Feasibility Study for Estimation of Depression Severity using Voice Analysis

Mitsuteru Nakamura; Shuji Shinohara; Yasuhiro Omiya; Masakazu Higuchi; Shunji Mitsuyoshi; Takeshi Takano; Hiroyuki Toda; Taku Saito; Masaaki Tanichi; Aihide Yoshino; Shinichi Tokuno

doi:10.1109/BIBM.2018.8621490

Feasibility Study for Estimation of Depression Severity using Voice Analysis

Mitsuteru Nakamura, Shuji Shinohara, Yasuhiro Omiya, Masakazu Higuchi, Shunji Mitsuyoshi, Takeshi Takano, Hiroyuki Toda, Taku Saito, Masaaki Tanichi, Aihide Yoshino, Shinichi Tokuno

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

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.

Original language	English (US)
Title of host publication	Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
Editors	Harald Schmidt, David Griol, Haiying Wang, Jan Baumbach, Huiru Zheng, Zoraida Callejas, Xiaohua Hu, Julie Dickerson, Le Zhang
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2792-2794
Number of pages	3
ISBN (Electronic)	9781538654880
DOIs	https://doi.org/10.1109/BIBM.2018.8621490
State	Published - Jan 21 2019
Externally published	Yes
Event	2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 - Madrid, Spain Duration: Dec 3 2018 → Dec 6 2018

Publication series

Name	Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

Conference

Conference	2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
Country/Territory	Spain
City	Madrid
Period	12/3/18 → 12/6/18

Keywords

Bipolar disorder
Hamilton Depression Rating Scale
Major depression
Voice analysis of pathophysiology

ASJC Scopus subject areas

Biomedical Engineering
Health Informatics

Access to Document

10.1109/BIBM.2018.8621490

Cite this

Nakamura, M., Shinohara, S., Omiya, Y., Higuchi, M., Mitsuyoshi, S., Takano, T., Toda, H., Saito, T., Tanichi, M., Yoshino, A., & Tokuno, S. (2019). Feasibility Study for Estimation of Depression Severity using Voice Analysis. In H. Schmidt, D. Griol, H. Wang, J. Baumbach, H. Zheng, Z. Callejas, X. Hu, J. Dickerson, & L. Zhang (Eds.), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 (pp. 2792-2794). [8621490] (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2018.8621490

Feasibility Study for Estimation of Depression Severity using Voice Analysis. / Nakamura, Mitsuteru; Shinohara, Shuji; Omiya, Yasuhiro et al.

Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. ed. / Harald Schmidt; David Griol; Haiying Wang; Jan Baumbach; Huiru Zheng; Zoraida Callejas; Xiaohua Hu; Julie Dickerson; Le Zhang. Institute of Electrical and Electronics Engineers Inc., 2019. p. 2792-2794 8621490 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Nakamura, M, Shinohara, S, Omiya, Y, Higuchi, M, Mitsuyoshi, S, Takano, T, Toda, H, Saito, T, Tanichi, M, Yoshino, A & Tokuno, S 2019, Feasibility Study for Estimation of Depression Severity using Voice Analysis. in H Schmidt, D Griol, H Wang, J Baumbach, H Zheng, Z Callejas, X Hu, J Dickerson & L Zhang (eds), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018., 8621490, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018, Institute of Electrical and Electronics Engineers Inc., pp. 2792-2794, 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018, Madrid, Spain, 12/3/18. https://doi.org/10.1109/BIBM.2018.8621490

Nakamura M, Shinohara S, Omiya Y, Higuchi M, Mitsuyoshi S, Takano T et al. Feasibility Study for Estimation of Depression Severity using Voice Analysis. In Schmidt H, Griol D, Wang H, Baumbach J, Zheng H, Callejas Z, Hu X, Dickerson J, Zhang L, editors, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 2792-2794. 8621490. (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018). doi: 10.1109/BIBM.2018.8621490

Nakamura, Mitsuteru ; Shinohara, Shuji ; Omiya, Yasuhiro et al. / Feasibility Study for Estimation of Depression Severity using Voice Analysis. Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. editor / Harald Schmidt ; David Griol ; Haiying Wang ; Jan Baumbach ; Huiru Zheng ; Zoraida Callejas ; Xiaohua Hu ; Julie Dickerson ; Le Zhang. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 2792-2794 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

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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.",

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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",

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AU - Nakamura, Mitsuteru

AU - Shinohara, Shuji

AU - Omiya, Yasuhiro

AU - Higuchi, Masakazu

AU - Mitsuyoshi, Shunji

AU - Takano, Takeshi

AU - Toda, Hiroyuki

AU - Saito, Taku

AU - Tanichi, Masaaki

AU - Yoshino, Aihide

AU - Tokuno, Shinichi

PY - 2019/1/21

Y1 - 2019/1/21

N2 - 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.

AB - 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.

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KW - Hamilton Depression Rating Scale

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KW - Voice analysis of pathophysiology

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Feasibility Study for Estimation of Depression Severity using Voice Analysis

Abstract

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Keywords

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