The voice of depression: speech features as biomarkers for major depressive disorder.

Journal: BMC psychiatry
PMID: 39533239

Abstract

BACKGROUND: Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessments are based on subjective evaluations. Automated speech analysis shows promise in detecting symptom severity in depressed patients. This project aimed to identify discriminating speech features between patients with major depressive disorder (MDD) and healthy controls (HCs) by examining associations with symptom severity measures.

Authors

  • Felix Menne
    ki:elements GmbH, Bleichstr. 27, 66111, Saarbrücken, Germany. felix.menne@ki-elements.de.
  • Felix Dörr
    ki:elements GmbH, Bleichstr. 27, 66111, Saarbrücken, Germany.
  • Julia Schräder
    Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany.
  • Johannes Tröger
    ki:elements GmbH, Bleichstr. 27, 66111, Saarbrücken, Germany.
  • Ute Habel
    Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Pauwelsstraße 30, 52074, Aachen, Germany. uhabel@ukaachen.de.
  • Alexandra König
    ki:elements GmbH, Bleichstr. 27, 66111, Saarbrücken, Germany.
  • Lisa Wagels
    Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany.

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