[The spectral analysis of heart rate variability. The methodological aspects]

Area of Science:

• Cardiology
• Physiology
• Biomedical Engineering

Background:

• Cardiac cycle variability (CCV) analysis is crucial for assessing autonomic nervous system function.
• Standardized methodologies are essential for reliable CCV interpretation in both time and frequency domains.

Purpose of the Study:

• To investigate how different data analysis methodologies influence the assessment of cardiac cycle variability.
• To compare time-domain and frequency-domain CCV parameters across various analytical approaches.

Main Methods:

• RR interval variability was analyzed in 25 individuals (non-smokers, smokers, non-smokers with guided respiration).
• Time-domain (SD, CV) and frequency-domain (spectral analysis, Fast Fourier Transform with 5 data windows) analyses were performed.
• Signal averaging of RR intervals was also evaluated.

Main Results:

• Significant differences in absolute spectral amplitudes (low frequency band) were observed across different data windows (p < 0.001).
• Normalized values and low/high frequency ratios showed no significant differences between data windows.
• Signal averaging significantly altered most CCV parameters. A trend towards reduced CCV was noted in smokers compared to non-smokers.

Conclusions:

• The choice of data window in Fourier analysis significantly affects absolute CCV parameters but not normalized ones.
• Signal averaging substantially modifies CCV results, impacting data interpretation.
• Age-related decline in CCV parameters is better described by an exponential model. Smoking may be associated with reduced CCV.