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Updated: Jun 16, 2025

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions
Published on: June 5, 2019
Update: factors influencing heart rate variability-a narrative review
Stefan Sammito1,2, Beatrice Thielmann2, Irina Böckelmann2
1German Air Force Centre of Aerospace Medicine, Cologne, Germany.
Heart rate variability (HRV) is a key indicator of autonomic function. Factors like age, disease, lifestyle, and environment significantly impact HRV, affecting its interpretation and clinical relevance.
Area of Science:
- Physiology
- Autonomic Nervous System
- Health Markers
Background:
- Heart rate variability (HRV) serves as a crucial non-invasive marker for assessing autonomic physiological regulatory pathways.
- Diminished HRV is linked to increased mortality, highlighting its clinical significance.
- HRV is susceptible to a wide array of influencing factors and diseases.
Purpose of the Study:
- To provide a comprehensive overview of factors influencing HRV.
- To elucidate the significance of these factors for accurate HRV interpretation.
- To consolidate current knowledge on HRV modulation.
Main Methods:
- A narrative review approach was employed.
- Inclusion criteria focused on reviews, meta-analyses, and cohort studies published up to 2021.
- Identified HRV confounders were systematically categorized into four groups: non-influenceable physiological factors, diseases, influenceable lifestyle factors, and external factors.
Main Results:
- HRV reduction was observed across non-influenceable physiological factors (age, gender, ethnicity).
- Numerous acute and chronic diseases (e.g., psychiatric disorders, myocardial infarction, heart failure) were associated with decreased HRV.
- Influenceable lifestyle factors (alcohol abuse, overweight, physical activity) and external factors (heat, noise, shift work, hazardous substances) also demonstrated a significant impact on HRV.
Conclusions:
- Accurate interpretation of HRV necessitates consideration of numerous influencing factors.
- Future diagnostic and workplace HRV measurements should account for identified confounders to mitigate data bias.
- Integrating confounder assessment into health promotion strategies can enhance the quality and reliability of HRV studies.
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