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This study explored using virtual avatars and facial monitoring to detect depression. Results showed distinct facial expression patterns in a virtual setting, aiding in differentiating individuals with or without depression symptoms.

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Area of Science:

  • Human-Computer Interaction
  • Psychology
  • Affective Computing

Background:

  • Depression significantly impacts quality of life, necessitating effective detection methods.
  • Human-machine interaction offers novel avenues for mental health assessment.
  • Virtual avatar communication systems combined with facial expression monitoring show potential for depression classification.

Purpose of the Study:

  • To assess the impact of human versus virtual avatar interviewers on individuals with depressive symptoms.
  • To clarify how neutral conversation topics influence facial expressions and emotions in those with depression.
  • To compare verbal and non-verbal cues between individuals with and without depression.

Main Methods:

  • Twenty-seven participants (15 control, 12 depression symptoms) interacted with virtual avatars and human interviewers.
  • Participants engaged in neutral and negative conversation topics, completing the PANAS scale.
  • Facial expressions were recorded via webcam and analyzed using manual annotation and automatic detection (OpenFace).

Main Results:

  • No significant differences in emotions were found between human and virtual avatar interviewers.
  • Neutral topics induced less negative emotion compared to negative topics for both groups.
  • Distinct facial expression patterns were observed between individuals with and without depression within the virtual avatar system.

Conclusions:

  • Virtual avatars and human interviewers did not significantly differ in emotional or facial expression outcomes.
  • Neutral conversation topics were associated with reduced negative emotions in both control and depression groups.
  • The virtual avatar communication system demonstrated potential for identifying differing facial expression patterns indicative of depression.