Computerized analysis of facial expression reveals objective indices of blunted facial affect.

Journal: European archives of psychiatry and clinical neuroscience
PMID: 37878034

Abstract

Blunted affect is associated with severe mental illness, particularly schizophrenia. Mechanisms of blunted affect are poorly understood, potentially due to a lack of phenomenological clarity. Here, we examine clinician rated blunted affect and computerized facial metrics derived from ambulatory video assessment using machine learning. With high predictive accuracy (80-82%), we found that head orientation, eye movement, and facets of mouth movement were associated with clinical ratings of blunted affect. Features denoting larger muscle movements were associated with social cognition (R = 0.37) and cognition (R = 0.40). Findings provide potential insights on psychological and pathophysiological contributors to blunted affect.

Authors

  • Tovah Cowan
    Department of Psychology, Louisiana State University.
  • Zachary B Rodriguez
    Department of Psychology, Center for Computation and Technology, Louisiana State University, 236 Audubon Hall, Baton Rouge, LA, 70803, USA.
  • Gregory P Strauss
    Department of Psychology, University of Georgia, Athens, GA, USA.
  • Ian M Raugh
    Department of Psychology, University of Georgia, Athens, GA, USA.
  • Alex S Cohen
    Department of Psychology, Louisiana State University.

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