Introduction of Mind Monitoring System for mental health status monitoring by the vocal analysis

DOI
  • OMIYA YASUHIRO
    PST Inc. Department of Voice Analysis of Pathophysiology Graduate School of Medicine The University of Tokyo
  • Shinohara Shuji
    Department of Mathematical Engineering of Morality Emotions Graduate School of Engineering The University of Tokyo
  • Nakamura Mitsuteru
    Department of Voice Analysis of Pathophysiology Graduate School of Medicine The University of Tokyo
  • Higuchi Masakazu
    Department of Voice Analysis of Pathophysiology Graduate School of Medicine The University of Tokyo
  • Mitsuyoshi Shunji
    Department of Mathematical Engineering of Morality Emotions Graduate School of Engineering The University of Tokyo
  • Tokuno Shinichi
    Department of Voice Analysis of Pathophysiology Graduate School of Medicine The University of Tokyo

Bibliographic Information

Other Title
  • 音声分析に基づくマインドモニタリングシステム(MIMOSYS)の概要

Abstract

<p>Healthy people generally express rich emotions whereas if stress is accumulated, and depressed the expression of emotions declines. Based on our previous research and studies estimate the state of mental health from the aspect of emotional expression using the voice.We developed the core technology that named MIMOSYS (Mind Monitoring System) for measuring the mental health state from the voice, and implemented it on the Android OS smartphone. MIMOSYS inputs speech and outputs two speech indices, Vitality which is a short-term indicator and Mental Activity which is calculated from the long-term tendency of Vitality. In order to verify the medical validity of the MIMOSYS, using as application for smartphone, social implementation research was carried out by the University of Tokyo and it was operated for more than two years. As a result, in the difference between men and women, showed similar trends in speech analysis and self-descriptive questionnaire.</p>

Journal

Details 詳細情報について

  • CRID
    1390564238023948928
  • NII Article ID
    130007484065
  • DOI
    10.11239/jsmbe.annual56.s48
  • ISSN
    18814379
    1347443X
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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