The future of automated capture of social kinesic signals for psychiatric purposes

Judee K. Burgoon, Aaron C. Elkins, Douglas Derrick, Bradley Walls, Dimitris Metaxas

Research output: Contribution to journalShort surveypeer-review


This article considers how computer vision can be enlisted for biomedical applications, specifically the measurement, data analytics and treatment of psychiatric disorders. Often, youngsters are too afraid or embarrassed to disclose their emotional and mental problems to human therapists. An AI system can be utilized not only to collect data in a non-threatening ongoing manner and record patient's temporal psychophysiological state but also to analyze and output the periodic results, it may be an efficient and effective means for therapists to plan treatments. We report on various tools for analyzing social kinesic signals for emotional and physiological states. Only one, AVATAR (and its predecessor SPECIES), both records a patient's state and also outputs an analysis that flags problem areas for therapists. In this way, automated tools can augment human observation and judgment.

Original languageEnglish (US)
Article number1168712
JournalFrontiers in Computer Science
StatePublished - 2023


  • automated visual capture
  • computer vision
  • kinesics
  • psychiatric disorders
  • social signals

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Science Applications


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