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

Title Analysis of speech-based measures for detecting and monitoring Alzheimer’s disease
Author Khodabakhsh, Ali, Demiroğlu, Cenk
Publication Date: 2014
Publication Place - Springer Science+Business Media
Subject Alzheimer’s disease, Speech analysis, Support vector machines
Type Book
Language English
Digital Yes
Manuscript No
Library: Özyeğin University
Library Asset ID 978-1-4939-1985-7
Record ID 0ed2bc37-26b7-4da9-ad5e-684365849f6a
Library Location Electrical & Electronics Engineering
Date 2014
Notes Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text 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

Author Khodabakhsh, Ali, Demiroğlu, Cenk
Publication Date 2014
Publication Place - Springer Science+Business Media
Subject Alzheimer’s disease, Speech analysis, Support vector machines
Type Book
Language English
Digital Yes
Manuscript No
Library Özyeğin University
Library Asset ID 978-1-4939-1985-7
Record ID 0ed2bc37-26b7-4da9-ad5e-684365849f6a
Library Location Electrical & Electronics Engineering
Date 2014
Notes Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text 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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