Pervasive Computing Paradigms for Mental Health. 9th International Conference, MindCare 2019, Buenos Aires, Argentina, April 23–24, 2019, Proceedings

Research Article

Discrimination of Bipolar Disorders Using Voice

  • @INPROCEEDINGS{10.1007/978-3-030-25872-6_16,
        author={Masakazu Higuchi and Mitsuteru Nakamura and Shuji Shinohara and Yasuhiro Omiya and Takeshi Takano and Hiroyuki Toda and Taku Saito and Aihide Yoshino and Shunji Mitsuyoshi and Shinichi Tokuno},
        title={Discrimination of Bipolar Disorders Using Voice},
        proceedings={Pervasive Computing Paradigms for Mental Health. 9th International Conference, MindCare 2019, Buenos Aires, Argentina, April 23--24, 2019, Proceedings},
        keywords={Voice Bipolar disorders Polytomous logistic regression analysis},
  • Masakazu Higuchi
    Mitsuteru Nakamura
    Shuji Shinohara
    Yasuhiro Omiya
    Takeshi Takano
    Hiroyuki Toda
    Taku Saito
    Aihide Yoshino
    Shunji Mitsuyoshi
    Shinichi Tokuno
    Year: 2019
    Discrimination of Bipolar Disorders Using Voice
    DOI: 10.1007/978-3-030-25872-6_16
Masakazu Higuchi1,*, Mitsuteru Nakamura1,*, Shuji Shinohara1,*, Yasuhiro Omiya2,*, Takeshi Takano2,*, Hiroyuki Toda3,*, Taku Saito3,*, Aihide Yoshino3,*, Shunji Mitsuyoshi1,*, Shinichi Tokuno1,*
  • 1: The University of Tokyo
  • 2: PST Inc.
  • 3: National Defense Medical College
*Contact email:,,,,,,,,,


Several methods have been developed for screening mentally impaired patients using biomarkers, but these methods are invasive and costly. Self-administered tests are also used as screening methods. They are non-invasive and relatively simple, but they cannot eliminate the influence of reporting bias. On the other hand, the authors have conducted studies on technologies for inferring the mental state of persons from their voices. Analysis using voice has the advantage of being noninvasive and easy to perform. This study proposes a vocal index that will distinguish between a healthy person and a bipolar I or II patient using a polytomous logistic regression analysis with patients with bipolar disorder as subjects. When the subjects were classified using the prediction model obtained from the analysis, the subjects were categorized into three groups with an accuracy of approximately . This result suggested that the vocal index could be a new evaluation index for discriminating between subjects with and those without bipolar disorder.