Diagnosis of Depressive Disorder Model on Facial Expression Based on Fast R-CNN

59Citations
Citations of this article
98Readers
Mendeley users who have this article in their library.

Abstract

This study examines related literature to propose a model based on artificial intelligence (AI), that can assist in the diagnosis of depressive disorder. Depressive disorder can be diagnosed through a self-report questionnaire, but it is necessary to check the mood and confirm the consistency of subjective and objective descriptions. Smartphone-based assistance in diagnosing depressive disorders can quickly lead to their identification and provide data for intervention provision. Through fast region-based convolutional neural networks (R-CNN), a deep learning method that recognizes vector-based information, a model to assist in the diagnosis of depressive disorder can be devised by checking the position change of the eyes and lips, and guessing emotions based on accumulated photos of the participants who will repeatedly participate in the diagnosis of depressive disorder.

Cite

CITATION STYLE

APA

Lee, Y. S., & Park, W. H. (2022). Diagnosis of Depressive Disorder Model on Facial Expression Based on Fast R-CNN. Diagnostics, 12(2). https://doi.org/10.3390/diagnostics12020317

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free