Derivation of Frequency Components from Overnight Heart Rate Variability Using an Adaptive Variational Mode...

Area of Science:

• Cardiology
• Biomedical Engineering
• Physiology

Background:

• Heart rate variability (HRV) reflects autonomic nervous system (ANS) function.
• Traditional HRV analysis relies on spectral decomposition into frequency bands (high, low, very low, ultra-low).
• Accurate extraction of these frequency components is crucial for understanding physiological regulation.

Purpose of the Study:

• To evaluate the efficacy of Adaptive Variational Mode Decomposition (AVMD) for extracting HRV frequency components.
• To compare AVMD's performance against the established multiband filtering (MBF) method.
• To assess the clinical relevance of AVMD-derived HRV components.

Main Methods:

• AVMD was applied to extract frequency components from overnight HRV signals.
• Performance was validated using synthetically generated HRV data.
• AVMD was further tested on real HRV data from three patients.
• AVMD results were compared quantitatively and qualitatively with MBF.

Main Results:

• AVMD demonstrated superior robustness and effectiveness compared to MBF.
• AVMD showed particular advantages in extracting high and low frequency HRV components.
• The method proved reliable for deriving key HRV frequency bands.

Conclusions:

• AVMD is a reliable and effective method for extracting HRV frequency components.
• This technique offers improved analysis of ANS activity through HRV.
• The extracted components provide valuable insights into physiological regulatory processes.