Analysis of speech-based measures for detecting and monitoring Alzheimer’s disease

Name: Analysis of speech-based measures for detecting and monitoring Alzheimer’s disease
Author: Khodabakhsh, Ali, Demiroğlu, Cenk

İsim	Analysis of speech-based measures for detecting and monitoring Alzheimer’s disease
Yazar	Khodabakhsh, Ali, Demiroğlu, Cenk
Basım Tarihi:	2014
Basım Yeri	- Springer Science+Business Media
Konu	Alzheimer’s disease, Speech analysis, Support vector machines
Tür	Kitap
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-1-4939-1985-7
Kayıt Numarası	0ed2bc37-26b7-4da9-ad5e-684365849f6a
Lokasyon	Electrical & Electronics Engineering
Tarih	2014
Notlar	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin	Automatic diagnosis of the Alzheimer’s disease as well as monitoring of the diagnosed patients can make significant economic impact on societies. We investigated an automatic diagnosis approach through the use of speech based features. As opposed to standard tests, spontaneous conversations are carried and recorded with the subjects. Speech features could discriminate between healthy people and the patients with high reliability. Although the patients were in later stages of Alzheimer’s disease, results indicate the potential of speech-based automated solutions for Alzheimer’s disease diagnosis. Moreover, the data collection process employed here can be done inexpensively by call center agents in a real-life application. Thus, the investigated techniques hold the potential to significantly reduce the financial burden on governments and Alzheimer’s patients.
DOI	10.1007/978-1-4939-1985-7_11
Cilt	1246

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Analysis of speech-based measures for detecting and monitoring Alzheimer’s disease

Yazar Khodabakhsh, Ali, Demiroğlu, Cenk

Basım Tarihi 2014

Basım Yeri - Springer Science+Business Media

Konu Alzheimer’s disease, Speech analysis, Support vector machines

Tür Kitap

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-1-4939-1985-7

Kayıt Numarası 0ed2bc37-26b7-4da9-ad5e-684365849f6a

Lokasyon Electrical & Electronics Engineering

Tarih 2014

Notlar Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Örnek Metin Automatic diagnosis of the Alzheimer’s disease as well as monitoring of the diagnosed patients can make significant economic impact on societies. We investigated an automatic diagnosis approach through the use of speech based features. As opposed to standard tests, spontaneous conversations are carried and recorded with the subjects. Speech features could discriminate between healthy people and the patients with high reliability. Although the patients were in later stages of Alzheimer’s disease, results indicate the potential of speech-based automated solutions for Alzheimer’s disease diagnosis. Moreover, the data collection process employed here can be done inexpensively by call center agents in a real-life application. Thus, the investigated techniques hold the potential to significantly reduce the financial burden on governments and Alzheimer’s patients.

DOI 10.1007/978-1-4939-1985-7_11

Cilt 1246