• 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