CogSci 2025

August 01, 2025

San Francisco, United States

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keywords:

emotion disorder

computer science

psychology

emotion

Psychomotor changes, while crucial indicators of depres- sion, remain underrepresented in clinical observations. We examined the relationship between depression and psychomotor behavior by analyzing head-tracking data related to yaw movements made during exploration of 360° emotional videos, alongside valence and arousal ratings on 9-point Likert scale. Symptoms of depres- sion were recorded using the Patient Health Question- naire (PHQ-9). While subjective ratings for valence and arousal showed no differences across depression groups, the head-tracking data revealed novel results. Individu- als with moderate to severe depression exhibited signif- icantly lower scanning speed and standard deviation in yaw movement compared to minimal to mild depression. Although preliminary, these results underscore the im- portance of psychomotor measures in diagnosis, risk as- sessment, and monitoring in psychiatric care, alongside subjective evaluations.

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