Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.3
3.4
Journals
Sensors
Special Issues
Sensing Technologies Applied in Human Emotion and Facial Expression Recognition
sensors-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Sensors Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Sensing Technologies Applied in Human Emotion and Facial Expression Recognition

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 25 November 2025 | Viewed by 621

Special Issue Editors

Dr. Tong Chen

E-Mail Website
Guest Editor
College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China
Interests: signal processing & image processing; affective computing; biomedical engineering
Prof. Dr. Hongying Meng

E-Mail Website
Guest Editor
Electronic and Electrical Engineering, Brunel University London, Uxbridge UB8 3PH, UK
Interests: image processing; artificial intelligence; signal processing; affective computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, we have witnessed significant advancements in sensing technologies for human emotions, which primarily rely on analyzing facial expressions, voice, body language, and physiological signals to accurately recognize and understand human emotional states. These technologies will provide more intelligent and personalized solutions for fields such as human–computer interaction, healthcare, education, customer service, etc.

This Special Issue aims to collate original research and review articles focusing on recent progress, technologies, approaches, applications, and new obstacles in the field of human emotion and facial expression recognition.

Dr. Tong Chen
Prof. Dr. Hongying Meng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • emotion recognition and understanding
  • intent recognition
  • facial expression recognition
  • micro-expression recognition
  • masked facial expression recognition
  • stress recognition
  • physiological signal
  • multi-modal signals
  • wearable sensors
  • imaging sensors
  • non-contact sensing for physiological signal measurement
  • non-contact sensing for emotion recognition

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

22 pages, 23958 KiB  
Article
A Lightweight Dual-Stream Network with an Adaptive Strategy for Efficient Micro-Expression Recognition
by Xinyu Liu, Ju Zhou, Feng Chen, Shigang Li, Hanpu Wang, Yingjuan Jia and Yuhao Shan
Sensors 2025, 25(9), 2866; https://doi.org/10.3390/s25092866 - 1 May 2025
Viewed by 207
Abstract
Micro-expressions (MEs), characterized by their brief duration and subtle facial muscle movements, pose significant challenges for accurate recognition. These ultra-fast signals, typically captured by high-speed vision sensors, require specialized computational methods to extract spatio-temporal features effectively. In this study, we propose a lightweight [...] Read more.
Micro-expressions (MEs), characterized by their brief duration and subtle facial muscle movements, pose significant challenges for accurate recognition. These ultra-fast signals, typically captured by high-speed vision sensors, require specialized computational methods to extract spatio-temporal features effectively. In this study, we propose a lightweight dual-stream network with an adaptive strategy for efficient ME recognition. Firstly, a motion magnification network based on transfer learning is employed to magnify the motion states of facial muscles in MEs. This process can generate additional samples, thereby expanding the training set. To effectively capture the dynamic changes of facial muscles, dense optical flow is extracted from the onset frame and the magnified apex frame, thereby obtaining magnified dense optical flow (MDOF). Subsequently, we design a dual-stream spatio-temporal network (DSTNet), using the magnified apex frame and MDOF as inputs for the spatial and temporal streams, respectively. An adaptive strategy that dynamically adjusts the magnification factor based on the top-1 confidence is introduced to enhance the robustness of DSTNet. Experimental results show that our proposed method outperforms existing methods in terms of F1-score on the SMIC, CASME II, SAMM, and composite dataset, as well as in cross-dataset tasks. Adaptive DSTNet significantly enhances the handling of sample imbalance while demonstrating robustness and featuring a lightweight design, indicating strong potential for future edge sensor deployment. Full article
(This article belongs to the Special Issue Sensing Technologies Applied in Human Emotion and Facial Expression Recognition)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop