Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/44023
Título: Alzheimer disease diagnosis based on automatic spontaneous speech analysis
Autores/as: Lopez-De-Ipina, K.
Alonso, J. B. 
Solé-Casals, J.
Barroso, N.
Faundez, M.
Ecay, M.
Travieso, C. 
Ezeiza, A.
Estanga, A.
Fecha de publicación: 2012
Publicación seriada: IJCCI 2012 - Proceedings of the 4th International Joint Conference on Computational Intelligence
Conferencia: 4th International Joint Conference on Computational Intelligence, IJCCI 2012 
Resumen: Alzheimer's disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to im-provement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.
URI: http://hdl.handle.net/10553/44023
ISBN: 9789898565334
Fuente: IJCCI 2012 - Proceedings of the 4th International Joint Conference on Computational Intelligence, p. 698-705
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