de carrera/grado es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.description.bibliographicCitation Ruiz Calvo, F. (2012). Towards a highly accurate mental activity detection bay electroencephalography sensor networks. http://hdl.handle.net/10251/29143. es_ES
dc.description.accrualMethod Archivo delegado es_ES


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