Abstract
Objective: In this study, we propose a voice index to identify healthy individuals, patients with bipolar disorder, and patients with major depressive disorder using polytomous logistic regression analysis. Methods: Voice features were extracted from voices of healthy individuals and patients with mental disease. Polytomous logistic regression analysis was performed for some voice features. Results: With the prediction model obtained using the analysis, we identified subject groups and were able to classify subjects into three groups with 90.79% accuracy. Conclusion: These results show that the proposed index may be used as a new evaluation index to identify depression.
Original language | English (US) |
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Pages (from-to) | 89-93 |
Number of pages | 5 |
Journal | Asian Journal of Pharmaceutical and Clinical Research |
Volume | 11 |
Issue number | Special Issue 3 |
DOIs | |
State | Published - 2018 |
Externally published | Yes |
Keywords
- Bipolar disorder
- Major depressive disorder
- Polytomous logistic regression analysis
- Voice
ASJC Scopus subject areas
- Pharmacology
- Pharmaceutical Science
- Pharmacology (medical)