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Depressive Mood Assessment Method Based on Emotion Level Derived from Voice: Comparison of Voice Features of Individuals with Major Depressive Disorders and Healthy Controls

Author

Listed:
  • Shuji Shinohara

    (Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan)

  • Mitsuteru Nakamura

    (Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan)

  • Yasuhiro Omiya

    (PST Inc., Yokohama 231-0023, Japan)

  • Masakazu Higuchi

    (Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan)

  • Naoki Hagiwara

    (AGI Inc., Tokyo 113-8655, Japan)

  • Shunji Mitsuyoshi

    (Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan)

  • Hiroyuki Toda

    (Department of Psychiatry, National Defense Medical College, Tokorozawa 359-8513, Japan)

  • Taku Saito

    (Department of Psychiatry, National Defense Medical College, Tokorozawa 359-8513, Japan)

  • Masaaki Tanichi

    (Department of Psychiatry, National Defense Medical College, Tokorozawa 359-8513, Japan)

  • Aihide Yoshino

    (Department of Psychiatry, National Defense Medical College, Tokorozawa 359-8513, Japan)

  • Shinichi Tokuno

    (Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan)

Abstract

Background: In many developed countries, mood disorders have become problematic, and the economic loss due to treatment costs and interference with work is immeasurable. Therefore, a simple technique to determine individuals’ depressive state and stress level is desired. Methods: We developed a method to assess specific the psychological issues of individuals with major depressive disorders using emotional components contained in their voice. We propose two indices: vitality, a short-term index, and mental activity, a long-term index capturing trends in vitality. To evaluate our method, we used the voices of healthy individuals ( n = 14) and patients with major depression ( n = 30). The patients were also assessed by specialists using the Hamilton Rating Scale for Depression (HAM-D). Results: A significant negative correlation existed between the vitality extracted from the voices and HAM-D scores (r = −0.33, p < 0.05). Furthermore, we could discriminate the voice data of healthy individuals and patients with depression with a high accuracy using the vitality indicator ( p = 0.0085, area under the curve of the receiver operating characteristic curve = 0.76).

Suggested Citation

  • Shuji Shinohara & Mitsuteru Nakamura & Yasuhiro Omiya & Masakazu Higuchi & Naoki Hagiwara & Shunji Mitsuyoshi & Hiroyuki Toda & Taku Saito & Masaaki Tanichi & Aihide Yoshino & Shinichi Tokuno, 2021. "Depressive Mood Assessment Method Based on Emotion Level Derived from Voice: Comparison of Voice Features of Individuals with Major Depressive Disorders and Healthy Controls," IJERPH, MDPI, vol. 18(10), pages 1-12, May.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:10:p:5435-:d:557882
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    Citations

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    Cited by:

    1. Masakazu Higuchi & Mitsuteru Nakamura & Shuji Shinohara & Yasuhiro Omiya & Takeshi Takano & Daisuke Mizuguchi & Noriaki Sonota & Hiroyuki Toda & Taku Saito & Mirai So & Eiji Takayama & Hiroo Terashi &, 2022. "Detection of Major Depressive Disorder Based on a Combination of Voice Features: An Exploratory Approach," IJERPH, MDPI, vol. 19(18), pages 1-13, September.
    2. Takayuki Maruyama & Daisuke Ekuni & Masakazu Higuchi & Eiji Takayama & Shinichi Tokuno & Manabu Morita, 2022. "Relationship between Psychological Stress Determined by Voice Analysis and Periodontal Status: A Cohort Study," IJERPH, MDPI, vol. 19(15), pages 1-8, August.
    3. Yasuhiro Omiya & Daisuke Mizuguchi & Shinichi Tokuno, 2023. "Distinguish the Severity of Illness Associated with Novel Coronavirus (COVID-19) Infection via Sustained Vowel Speech Features," IJERPH, MDPI, vol. 20(4), pages 1-13, February.

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