Stress recognition identifying relevant facial action units through explainable artificial intelligence and machine learning.

Journal: Computer methods and programs in biomedicine
PMID: 39608217

Abstract

BACKGROUND AND OBJECTIVE: Facial cues and expressions constitute a component of bodily responses that provide useful information about one's stress levels. According to the Facial Action Coding System, they can be modelled consistently in terms of fundamental facial muscle movements, called facial Action Units (AUs). This article investigates automatic acute stress recognition based on AUs using conventional Machine and Deep Learning techniques.

Authors

  • Giorgos Giannakakis
  • Anastasios Roussos
    Institute of Computer Science, Foundation for Research and Technology Hellas (FORTH), N. Plastira 100, Heraklion, 70013, Crete, Greece; College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK.
  • Christina Andreou
    Department of Psychiatry and Psychotherapy, University Hospital Lübeck (UKSH), Ratzeburger Allee 160, 23538 Lübeck, Germany.
  • Stefan Borgwardt
    Department of Psychiatry, University of Basel, Basel, Switzerland.
  • Alexandra I Korda
    Department of Psychiatry and Psychotherapy, University Hospital Lübeck (UKSH), Ratzeburger Allee 160, 23538 Lübeck, Germany.

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