Automatic assessment of depression based on visual cues: A systematic review

A Pampouchidou, PG Simos, K Marias… - IEEE Transactions …, 2017 - ieeexplore.ieee.org
Automatic depression assessment based on visual cues is a rapidly growing research
domain. The present exhaustive review of existing approaches as reported in over sixty …

Automatic depression recognition by intelligent speech signal processing: A systematic survey

P Wu, R Wang, H Lin, F Zhang, J Tu… - CAAI Transactions on …, 2023 - Wiley Online Library
Depression has become one of the most common mental illnesses in the world. For better
prediction and diagnosis, methods of automatic depression recognition based on speech …

[PDF][PDF] Detecting Depression with Audio/Text Sequence Modeling of Interviews.

T Al Hanai, MM Ghassemi, JR Glass - Interspeech, 2018 - isca-archive.org
Medical professionals diagnose depression by interpreting the responses of individuals to a
variety of questions, probing lifestyle changes and ongoing thoughts. Like professionals, an …

[HTML][HTML] Automated depression analysis using convolutional neural networks from speech

L He, C Cao - Journal of biomedical informatics, 2018 - Elsevier
To help clinicians to efficiently diagnose the severity of a person's depression, the affective
computing community and the artificial intelligence field have shown a growing interest in …

Audio based depression detection using Convolutional Autoencoder

S Sardari, B Nakisa, MN Rastgoo, P Eklund - Expert Systems with …, 2022 - Elsevier
Depression is a serious and common psychological disorder that requires early diagnosis
and treatment. In severe episodes the condition may result in suicidal thoughts. Recently …

Multimodal measurement of depression using deep learning models

L Yang, D Jiang, X Xia, E Pei, MC Oveneke… - Proceedings of the 7th …, 2017 - dl.acm.org
This paper addresses multi-modal depression analysis. We propose a multi-modal fusion
framework composed of deep convolutional neural network (DCNN) and deep neural …

Spectral representation of behaviour primitives for depression analysis

S Song, S Jaiswal, L Shen… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Depression is a serious mental disorder affecting millions of people all over the world.
Traditional clinical diagnosis methods are subjective, complicated and require extensive …

Topic modeling based multi-modal depression detection

Y Gong, C Poellabauer - Proceedings of the 7th annual workshop on …, 2017 - dl.acm.org
Major depressive disorder is a common mental disorder that affects almost 7% of the adult
US population. The 2017 Audio/Visual Emotion Challenge (AVEC) asks participants to build …

Human behaviour-based automatic depression analysis using hand-crafted statistics and deep learned spectral features

S Song, L Shen, M Valstar - 2018 13th IEEE International …, 2018 - ieeexplore.ieee.org
Depression is a serious mental disorder that affects millions of people all over the world.
Traditional clinical diagnosis methods are subjective, complicated and need extensive …

[HTML][HTML] Deep neural networks for depression recognition based on 2d and 3d facial expressions under emotional stimulus tasks

W Guo, H Yang, Z Liu, Y Xu, B Hu - Frontiers in neuroscience, 2021 - frontiersin.org
The proportion of individuals with depression has rapidly increased along with the growth of
the global population. Depression has been the currently most prevalent mental health …