@inproceedings{5ed6059a47fc445f9ddbbf2405291346,
title = "Feasibility Study for Estimation of Depression Severity using Voice Analysis",
abstract = "Voice analysis is suitable for screening large populations and daily monitoring of illnesses because of its advantages of cost and usability. We examined the feasibility of estimating the severity of major depressive disorder (MDD) using voice analysis. We developed an estimator for the Hamilton depression rating scale (HAM-D), which is the gold-standard of evaluation for MDD, by iteration of multiple regressions. As a result, the estimation index had a high correlation (0.832) with the HAM-D score. The results thus demonstrated the feasibility of voice-based screening and monitoring of MDD.",
keywords = "Bipolar disorder, Hamilton Depression Rating Scale, Major depression, Voice analysis of pathophysiology",
author = "Mitsuteru Nakamura and Shuji Shinohara and Yasuhiro Omiya and Masakazu Higuchi and Shunji Mitsuyoshi and Takeshi Takano and Hiroyuki Toda and Taku Saito and Masaaki Tanichi and Aihide Yoshino and Shinichi Tokuno",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 ; Conference date: 03-12-2018 Through 06-12-2018",
year = "2019",
month = jan,
day = "21",
doi = "10.1109/BIBM.2018.8621490",
language = "English (US)",
series = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2792--2794",
editor = "Harald Schmidt and David Griol and Haiying Wang and Jan Baumbach and Huiru Zheng and Zoraida Callejas and Xiaohua Hu and Julie Dickerson and Le Zhang",
booktitle = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",
address = "United States",
}