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Taku Saito

Biographic Data

ID7429135
NAMETaku Saito
GIVEN NAMESTaku
FAMILY NAMESaito
SIGNATURESAITO T
AFFILIATIONSNational Defense Medical College
ORCID0000-0001-9547-6674
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
AUTHOR COUNT3
EDITOR COUNT0
FIRST PUBLICATION YEAR2021
LATEST PUBLICATION YEAR2023
H-INDEX0
  • Estimating Depressive Symptom Class from Voice

    Open Access•Takeshi Takano, Daisuke Mizuguchi et al.•ARTICLE•International Journal of…•2023

    Voice-based depression detection methods have been studied worldwide as an objective and easy method to detect depression. Conventional studies estimate the presence or severity of depression. However, an estimation of symptoms is a necessary technique not only to treat depression, but also to relieve patients' distress. Hence, we studied a method for clustering symptoms from HAM-D scores of depressed patients and by estimating patients in differ…

  • Detection of Major Depressive Disorder Based on a Combination of Voice Features: An Exploratory Approach

    Open Access•Masakazu Higuchi, Mitsuteru Nakamura et al.•ARTICLE•International Journal of…•2022

    In general, it is common knowledge that people's feelings are reflected in their voice and facial expressions. This research work focuses on developing techniques for diagnosing depression based on acoustic properties of the voice. In this study, we developed a composite index of vocal acoustic properties that can be used for depression detection. Voice recordings were collected from patients undergoing outpatient treatment for major depressive d…

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

    Open Access•Shuji Shinohara, Mitsuteru Nakamura et al.•ARTICLE•International Journal of…•2021

    A significant negative correlation existed between the vitality extracted from the voices and HAM-D scores (r = -0.33, p p = 0.0085, area under the curve of the receiver operating characteristic curve = 0.76)

No prominent works on this page.

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

    Open Access•Shuji Shinohara, Mitsuteru Nakamura et al.•ARTICLE•International Journal of…•2021

    A significant negative correlation existed between the vitality extracted from the voices and HAM-D scores (r = -0.33, p p = 0.0085, area under the curve of the receiver operating characteristic curve = 0.76)

  • Detection of Major Depressive Disorder Based on a Combination of Voice Features: An Exploratory Approach

    Open Access•Masakazu Higuchi, Mitsuteru Nakamura et al.•ARTICLE•International Journal of…•2022

    In general, it is common knowledge that people's feelings are reflected in their voice and facial expressions. This research work focuses on developing techniques for diagnosing depression based on acoustic properties of the voice. In this study, we developed a composite index of vocal acoustic properties that can be used for depression detection. Voice recordings were collected from patients undergoing outpatient treatment for major depressive d…

  • Estimating Depressive Symptom Class from Voice

    Open Access•Takeshi Takano, Daisuke Mizuguchi et al.•ARTICLE•International Journal of…•2023

    Voice-based depression detection methods have been studied worldwide as an objective and easy method to detect depression. Conventional studies estimate the presence or severity of depression. However, an estimation of symptoms is a necessary technique not only to treat depression, but also to relieve patients' distress. Hence, we studied a method for clustering symptoms from HAM-D scores of depressed patients and by estimating patients in differ…

Emotion and Mood Recognition (3 works) · Mental Health Research Topics (3 works) · Psychiatry (3 works) · Psychology (3 works) · Anxiety (2 works) · Audiology (2 works) · Clinical Psychology (2 works) · Clinical Psychology (2 works) · Depression (economics (2 works) · Depressive symptoms (2 works)

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