Study on indicators for depression in the elderly using voice and attribute information

Masakazu Higuchi, Shuji Shinohara, Mitsuteru Nakamura, Yasuhiro Omiya, Naoki Hagiwara, Takeshi Takano, Shunji Mitsuyoshi, Shinichi Tokuno

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As the age of the human population increases worldwide, depression in elderly patients has become a problem in medical care. In this study, we analyzed voice-emotion component data, attribute data, and Beck Depression Inventory (BDI) scores by multivariate analysis, particularly in the elderly, and proposed evaluation indicators for estimating the state of depression of elderly patients. We divided the data into two groups according to BDI scores: a state of depression and the absence of this state. The labels distinguishing the two groups were dependent variables, while the voice-emotion component and attribute information were set as independent variables, and we performed logistic regression analysis on the data. We obtained a prediction model with significantly sufficient fitness. In the receiver operating characteristic curve for the proposed depression evaluation indicator, a sorting performance with an area under the curve of approximately 0.93 was obtained.

Original languageEnglish (US)
Title of host publicationInformation and Communication Technologies for Ageing Well and e-Health - 3rd International Conference, ICT4AWE 2017, Revised Selected Papers
EditorsLeszek Maciaszek, John O Donoghue, William Molloy, Carsten Rocker, Martina Ziefle
PublisherSpringer Verlag
Pages127-146
Number of pages20
ISBN (Print)9783319936437
DOIs
StatePublished - 2018
Externally publishedYes
Event3rd International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2017 - Porto, Portugal
Duration: Apr 28 2017Apr 29 2017

Publication series

NameCommunications in Computer and Information Science
Volume869
ISSN (Print)1865-0929

Conference

Conference3rd International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2017
Country/TerritoryPortugal
CityPorto
Period4/28/174/29/17

Keywords

  • Attribute information
  • Beck depression inventory
  • Depression
  • Emotion recognition
  • Voice

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

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