This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2491) mHealth for Screening (221) Depression and Mood Disorders; Suicide Prevention (1392) Diagnostic Tools in Mental Health (248) Innovations in Mental Health Systems (398)

Published on in Vol 4, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16455, first published .
Effectiveness of a Voice-Based Mental Health Evaluation System for Mobile Devices: Prospective Study

Effectiveness of a Voice-Based Mental Health Evaluation System for Mobile Devices: Prospective Study

Effectiveness of a Voice-Based Mental Health Evaluation System for Mobile Devices: Prospective Study

Authors of this article:

Masakazu Higuchi1 Author Orcid Image ;   Mitsuteru Nakamura2 Author Orcid Image ;   Shuji Shinohara1 Author Orcid Image ;   Yasuhiro Omiya3 Author Orcid Image ;   Takeshi Takano3 Author Orcid Image ;   Shunji Mitsuyoshi1 Author Orcid Image ;   Shinichi Tokuno1 Author Orcid Image
Article Authors Cited by (15) Tweetations (4) Metrics

Journals

  1. Shinohara S, Nakamura M, Omiya Y, Higuchi M, Hagiwara N, Mitsuyoshi S, Toda H, Saito T, Tanichi M, Yoshino A, Tokuno S. Depressive Mood Assessment Method Based on Emotion Level Derived from Voice: Comparison of Voice Features of Individuals with Major Depressive Disorders and Healthy Controls. International Journal of Environmental Research and Public Health 2021;18(10):5435 View
  2. Higuchi M, Nakamura M, Shinohara S, Omiya Y, Takano T, Mizuguchi D, Sonota N, Toda H, Saito T, So M, Takayama E, Terashi H, Mitsuyoshi S, Tokuno S. Detection of Major Depressive Disorder Based on a Combination of Voice Features: An Exploratory Approach. International Journal of Environmental Research and Public Health 2022;19(18):11397 View
  3. Saito Y, Nakamura S, Tanaka A, Watanabe R, Narimatsu H, Chung U. Checking the validity and reliability of the Japanese version of the Mini-Cog using a smartphone application. BMC Research Notes 2022;15(1) View
  4. Saito Y, Nakamura S, Tanaka A, Watanabe R, Narimatsu H, Chung U. Evaluation of the validity and reliability of the 10-meter walk test using a smartphone application among Japanese older adults. Frontiers in Sports and Active Living 2022;4 View
  5. Higuchi M, Sonota N, Nakamura M, Miyazaki K, Shinohara S, Omiya Y, Takano T, Mitsuyoshi S, Tokuno S. Performance Evaluation of a Voice-Based Depression Assessment System Considering the Number and Type of Input Utterances. Sensors 2021;22(1):67 View
  6. Omiya Y, Mizuguchi D, Tokuno S. Distinguish the Severity of Illness Associated with Novel Coronavirus (COVID-19) Infection via Sustained Vowel Speech Features. International Journal of Environmental Research and Public Health 2023;20(4):3415 View
  7. Nakamura S, Watanabe R, Saito Y, Watanabe K, Chung U, Narimatsu H. The ME-BYO index: A development and validation project of a novel comprehensive health index. Frontiers in Public Health 2023;11 View
  8. Watase T, Omiya Y, Tokuno S. Severity Classification Using Dynamic Time Warping–Based Voice Biomarkers for Patients With COVID-19: Feasibility Cross-Sectional Study. JMIR Biomedical Engineering 2023;8:e50924 View
  9. Yang Z, Zhou S, Zhang L, Serikawa S. Optimizing Speech Emotion Recognition with Hilbert Curve and convolutional neural network. Cognitive Robotics 2024;4:30 View
  10. Shin J, Bae S. Use of voice features from smartphones for monitoring depressive disorders: Scoping review. DIGITAL HEALTH 2024;10 View
  11. Mohsen B, Al-Khaleel O, Alfadhly A. Mental Health Monitoring and Detection Based on Machine Learning and IoT Data. International Journal of Information Technology & Decision Making 2024;23(04):1449 View
  12. Kim D, Yi B, Won Y. Speech Emotion Recognition in People at High Risk of Dementia. Dementia and Neurocognitive Disorders 2024;23(3):146 View
  13. Vinh Phuc L, Nakamura M, Higuchi M, Tokuno S. Effectiveness of a voice analysis technique in the assessment of depression status of individuals from Ho Chi Minh City, Viet Nam: A cross-sectional study. Advances in Science, Technology and Engineering Systems Journal 2024;9(4):73 View