Clinical Evidence of Wearable-Derived Heart Rate Variability for Detecting Systemic Inflammation: A Systematic Review

Area of Science:

• Biomedical Engineering
• Physiological Monitoring
• Digital Health

Background:

• Wearable devices offer continuous autonomic nervous system (ANS) assessment via heart rate variability (HRV).
• Systemic inflammation impacts ANS balance, making HRV a potential non-invasive biomarker.
• The accuracy of wearable HRV for detecting inflammation needs clarification.

Purpose of the Study:

• To systematically review the clinical relevance of wearable-derived HRV indices against established inflammatory biomarkers.
• To assess the consistency and accuracy of wearable HRV in reflecting inflammatory states.

Main Methods:

• Systematic literature search across major databases (PubMed, Scopus, Web of Science, Cochrane Library) up to April 2025.
• Synthesis Without Meta-analysis (SWiM) framework employed due to methodological heterogeneity.
• Vote counting, effect-direction plots, and sign tests used for data synthesis.

Main Results:

• Eleven studies (2419 participants) were included.
• SDNN (standard deviation of NN intervals) showed a significant inverse association with CRP (p=0.031).
• ECG-based wearables demonstrated more consistent HRV-inflammation associations than photoplethysmography (PPG) devices.

Conclusions:

• Wearable-derived HRV, especially SDNN from ECG devices, correlates inversely with CRP, indicating potential as a systemic inflammation biomarker.
• Heterogeneity and lack of diagnostic accuracy data limit current clinical utility.
• Further validation in standardized studies is required for clinical application.