Improving Early Diagnosis of Alzheimer's Disease Using Synchrony Measures

Gallego Jutglà, Esteve; Solé-Casals, Jordi

Inici
→
Recerca
→
Articles, congressos, llibres
→
Llibres i capítols de llibres
→
Visualitza el document

dc.contributor	Universitat de Vic. Escola Politècnica Superior
dc.contributor	Universitat de Vic. Grup de Recerca en Tecnologies Digitals
dc.contributor.author	Gallego Jutglà, Esteve
dc.contributor.author	Solé-Casals, Jordi
dc.date.accessioned	2014-03-20T11:05:02Z
dc.date.available	2014-03-20T11:05:02Z
dc.date.created	2013
dc.date.issued	2013
dc.identifier.citation	Gallego-Jutglà, E., & Sole-Casals, J. (2013). In Gibert K., Botti V. and Reig-Bolano R.(Eds.), Improving early diagnosis of alzheimer's disease using synchrony measures A: Frontiers in Artificial Intelligence and Applications, vol. 256, IOS Press, 2013, p. 167-170 doi:10.3233/978-1-61499-320-9-167	ca_ES
dc.identifier.isbn	9781614993193
dc.identifier.issn	0922-6389
dc.identifier.uri	http://hdl.handle.net/10854/2792
dc.description.abstract	It is well-known that Alzheimer's disease causes changes on the electroencephalography of the patients. However those changes are difficult to parameterize. In this paper a new ratio between synchrony in 0 and a band is investigated in arder to get an early diagnosis of Mild Alzheimer's patients. The presented ratio is compared using two types of classifiers, Linear Discriminan! Analysis and Artificial Neural Networks, with values of synchrony in the standard frequency bands. Presented results improve using the ratio in the linear classifier. Using the non-linear classifíer, best results are obtained using synchrony measures in 0 and a band simultaneously.	en
dc.format	application/pdf
dc.format.extent	4 p.	ca_ES
dc.language.iso	eng	ca_ES
dc.publisher	IOS Press	ca_ES
dc.rights	(c) 2013, IOS Press
dc.rights	Tots els drets reservats	ca_ES
dc.subject.other	Alzheimer, Malaltia d'	ca_ES
dc.title	Improving Early Diagnosis of Alzheimer's Disease Using Synchrony Measures	en
dc.type	info:eu-repo/semantics/bookPart	ca_ES
dc.identifier.doi	https://doi.org/:I0.3233/978-1-61499-320-9-167
dc.relation.publisherversion	http://ebooks.iospress.nl/publication/35243
dc.rights.accessRights	info:eu-repo/semantics/closedAccess	ca_ES