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. 2021 May 19;18(10):5435.
doi: 10.3390/ijerph18105435.

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

Shuji Shinohara  1 , Mitsuteru Nakamura  1 , Yasuhiro Omiya  2 , Masakazu Higuchi  1 , Naoki Hagiwara  3 , Shunji Mitsuyoshi  1 , Hiroyuki Toda  4 , Taku Saito  4 , Masaaki Tanichi  4 , Aihide Yoshino  4 , Shinichi Tokuno  1
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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

Shuji Shinohara et al. Int J Environ Res Public Health. .

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).

Keywords: emotion analysis; mental activity; mood disorder assessment; noninvasiveness; vitality; voice index.

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Conflict of interest statement

M.H., M.N. and S.T. received financial support from PST Inc. until 2019 and currently report no financial support from the company. All other authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Scatter plot of relaxation and vivacity. Data are plotted for each voice acquisition. There are 50 data for the 13 people in the healthy group and 58 for the 9 people in the patient group. The straight line separates the healthy group from the patient group (0.60X + 0.40Y = 0.52).
Figure 2
Figure 2
Scatter plot of mean vitality and the mean standard deviation of vitality for each participant (N = 22).
Figure 3
Figure 3
Relationship between Hamilton Rating Scale for Depression (HAM-D) score and vitality in the data of patient group for algorithm verification. The figure also shows the regression line for the data (y = −0.0041x + 0.5361).
Figure 4
Figure 4
Comparison of vitality for each group. Error bars represent standard error. ** p < 0.01, n.s.: not significant. HAM-D: Hamilton Rating Scale for Depression.
Figure 5
Figure 5
Receiver operating characteristic curves when using vitality to identify groups. The straight line represents y = x.
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