On the analysis of speech and disfluencies for automatic detection of Mild Cognitive Impairment
Visualitza/Obre
Autor/a
Calvo, Paula M.
Beitia, Blanca
García Melero, J.
Fernández, E.
Sanz, P.
Data de publicació
2018-05-08Resum
Alzheimer’s disease is characterized by a progressive and irreversible cognitive deterioration. In a previous stage, the so-called Mild Cognitive Impairment or cognitive loss appears. Nevertheless, this previous stage does not seem sufficiently severe to interfere in independent abilities of daily life, so it is usually diagnosed inappropriately. Thus, its detection is a crucial challenge to be addressed by medical specialists. This paper presents a novel proposal for such early diagnosis based on automatic analysis of speech and disfluencies, and Deep Learning methodologies. The proposed tools could be useful for supporting Mild Cognitive Impairment diagnosis. The Deep Learning approach includes Convolutional Neural Networks and nonlinear multifeature modeling. [...]
Tipus de document
Article
Citació
López-de-Ipiña K, Martinez de Lizarduy U, Calvo PM, Beitia B, García Melero J, Fernández E, Ecay-Torres M, FAundez-Zanuy M, Sanz P. On the analysis of speech and disfluencies for automatic detection of Mild Cognitive Impairment. Neural Comput Applic. 2020;( 32):15761–15769. DOI: 10.1007/s00521-018-3494-1
Drets
(c) López-de-Ipiña K, et al. 2018
Excepte que s'indiqui una altra cosa, la llicència de l'ítem es descriu com http://creativecommons.org/licenses/by/4.0/