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On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature

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dc.contributor Universitat de Vic. Escola Politècnica Superior
dc.contributor Universitat de Vic. Grup de Recerca en Tecnologies Digitals
dc.contributor.author Lopez-de-Ipiña, Karmele
dc.contributor.author Alonso, Jesús B.
dc.contributor.author Solé-Casals, Jordi
dc.contributor.author Barroso, Nora
dc.contributor.author Henriquez, P.
dc.contributor.author Faundez-Zanuy, Marcos
dc.contributor.author Travieso, Carlos M.
dc.contributor.author Ecay-Torres, Miriam
dc.contributor.author Martinez-Lage, Pablo
dc.contributor.author Egiraun, Harkaitz
dc.date.accessioned 2013-09-18T12:32:43Z
dc.date.available 2015-01-08T00:02:56Z
dc.date.created 2013
dc.date.issued 2013
dc.identifier.citation Lopez-de-Ipina, K., Alonso, J. B., Sole-Casals, J., Barroso, N., Henriquez, P., Faundez-Zanuy, M., et al. (2015). On automatic diagnosis of alzheimer's disease based on spontaneous speech analysis and emotional temperature. Cognitive Computation, 7(1), 44-55. ca_ES
dc.identifier.issn 1866-9956
dc.identifier.uri http://hdl.handle.net/10854/2351
dc.description.abstract Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients. ca_ES
dc.format application/pdf
dc.format.extent 18 p. ca_ES
dc.language.iso eng ca_ES
dc.publisher Springer ca_ES
dc.rights (c) Springer (The original publication is available at www.springerlink.com)
dc.rights Tots els drets reservats ca_ES
dc.subject.other Alzheimer, Malaltia d' ca_ES
dc.subject.other Processament de la parla ca_ES
dc.title On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature ca_ES
dc.type info:eu-repo/semantics/article ca_ES
dc.embargo.terms 12 mesos
dc.identifier.doi https://doi.org/10.1007/s12559-013-9229-9
dc.relation.publisherversion http://link.springer.com/article/10.1007%2Fs12559-013-9229-9
dc.rights.accessRights info:eu-repo/semantics/openAccess ca_ES
dc.type.version info:eu-repo/acceptedVersion ca_ES
dc.indexacio Indexat a WOS/JCR
dc.indexacio Indexat a SCOPUS ca_ES

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