Time-Frequency analysis of heart rate variability during transient segments

Area of Science:

• Biomedical Engineering
• Physiology
• Signal Processing

Background:

• Heart rate variability (HRV) spectral characteristics reflect autonomic nervous system (ANS) modulation.
• Physiological changes (drugs, posture, syncope) and internal deregulation can alter HRV.
• Time-frequency analysis is crucial for understanding time-varying HRV but can be confounded by transient heart rate changes.

Purpose of the Study:

• To evaluate the impact of transient heart rate components on various time-frequency analysis methods for HRV.
• To identify methods robust to spectral interference caused by heart rate fluctuations.
• To compare the performance of short-time Fourier transform, Choi-Williams distribution, SPWVD, filtering SPWVD compensation, and discrete wavelet transform.

Main Methods:

• Analysis of a simulated heart rate signal.
• Assessment of real heart rate signals during general anesthesia.
• Evaluation of heart rate signals during postural changes.
• Comparison of spectral interference across multiple time-frequency analysis techniques.

Main Results:

• Transient heart rate changes introduce spectral spread, obscuring ANS-related frequency components.
• Short-time Fourier transform, Choi-Williams distribution, and standard SPWVD showed significant interference.
• Filtering SPWVD compensation and discrete wavelet transform demonstrated minimal spectral interference.

Conclusions:

• Filtering SPWVD compensation and discrete wavelet transform are superior methods for analyzing HRV in the presence of transient heart rate alterations.
• These robust methods enhance the accurate assessment of autonomic nervous system function during dynamic physiological conditions.
• The findings are critical for reliable HRV analysis in clinical and research settings involving physiological instability.