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

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.

Methods

The study included 147 participants (MDD: 41, PD: 47, HC: 59) who visited the laboratory up to five ti

SUBMITTER: Byun S 

PROVIDER: S-EPMC11754969 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature