Face Recognition Technology in the Field of Intelligent Psychological Analysis

DOI

10.2991/978-94-6463-986-5_61How to use a DOI?

Keywords

Face recognition technology; Convolutional neural network (CNN); Recurrent neural network (RNN); Long short-term memory (LSTM); 3D CNN

Abstract

With the development of artificial intelligence technology, facial emotion recognition is being used in more fields. Nowadays, mental health issues of people of all ages have already become hot issues. Researchers have found that intelligent psychological analysis has a significant impact on improving mental health levels. However, there is still a lack of a unified understanding of how to use facial recognition technology to reasonably and accurately identify patients’ emotions, enabling a deeper psychological analysis. Minute changes in a person’s facial expressions are often challenging to detect without the aid of specialised equipment. This can sometimes lead therapists to misinterpret crucial information, particularly when working with patients who habitually conceal their emotions. Consequently, the benefits of applying modern deep learning technology for such assessments become especially evident. Drawing from research and scholarship across multiple disciplines, this review integrates deep learning models into the field of psychological analysis. By using deep learning models to capture patients’ micro-expressions and accurately identify sentiment, it reduces errors caused by human judgment, provides therapists with accurate sentiment data, helps therapists better understand the development of patients’ emotions, and proposes personalised treatment plans based on the patients’ own situations, pointing the direction for the future Fusion development of psychotherapy and artificial intelligence.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Yufei Zang
AU  - Zixi Zhu
PY  - 2026
DA  - 2026/02/18
TI  - Face Recognition Technology in the Field of Intelligent Psychological Analysis
BT  - Proceedings of the 2025 International Conference on Electronics, Electrical and Grid Technology (ICEEGT 2025)
PB  - Atlantis Press
SP  - 596
EP  - 604
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-986-5_61
DO  - 10.2991/978-94-6463-986-5_61
ID  - Zang2026
ER  -