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

This study demonstrated that differentiating between stress and relaxation was more challenging in the PD and MDD groups than in the HC group, underscoring the potential of HRV metrics as stress biomarkers. Psychiatric patients exhibited altered autonomic responses, which may influence their stress reactivity. This indicates the need for a tailored approach to stress monitoring in these patient groups. Additionally, we emphasized the significance of longitudinal scaling in enhancing classification accuracy, which can be utilized to develop personalized monitoring technologies for psychiatric patients.

Authors

Institutions

Publication Details

Journal
Frontiers in Psychiatry
Published
2025-01-09
DOI
https://doi.org/10.3389/fpsyt.2024.1500310
Citations
2
Primary Topic
Heart Rate Variability and Autonomic Control
Type
article
Field-Weighted Citation Impact
2.78

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Ah Young Kim, Sangwon Byun, Chul‐Hyun Cho, Min‐Sup Shin et al.
2 citations
Frontiers in Psychiatry
Heart Rate Variability and Autonomic Control
2.78
article

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

Ah Young Kim, Sangwon Byun, Chul‐Hyun Cho, Min‐Sup Shin, Hong Jin Jeon
article en
2 citations

Abstract

This study demonstrated that differentiating between stress and relaxation was more challenging in the PD and MDD groups than in the HC group, underscoring the potential of HRV metrics as stress biomarkers. Psychiatric patients exhibited altered autonomic responses, which may influence their stress reactivity. This indicates the need for a tailored approach to stress monitoring in these patient groups. Additionally, we emphasized the significance of longitudinal scaling in enhancing classification accuracy, which can be utilized to develop personalized monitoring technologies for psychiatric patients.

Frontiers in PsychiatryVol. 15
Electronics and Telecommunications Research Institute (KR), Incheon National University (KR), Korea University (KR), Samsung Medical Center (KR), Sungkyunkwan University (KR)
Incheon National University, Ministry of Science and ICT, South Korea, Institute for Information and Communications Technology Promotion
Good health and well-being
Openalex Percentile: Top 12%
Heart Rate Variability and Autonomic Control
2.78
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Automated classification of stress and relaxation responses in major depressive disorder, panic disorder, and healthy participants via heart rate variability — Ah Young Kim, Sangwon Byun, et al. · Frontiers in Psychiatry (2025) | TGRS Research Map | TGRS