DocumentCode
3685207
Title
Detection of mild Alzheimer´s disease and mild cognitive impairment from elderly speech: Binary discrimination using logistic regression
Author
Shohei Kato;Akira Homma;Takuto Sakuma;Munehiro Nakamura
Author_Institution
Nagoya Institute of Technology, Gokiso-cho, Showa-ku, 466-8555 Japan
fYear
2015
Firstpage
5569
Lastpage
5572
Abstract
In this research, we have developed a novel data-mining approach for detection of cognitive impairment, SPCIR (Speech Prosody-Based Cognitive Impairment Rating), which can discriminate between mild cognitive impairment and mild Alzheimer´s disease from elderly using prosodic sign extracted from elderly speech during questionnaire test. This paper proposes a binary discrimination model of SPCIR using multivariate logistic regression and model selection using receiver operating characteristic (ROC) curve analysis, and reports the sensitivity and specificity of SPCIR for diagnosis (control; mild cognitive impairment/mild Alzheimer´s disease).
Keywords
"Speech","Dementia","Senior citizens","Sensitivity","Feature extraction"
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
ISSN
1094-687X
Electronic_ISBN
1558-4615
Type
conf
DOI
10.1109/EMBC.2015.7319654
Filename
7319654
Link To Document