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 Mitsuteru NakamuraYasuhiro OmiyaMasakazu HiguchiNaoki HagiwaraShunji MitsuyoshiHiroyuki TodaTaku SaitoMasaaki TanichiAihide YoshinoShinichi Tokuno

Published in: International journal of environmental research and public health (2021)

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).

Keyphrases

bipolar disorder
depressive symptoms
sleep quality
stress induced
autism spectrum disorder
electronic health record
machine learning
data analysis
deep learning
borderline personality disorder