Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44023
Title: Alzheimer disease diagnosis based on automatic spontaneous speech analysis
Authors: Lopez-De-Ipina, K.
Alonso, J. B. 
Solé-Casals, J.
Barroso, N.
Faundez, M.
Ecay, M.
Travieso, C. 
Ezeiza, A.
Estanga, A.
Issue Date: 2012
Journal: IJCCI 2012 - Proceedings of the 4th International Joint Conference on Computational Intelligence
Conference: 4th International Joint Conference on Computational Intelligence, IJCCI 2012 
Abstract: 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
Source: IJCCI 2012 - Proceedings of the 4th International Joint Conference on Computational Intelligence, p. 698-705
Appears in Collections:Actas de congresos
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