Spectral methods of heart rate variability analysis during dynamic exercise.

Area of Science:

• Cardiovascular Physiology
• Exercise Science
• Biomedical Engineering

Background:

• Heart rate variability (HRV) analysis is crucial for assessing autonomic nervous system function.
• Autoregressive (AR) and Fast Fourier Transform (FFT) are common spectral analysis methods for HRV.
• Understanding the differences between AR and FFT under various physiological conditions is important for accurate interpretation.

Purpose of the Study:

• To compare AR and FFT spectral analysis of HRV at rest, during dynamic exercise, and during recovery.
• To evaluate differences in raw and normalized power spectra obtained by AR and FFT methods.
• To determine the sensitivity of each method to exercise intensity and recovery.

Main Methods:

• Sixteen healthy participants underwent resting, submaximal, and maximal exercise protocols.
• Beat-to-beat R-R interval series were recorded during rest, 5-minute walks at 4 km/h with 0% and 7.5% grades, and recovery.
• Both AR and FFT spectral analyses were performed on the same R-R interval data.

Main Results:

• FFT yielded higher total power and raw high-frequency power compared to AR at rest and during exercise.
• FFT showed a lower LF/HF ratio than AR, except at rest.
• Both methods indicated reductions in total power and raw powers during exercise and recovery, but only AR detected significant changes in normalized power spectra.

Conclusions:

• AR and FFT methods are not interchangeable for HRV analysis at rest or during dynamic exercise.
• The AR method demonstrates greater sensitivity to exercise-induced changes in normalized HRV power spectra compared to FFT.
• Neither AR nor FFT offers a practical advantage for HRV spectral analysis at higher exercise intensities.