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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
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 869)

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.

Keywords

Voice Emotion recognition Depression Beck depression inventory Attribute information 

Notes

Acknowledgements

This research is (partially) supported by the Center of Innovation Program from Japan Science and Technology Agency, JST. This work was supported by JSPS KAKENHI Grant Numbers JP15H03002 and JP17K01404.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Masakazu Higuchi
    • 1
  • Shuji Shinohara
    • 1
  • Mitsuteru Nakamura
    • 1
  • Yasuhiro Omiya
    • 2
  • Naoki Hagiwara
    • 2
  • Takeshi Takano
    • 2
  • Shunji Mitsuyoshi
    • 1
  • Shinichi Tokuno
    • 1
  1. 1.Verbal Analysis of Pathophysiology, Graduate School of MedicineThe University of TokyoTokyoJapan
  2. 2.Research and Product Development Department, PST Inc.KanagawaJapan

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