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  3. Facial Expression Recognition For Emotion Perception: A Comprehensive Science Mapping.
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Related Experiment Video

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
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Facial expression recognition for emotion perception: A comprehensive science mapping.

Hou-Ming Kan1, Li-Ping Chen2, Yu Zhang1

  • 1Faculty of Medicine Macau University of Science and Technology Macau SAR China.

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|April 23, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Facial expression recognition (FER) research maps technological evolution and future trends. This interdisciplinary field, bridging computer science and medicine, shows potential in disease identification and emotion analysis.

Keywords:
artificial intelligencebibliometric analysisemotion perceptionfacial expression recognitionscience mapping

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Area of Science:

  • Interdisciplinary research at the intersection of computer science, psychology, neuroscience, and medicine.

Background:

  • Facial expression recognition (FER) is a pivotal research domain.
  • Mapping the FER scientific knowledge graph explores technological evolution and future trends.

Purpose of the Study:

  • To explore the technological evolution and forecast future trends in facial expression recognition (FER).

Main Methods:

  • Collected and cleaned research from the Web of Science (WoS) database.
  • Utilized CiteSpace and R (BiblioShiny) for scientific knowledge mapping.
  • Applied K-means clustering, Latent Dirichlet Allocation (LDA), and Uniform Manifold Approximation and Projection (UMAP) for analysis.

Main Results:

  • Research is concentrated in North America, Western Europe, East Asia, India, and Australia.
  • Primary research focus areas include neuroscience, psychiatry, and psychology.
  • Artificial intelligence (AI) has shifted FER from manual to machine learning-based feature extraction, enhancing accuracy and speed.

    • Conclusions:

    • FER demonstrates strong potential in identifying rare and neurological diseases.
    • The interdisciplinary nature of FER is increasingly important with advancements in computer technology.
    • FER shows promising applications in neuroscience, emotion analysis, and pain assessment.