Automated classification of stress and relaxation responses in major depressive disorder, panic disorder, and healthy participants via heart rate variability.

Journal: Frontiers in psychiatry
Published Date: Jan 9, 2025

Abstract

BACKGROUND: Stress is a significant risk factor for psychiatric disorders such as major depressive disorder (MDD) and panic disorder (PD). This highlights the need for advanced stress-monitoring technologies to improve treatment. Stress affects the autonomic nervous system, which can be evaluated via heart rate variability (HRV). While machine learning has enabled automated stress detection via HRV in healthy individuals, its application in psychiatric patients remains underexplored. This study evaluated the feasibility of using machine-learning algorithms to detect stress automatically in MDD and PD patients, as well as healthy controls (HCs), based on HRV features.

Authors

  • Sangwon Byun
    Department of Electronics Engineering, Incheon National University, Incheon, Republic of Korea.
  • Ah Young Kim
    Medical Information Research Section, Electronics and Telecommunications Research Institute, Dajeon, Republic of Korea.
  • Min-Sup Shin
    Department of Psychology, Korea University, Seoul, Republic of Korea.
  • Hong Jin Jeon
    Department of Psychiatry, Depression Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Chul-Hyun Cho
    Department of Biomedical Informatics, Korea University College of Medicine, Seoul, Republic of Korea.

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