Alzheimer disease diagnosis based on automatic spontaneous speech analysis


Autoria(s): Lopez-de-Ipiña, Karmele; Alonso, Jesús B.; Solé-Casals, Jordi; Barroso, Nora; Faundez-Zanuy, Marcos; Ecay-Torres, Miriam; Travieso, Carlos M.; Ezeiza, Aitzol; Estanga, A.
Contribuinte(s)

Universitat de Vic. Escola Politècnica Superior

Universitat de Vic. Grup de Recerca en Tecnologies Digitals

International Joint Conference on Computational Intelligence (4rt : 2012 : Barcelona, Catalunya)

Data(s)

2012

Resumo

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.

Formato

8 p.

Identificador

http://hdl.handle.net/10854/2482

Idioma(s)

eng

Publicador

SciTePress - Science and Technology Publications

Direitos

(c) SciTePress - Science and Technology Publications

Tots els drets reservats

Palavras-Chave #Alzheimer, Malaltia d'
Tipo

info:eu-repo/semantics/conferenceObject