Application of facial expression recognition technology in diagnosis and treatment of psychiatry
10.3760/cma.j.cn371468-20201227-00084
- VernacularTitle:面部表情识别技术在精神疾病诊疗中的应用
- Author:
Bowen LIU
1
;
Jianwei SHUAI
;
Yuping CAO
Author Information
1. 中南大学湘雅二医院精神科，长沙 410000
- Keywords:
Facial expression recognition;
Deep learning;
Mental disorders;
Convolutional neural networks
- From:
Chinese Journal of Behavioral Medicine and Brain Science
2021;30(10):955-960
- CountryChina
- Language:Chinese
-
Abstract:
In psychiatry, observation of the patients is often an important basis for making a diagnosis during clinical practice. However, changes in emotional facial expressions are often subtle and difficult to detect. For this reason, automated facial expression recognition can be used to assist in identifying mental disorders. Facial expression is one of the important ways of emotional expression, and strong similarities of basic human facial expression are not affected by cultural background or congenital blindness. With the development of computer science, facial expression recognition methods are also constantly improving. Among them, deep-learning-based facial expression recognition approaches, with their powerful information processing capabilities, highly reduce the dependence on face-physics-based models and other pre-processing techniques by using trainable feature extraction models to automatically learn representations from images and videos. This article focuses on the progress of facial expression recognition system in the diagnosis and treatment of schizophrenia, depression, borderline personality disorder, autism spectrum disorder and other diseases. This article also explores the application of facial expression recognition technology in the field of psychiatry and remote psychology intervention.
