Detection and Analysis of Circadian Biomarkers for Metabolic Syndrome Using Wearable Data: Cross-Sectional Study

This study identified CCE and relative amplitude of heart rate as key circadian rhythm biomarkers for MetS monitoring, demonstrating their high importance across multiple XAI models. In contrast, traditional sleep markers showed limited significance, suggesting that circadian rhythm analysis may offer additional insights into MetS beyond sleep-related indicators. These findings highlight the potential of wearable-based circadian biomarkers for improving MetS assessment and management.

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Publication Details

Journal
JMIR Medical Informatics
Published
2025-05-15
DOI
https://doi.org/10.2196/69328
Citations
5
Primary Topic
Heart Rate Variability and Autonomic Control
Type
article
Field-Weighted Citation Impact
6.94
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article

Detection and Analysis of Circadian Biomarkers for Metabolic Syndrome Using Wearable Data: Cross-Sectional Study

Jeong-Kyun Kim, Sujeong Mun, Siwoo Lee
5 citations
JMIR Medical Informatics
Heart Rate Variability and Autonomic Control
6.94
article

Detection and Analysis of Circadian Biomarkers for Metabolic Syndrome Using Wearable Data: Cross-Sectional Study

Jeong-Kyun Kim, Sujeong Mun, Siwoo Lee
article en
5 citations

Abstract

This study identified CCE and relative amplitude of heart rate as key circadian rhythm biomarkers for MetS monitoring, demonstrating their high importance across multiple XAI models. In contrast, traditional sleep markers showed limited significance, suggesting that circadian rhythm analysis may offer additional insights into MetS beyond sleep-related indicators. These findings highlight the potential of wearable-based circadian biomarkers for improving MetS assessment and management.

JMIR Medical InformaticsVol. 13
Korea Institute of Oriental Medicine (KR)
Zero hunger
Openalex Percentile: Top 3%
Heart Rate Variability and Autonomic Control
6.94
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